{"paper_id":"06c41d92-649c-4e04-ae1f-74307c0ad1d9","body_text":"1\nIdentification of an endocannabinoid gut-brain vagal mechanism controlling 1 \nfood reward and energy homeostasis 2 \n 3 \n 4 \nChloé Berland1, Julien Castel1, Romano Terrasi2, Enrica Montalban1, Ewout 5 \nFoppen1, Claire Martin1, Giulio G. Muccioli2, Serge Luquet1, Giuseppe Gangarossa1 6 \n 7 \n 8 \n 9 \n 10 \n 11 \n1 Université de Paris, BFA, UMR 8251, CNRS, F-75013 Paris, France 12 \n2 Bioanalysis and Pharmacology of Bioactive Lipids Research Group, Louvain Drug 13 \nResearch Institute, Université catholique de Louvain, 1200 Brussels, Belgium 14 \n 15 \n 16 \n 17 \n 18 \nCorrespondence to: giuseppe.gangarossa@u-paris.fr (GG, @PeppeGanga)  19 \n 20 \n 21 \n 22 \nRunning title: Peripheral endocannabinoids gate reward feeding and homeostasis  23 \n 24 \n 25 \n 26 \nKey words: binge eating, dopamine, 2-AG, vagus nerve, striatum, reward, 27 \nmetabolism   28 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 2\nAbstract (234)  29 \nThe regulation of food intake, a sine qua non requirement for survival, thoroughly 30 \nshapes feeding and energy balance by integrating both homeostatic and hedonic 31 \nvalues of food. Unfortunately, the widespread access to palatable food has led to the 32 \ndevelopment of feeding habits that are independent from metabolic needs. Among 33 \nthese, binge eating (BE) is characterized by uncontrolled voracious eating. While 34 \nreward deficit seems to be a major contributor of BE, the physiological and molecular 35 \nunderpinnings of BE establishment remain elusive. Here, we combined a 36 \nphysiologically relevant BE mouse model with multiscale in vivo  approaches to 37 \nexplore the functional connection between the gut-brain axis and the reward and 38 \nhomeostatic brain structures.  39 \nOur results show that BE elicits compensatory adaptations requiring the gut-to-brain 40 \naxis which, through the vagus nerve, relies on the permissive actions of peripheral 41 \nendocannabinoids (eCBs) signaling. Selective inhibition of peripheral CB1 receptors 42 \nresulted in a vagus-dependent increased hypothalamic activity, modified metabolic 43 \nefficiency, and dampened activity of mesolimbic dopamine circuit, altogether leading 44 \nto the suppression of palatable eating. We provide compelling evidence for a yet 45 \nunappreciated physiological integrative mechanism by which variations of peripheral 46 \neCBs control the activity of the vagus nerve, thereby in turn gating the additive 47 \nresponses of both homeostatic and hedonic brain circuits which govern homeostatic 48 \nand reward-driven feeding.  49 \nIn conclusion, we reveal that vagus-mediated eCBs/CB1R functions represent an 50 \ninteresting and innovative target to modulate energy balance and counteract food-51 \nreward disorders.  52 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 3\nIntroduction 53 \n 54 \nFeeding is a complex and highly conserved process whose orchestration results from 55 \nthe dynamic integration of interoceptive and exteroceptive signals. The homeostatic 56 \nand hedonic components of feeding have been attributed to the hypothalamus and 57 \nthe dopamine (DA) reward system, respectively [1]. While the firsts can be broadly 58 \ndefined as key regulators of food intake to ensure optimal energy balance, the 59 \nseconds mainly relate to the reinforcing properties of sensory stimuli (perception, 60 \ncues, taste, odors) and reward-associated features of feeding. However, despite the 61 \nwell-accepted recognition that both feeding components are tightly and functionally 62 \ninterconnected [1], they are usually investigated as isolated systems. In addition, the 63 \ncounterpointing central vs peripheral regulations of feeding add a supplemental 64 \ndegree of complexity in the identification of integrative regulatory mechanisms [2].    65 \nWhile energy homeostasis refers to negative feedback mechanisms maintaining 66 \nbody weight at set-points, the combination of both homeostatic and hedonic 67 \ncomponents of feeding leads to the establishment of feed-forward mechanisms of 68 \nphysiological adaptations. Feed-forward adaptation, also known as allostasis 69 \n(stability through changes), is critical for energy balance and metabolic efficiency [3] 70 \nbut also contributes to reward-associated events [4]. Indeed, the widespread 71 \navailability and consumption of palatable diets have profoundly altered the delicate 72 \nallostatic integration of homeostatic and hedonic signals, leading to the development 73 \nof metabolic disorders. This is particularly evident in food reward-driven dysfunctions 74 \nsuch as binge eating (BE), where uncontrolled feeding perfectly recapitulates the 75 \nefforts for an organism to adapt its homeostatic processes to the hedonic aspects of 76 \nfeeding. In fact, short- and/or long-term consumptions of energy-rich palatable diets 77 \nremodel the DA reward system [5] and promote functional adaptations within the 78 \nhypothalamus [6–8]. Beyond these two core processors of feeding, recent reports 79 \nhave mechanistically demonstrated that the gut-brain vagal axis, besides sensing 80 \ninteroceptive signals and influencing feeding and energy homeostasis [9–11], is also 81 \na major modulator of the reward system [12–14]. However, the physiological 82 \nprocesses by which the gut-to-brain axis modulates reward feeding remain unclear. 83 \nEmerging evidence strongly suggest that, besides a plethora of peripheral hormones 84 \n(i.e. ghrelin, leptin, GLP-1, CCK), peripheral endocannabinoids (eCBs) may be 85 \nfundamental players in the regulation of feeding and metabolic efficiency [15–17]. 86 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 4\nIndeed, eating disorders-associated alterations in peripheral eCBs have been 87 \nreported in obese and BE patients [18, 19] as well as in diet-induced obese rodents 88 \n[15, 20]. However, whether and how peripheral eCBs play a permissive role in 89 \nguiding reward-based feeding behaviors and in buffering the allostatic regulation of 90 \nenergy balance is unexplored. 91 \nTo tackle this question, we took advantage of a physiologically relevant BE-92 \nlike mouse paradigm which, by promoting anticipatory and escalated consummatory 93 \nfood responses, triggers reward-driven behavioral, molecular and allostatic 94 \nadaptations. Binge eating, which elicited DA-dependent molecular modifications in 95 \nthe reward-related structures [dorsal striatum (DS) and nucleus accumbens (NAc)], 96 \nrevealed an unappreciated integrative gut-to-brain orchestration requiring the 97 \nmodulatory actions of peripheral eCBs. In particular, we show that BE requires an 98 \norchestrated dialog between peripheral eCBs and both central hypothalamic and 99 \nVTA structures through the gut-brain vagal axis, thus modulating both energy 100 \nbalance and reward-like events.   101 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 5\nMaterial and methods 102 \nSee Suppl. Material  for the detailed description of materials, methods and 103 \ntechniques, and experimental sizes used in the whole study.   104 \n 105 \nAnimals 106 \nAll experiments were approved by the Animal Care Committee of the Université de 107 \nParis (CEB-25–2016) and carried out following the 2010/63/EU directive. 8-12 weeks 108 \nold male and/or female C57Bl/6J mice (Janvier, Le Genest St Isle, France) were 109 \nsingle-housed one week prior to any experimentation in a room maintained at 22 +/-1 110 \n°C, with light period from 7 AM to 7 PM. Regular chow diet (3 438 kcal/kg, protein 111 \n19%, fat 5%, carbohydrates 55%, of total kcal, reference #U8959 version 63 Safe, 112 \nAugy, France) and water were provided ad libitum . Drd2-Cre mice [Tg(Drd2-cre) 113 \nER44Gsat/Mmucd, Jackson laboratory] were used for in vivo fiber photometry Ca 2+ 114 \nimaging in the VTA. Drd2 -eGFP mice [Tg(Drd2-eGFP)S118Gsat/Mmnc] were 115 \ngenerated by GENSAT at the Rockefeller University. See Suppl. Material for further 116 \ndetails.   117 \n 118 \nBehaviors  119 \nPalatable binge eating-like paradigm. Intermittent daily access to a palatable mixture 120 \n(Intralipid 20% w/v + sucrose 10% w/v) was provided for 1-hour/day during 10-14 121 \nconsecutive days at 10-11 AM in home-cages. During time-locked binge sessions 122 \nregular chow pellets were not removed. Volume (mL) of consumed palatable mixture 123 \nwas measured at the end of the session.  124 \nLocomotor activity. Spontaneous and/or induced locomotor activities were measured 125 \nusing an infrared beam-based activity monitoring system (Phenomaster, TSE 126 \nSystems GmbH, Germany). 127 \nTail suspension. To record the activity of GCaMP6f-expressing VTA neurons, mice 128 \nwere suspended above the ground by their tails. Ca 2+ imaging was performed before 129 \nand during tail suspension.  130 \nExploratory drive in a new environment . To record the activity of GCaMP6f-131 \nexpressing VTA neurons in a novelty-induced exploratory drive, mice were put in a 132 \nnew environment (NE) consisting in a novel cage. Ca 2+ imaging was performed 133 \nbefore and immediately after changing the environment. See Suppl. Material  for 134 \nfurther details.   135 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 6\n 136 \nMetabolic efficiency analysis  137 \nMice were monitored for whole energy expenditure (EE), O 2 consumption, CO 2 138 \nproduction, respiratory exchange rate (RER=VCO 2/VO2, V=volume), and locomotor 139 \nactivity using calorimetric cages (Labmaster, TSE Systems GmbH, Bad Homburg, 140 \nGermany). Ratio of gases was determined through an indirect open circuit 141 \ncalorimeter. This system monitors O 2 and CO 2 at the inlet ports of a tide cage 142 \nthrough which a known flow of air is ventilated (0.4 L/min) and regularly compared to 143 \na reference empty cage. O 2 consumption and CO 2 production were recorded every 144 \n15 min during the entire experiment. EE was calculated using the Weir equation for 145 \nrespiratory gas exchange measurements. Food intake was measured with highly 146 \nsensitive sensors for automated online measurements. Mice had access to food and 147 \nwater ad libitum. Mice were monitored for body weight and composition at the entry 148 \nand exit of the experiment using an EchoMRI (Whole Body Composition Analyzers, 149 \nEchoMRI, Houston, USA). Data analysis was performed on Excel XP using extracted 150 \nraw values of VO2, VCO2 (mL/h), and EE (kcal/h). 151 \n 152 \nBrown adipose tissue and telemetry body temperature measurements 153 \nInfrared camera for BAT temperature . Heat production was visualized using a high-154 \nresolution infrared camera (FLIR E8; FLIR Systems, Portland, OR, USA). To 155 \nmeasure brown adipose tissue (BAT) temperature, images of interscapular regions 156 \nwere captured before and after binge sessions. Infrared thermography was analyzed 157 \nusing the FLIR TOOLS.  158 \nTelemetry body temperature. Anesthetized mice were implanted with a the telemetric 159 \ntransmitter (HD-XG; Data Sciences International) to measure longitudinal fluctuations 160 \nof core temperature. They were allowed to recover at 35°C and received a daily 161 \ninjection of ketoprofen (Ketofen® 10%) for 3 days. During a 7-days recovery period, 162 \nmice were monitored and had facilitated access to food. Data were collected using 163 \nthe Ponemah® software (DSI). The detection of transmitted signals was 164 \naccomplished by a radio receiver (body temperature and locomotor activity) and 165 \nprocessed by a microcomputer system. 166 \n 167 \nTissue preparation and immunofluorescence 168 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 7\nMice were anaesthetized with pentobarbital (500 mg/kg, i.p., Sanofi-Aventis, France) 169 \nand transcardially perfused with 4°C PFA 4% for 5 minutes. Sections were processed 170 \nas previously described [21]. Quantification of immunopositive cells was performed 171 \nusing the cell counter plugin of ImageJ software taking a fixed threshold of 172 \nfluorescence as standard reference. See Suppl. Material for further details and list of 173 \nantibodies.     174 \n 175 \nWestern blotting and quantitative RT-PCR 176 \nAt the end of the binge session, the mouse head was cut and immediately immersed 177 \nin liquid nitrogen for 3 seconds. Brains and sampled structures were processed as 178 \npreviously described [21]. Quantifications were performed using ImageJ software. 179 \nSee Suppl. Material for further details, list of antibodies and primers. 180 \n 181 \nDrug treatments  182 \nThe following compounds were used: insulin (0.5 U/kg, Novo Nordisk), CCK-8S (10 183 \nug/kg, Tocris), liraglutide (100 ug/kg, gift from Novo Nordisk), exendin 4 (10 ug/kg, 184 \nTocris), leptin (twice/day for 2 days at 0.25 mg/kg, Tocris), AM251 (3 mg/kg, Tocris), 185 \nAM6545 (10 mg/kg, Tocris), JD-5037 (3 mg/kg, MedChemExpress), SKF81297 (5 186 \nmg/kg, Tocris), haloperidol (0.25 and 0.5 mg/kg, Tocris), SCH23390 (0.1 mg/kg, 187 \nTocris), GBR12909 (10 mg/kg, Tocris), d-amphetamine sulphate (2 mg/kg, Tocris), 188 \nJZL184 (8 mg/kg, Tocris). See Suppl. Material for further details. 189 \n 190 \nSubdiaphragmatic vagotomy  191 \nPrior to surgery and during 3 post-surgery days, animals were provided with ad 192 \nlibitum jelly food (DietGel Boost #72-04-5022, Clear H 2O) to avoid the presence of 193 \nsolid food in the gastrointestinal tract. Animals received Buprécare® (Buprenorphine 194 \n0.3 mg) and Ketofen® (100 mg) and were anaesthetized with isoflurane (3.5% for 195 \ninduction, 1.5% for maintenance). Body temperature was maintained at 37°C. Briefly, 196 \nusing a binocular microscope, the right and left vagus nerve branches were carefully 197 \nisolated along the esophagus and sectioned in vagotomized (VGX) animals or left 198 \nintact in sham animals. Mice recovered for at least 3 weeks before being used for 199 \nexperimental procedures. See Suppl. Material for further details.    200 \n 201 \nQuantification of eCBs by UHPLC-MS/MS  202 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 8\nLipids were extracted by liquid/liquid extraction in the presence of deuterated 203 \nstandards. They were then purified by SPE to obtain a fraction containing eCB and 204 \nNAE that were analyzed by UHPLC-MS/MS using a Xevo TQ-S (ESI source; positive 205 \nmode). For each analyte, the signal (AUC) of the relevant internal standard was used 206 \nfor normalization. See Suppl. Material for further details.    207 \n 208 \nViral production 209 \npAAV.Syn.Flex.GCaMP6f.WPRE.SV40 (titer ≥  1×10 13 vg/ml, working dilution 1:5) 210 \nwas a gift from Douglas Kim (Addgene viral prep #100833-AAV9; 211 \nhttp://n2t.net/addgene:100833; RRID:Addgene_100833).  212 \npAAV5-hSyn-dLigh1.2 (titer ≥  4×10¹² vg/mL) was a gift from Lin Tian (Addgene viral 213 \nprep #111068-AAV5; http://n2t.net/addgene:111068; RRID:Addgene_111068). 214 \n 215 \nStereotaxic procedure  216 \nMice were anaesthetized with isoflurane, administered with Buprécare® 217 \n(Buprenorphine 0.3 mg) and Ketofen® (Ketoprofen 100 mg), and placed on a 218 \nstereotactic frame (Model 940, David Kopf Instruments, California). 219 \npAAV.Syn.Flex.GCaMP6f.WPRE.SV40 (0.3 μ l) was injected unilaterally into the VTA 220 \n(L=−0.5; AP=−3.4; V=−4.4, mm) of Drd2-Cre mice at a rate of 0.05 μ l/min.  221 \npAAV5-hSyn-dLight1.2 (0.5 μ l) was injected unilaterally into the NAc (L=−0.75; 222 \nAP=1.18; V=−4.4, mm) of C57BL6/J male and female mice at a rate of 0.05 μ l/min.  223 \nThe injection needle was carefully removed after 5 minutes waiting at the injection 224 \nsite and 2 minutes waiting halfway to the top. Optical fiber for Ca 2+ (VTA) and 225 \ndopamine (NAc) imaging was implanted 100 μ m above the viral injection site. 226 \nAnimals were tested 4 weeks after viral stereotaxic injections.    227 \n 228 \nFiber photometry and data analysis 229 \nA chronically implantable cannula (Doric Lenses, Québec, Canada) composed of a 230 \nbare optical fiber (400 μ m core, 0.48 N.A.) and a fiber ferrule was implanted 100 μ m 231 \nabove the location of the viral injection site in the VTA or in the NAc. The fiber was 232 \nfixed onto the skull using dental cement (Super-Bond C&B, Sun Medical). Real-time 233 \nfluorescence signals emitted by GCaMP6f or the DA biosensor dLight1.2 [22] were 234 \nrecorded and analyzed as previously described [21]. Fluorescence was collected 235 \nusing a single optical fiber for both delivery of excitation light streams and collection 236 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 9\nof emitted fluorescence. The fiber photometry setup used 2 light-emitting LEDs: 405 237 \nnm LED sinusoidally modulated at 330 Hz and a 465 nm LED sinusoidally modulated 238 \nat 533 Hz merged in a FMC4 MiniCube (Doric Lenses) that combines the 2 239 \nwavelengths excitation light streams and separate them from the emission light. The 240 \nMiniCube was connected to a Fiberoptic rotary joint connected to the cannula. A 241 \nRZ5P lock-in digital processor controlled by the Synapse software (Tucker-Davis 242 \nTechnologies, TDT, USA), commanded the voltage signal sent to the emitting LEDs 243 \nvia the LED driver (Doric Lenses). Data are presented as z-score of Δ F/F. See 244 \nSuppl. Material for further details.    245 \n 246 \nStatistics  247 \nAll data are presented as mean ± SEM. Statistical tests were performed with Prism 7 248 \n(GraphPad Software, La Jolla, CA, USA). The detailed statistical analyses are listed 249 \nin the Suppl. Table 1. Normality was assessed by the D’Agostino-Pearson test. 250 \nDepending on the experimental design, data were analyzed using either Student t-251 \ntest (paired or unpaired) with equal variances, One-way ANOVA or Two-way 252 \nANOVA. In all cases, the significance threshold was automatically set at p < 0.05. 253 \nANOVA analyses were followed by Bonferroni post hoc test for specific comparisons 254 \nonly when overall ANOVA revealed a significant difference (at least p < 0.05). 255 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 10\nResults  256 \n 257 \nTime-locked access to palatable diet induces adaptation of nutrient partitioning 258 \nand metabolic efficiency  259 \nSeveral paradigms of bingeing are widely used to model eating disorders [23]. 260 \nHowever, the majority of these paradigms mainly rely on ( i) prior alterations of basal 261 \nhomeostasis (food or water restriction/deprivation, stress induction), (ii) dietary 262 \nexposure to either high-sugar or high-fat foods, or (iii) absence of food choice during 263 \nbingeing periods. We therefore adapted existing protocols to better study reward and 264 \nhomeostatic components of food intake during binge eating (BE). Since dietary 265 \nmixtures of fat and sugar lead to enhanced food reward properties [24], we designed 266 \na highly palatable diet (sugar and fat) to promote intense reward-driven feeding. 267 \nTime-locked access to this palatable diet was sufficient to drive escalating binge-like 268 \nconsumption without restricting access to chow diet ( Fig. 1A). In that regard, we are 269 \nconfident that this model is preferentially driven by reward values over metabolic 270 \ndemands since animals are neither food nor water restricted. 271 \nMale mice intermittently exposed to this dietary palatable mixture maximized their 272 \nintake within a few days ( Fig. 1B ). This palatable food consumption was 273 \nsimultaneously associated with an increased anticipatory locomotor activity ~2 hours 274 \nbefore food access and lasted for another ~1-2 hours ( Fig. 1C, C1), with no changes 275 \nin the ambulatory activity during the dark phase (Fig. 1C ). The same animals were 276 \ncharacterized by a significant reduction in spontaneous nocturnal food intake ( Fig. 277 \n1D, D1). However, the overall caloric intake [standard diet (SD) + palatable food (PF)] 278 \nremained similar to controls, thus indicating a conserved maintenance in calories 279 \nconsumption despite reward-driven food intake (Fig. 1E ). Importantly, isocaloric 280 \nfeeding was associated with conserved body weight (BW) and body composition 281 \n(Fig. 1F, Suppl. Fig. 1A, B). A similar pattern of food reward-driven adaptations was 282 \nalso observed in female mice (Suppl. Fig. 1C-E).  283 \nNext, we investigated the consequences of BE on metabolic efficiency. Indirect 284 \ncalorimetry analysis revealed an increase in the respiratory exchange ratio (RER) 285 \nbefore and after intermittent palatable food consumption ( Fig. 1G, G1), whilst a stark 286 \nreduction was detected in the dark phase (Fig. 1G ), thereby highlighting a metabolic 287 \nshift of energy substrates use (from carbohydrates to lipids as indicated by RER ~1 288 \nor RER ~0.7, respectively). This was further confirmed by the modulation of fatty acid 289 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 11\noxidation (FAO, Suppl. Fig. 1F). In addition, we also observed an increased energy 290 \nexpenditure (EE) during the food anticipatory and consummatory phases ( Fig. 1H, 291 \nH1). Furthermore, infrared thermographic analysis revealed that BE was associated 292 \nwith a transient increase in brown adipose tissue (BAT) energy dissipation ( Fig. 1I), 293 \nwhile telemetric recording of core body temperature revealed a BE-specific increase 294 \nduring the anticipatory, consummatory and post-prandial phases ( Fig. 1J, J1, Suppl. 295 \nFig. 1G ) and a sharp reduction during the last hours of the dark phase. Overall, 296 \nchanges in core body temperature were fostered around the time of locked palatable 297 \nfood access and overlapped with the increase in locomotor activity (Fig. 1J, K).  298 \nAccess to calories-rich food and time-restricted feeding are invariably associated with 299 \nchanges in circulating signals reflecting metabolic and behavioral adaptations [25]. In 300 \nline with this, we observed that our BE model was associated with reduced 301 \ncirculating triglycerides and insulin, and increased circulating corticosterone during 302 \nthe anticipatory phase ( Suppl. Fig. 1H-J ) while insulin sensitivity, as assessed by 303 \noral glucose tolerance test, remained unchanged ( Suppl. Fig. 1K, L ). These data 304 \nindicate that homeostatic adaptations occurring during time-locked palatable feeding 305 \nlead to changes in lipid-substrates utilization and promote adaptive activation of the 306 \nhypothalamic-pituitary-adrenal (HPA) axis. However, bingeing did not elicit major 307 \nchanges in the expression of key hunger- and satiety-related hypothalamic genes 308 \n(Npy, Agrp, Pomc, Cart, Hcrt, Suppl. Fig. 1M).    309 \nOverall, these results point to rapid reward-driven allostatic adaptations during which 310 \nanimals optimize their palatable food consumption and physiologically adapt, at the 311 \ncost of regular chow food intake, to maintain a stable body weight.  312 \n  313 \nBE induces dopamine-related modifications in a D1R-dependent manner 314 \nDopamine (DA)-neurons and DA-sensitive structures, such as the dorsal striatum 315 \n(DS) and the nucleus accumbens (NAc), are critical players in reward-based 316 \nparadigms and in BE disorders [26, 27]. Here, we investigated whether and how 317 \nbingeing modulated the DA-associated signaling machinery. The activations 318 \n(phosphorylation) of the ribosomal protein S6 and the extracellular signal-regulated 319 \nkinases (ERK) were used as functional readouts of DA-dependent molecular activity 320 \n[28, 29] ( Suppl. Fig. 2A, B ). The food anticipatory phase was associated with an 321 \nincrease in phospho-ERK only in the DS ( Fig. 2A, B, Suppl. Fig. 2C ), mostly 322 \nreflecting the increased locomotor activity during the anticipatory phase. Palatable 323 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 12\nfood consumption induced an increase in phospho-ERK and phospho-S6 (at both 324 \nSer235/236 and Ser 240/244 sites) in both DS and NAc ( Fig. 2A, B, Suppl. Fig. 2C). 325 \nInterestingly, acute (single) consumption of palatable diet failed to trigger ERK and 326 \nS6 activation ( Fig. 2A, B, Suppl. Fig. 2C), revealing that molecular adaptations of 327 \nDA signaling in the DS/NAc require the full establishment of BE and not only 328 \npalatable food consumption. Immunofluorescence analysis further confirmed BE-329 \ninduced S6 activation (Suppl. Fig. 2D, E).    330 \nNext, we wondered whether food-reward anticipatory and/or consummatory 331 \nphases were followed by adaptive changes in DA signaling. We treated mice with 332 \nGBR12909 (10 mg/kg), a specific DA transporter (DAT) blocker that leads to synaptic 333 \naccumulation of DA. Interestingly, we observed a different behavior depending on BE 334 \nphases (anticipatory vs consummatory). Before palatable food access, GBR similarly 335 \nincreased locomotor activity in both bingeing and control animals ( Fig. 2C, C 1). 336 \nHowever, when GBR was administered following palatable food consumption (1h), 337 \nGBR-induced locomotor response was blunted in bingeing animals ( Fig. 2D, D 1). 338 \nThese results indicate that BE-induced physiological adaptations are characterized 339 \nby the enabled ability for palatable food to impinge on DA release and action.  340 \nAt the postsynaptic level, DA acts onto medium spiny neurons (MSNs) which express 341 \neither the dopamine D1R or D2R. In order to discriminate the role of D1R vs D2R 342 \nsignaling in BE, we pretreated animals with the D1R antagonist SCH23390 (0.1 343 \nmg/kg) or vehicle (Veh) 30 min prior access to palatable diet. SCH23390 dramatically 344 \nreduced palatable food consumption (Fig. 2E). On the contrary, 30 min pretreatment 345 \nwith the D2R antagonist haloperidol (0.25 and 0.5 mg/kg) did not dampen palatable 346 \nfood consumption (Fig. 2F), even at cataleptic doses [30]. In line with this evidence, 347 \nactivation of striatal D1R leads to downstream phosphorylation of S6 and ERK [28, 348 \n29]. The adaptive molecular changes also required D1R activation since SCH23990 349 \n(0.1 mg/kg) largely suppressed BE-associated phosphorylation of S6 in both DS (Fig. 350 \n2G, G1, H1) and NAc ( Fig. 2G2, H 2, Suppl. Fig. 2F ). Of note, although SCH23390 351 \nreduced binge-elicited anticipatory locomotor activity, basal locomotor activity in 352 \nnaive animals was not impaired (Fig. 2I, I 1), thereby excluding the confounding 353 \neffects due to changes in basal locomotor activity. Furthermore, a compensatory 354 \nrescue in chow intake was observed in SCH23390-pretreated bingeing animals 355 \nduring the dark phase, excluding potential long-lasting effects of the D1R inhibition 356 \n(Fig. 2J). To further validate the implication of D1R in BE-elicited DA modifications, 357 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 13\nwe measured the locomotor activity triggered by the D1R agonist SKF81297 (5 358 \nmg/kg) at the end of the BE session (1h after food access). Interestingly, we 359 \nobserved an earlier (first 30 min) significant increase in locomotor activity in bingeing 360 \nanimals compared to control mice, although no major differences were detected 361 \nduring the cumulative 2-hrs response (Fig. 2K, K1).  362 \nOverall, our results reveal that the critical phases surrounding palatable food 363 \nconsumption in the context of BE profoundly affect D1R-associated signaling. 364 \n  365 \nPeripheral endocannabinoids govern binge eating 366 \nRecent studies have highlighted the role of neuronal and endocrine gut systems in 367 \nthe regulation of food reward-seeking and DA-associated behaviors [31, 32]. We 368 \ntherefore tested whether gut-born metabolic signals had a privileged action onto BE-369 \nlike consumption of palatable diet when compared to other known circulating satiety 370 \nsignals.  371 \nFirst, we observed that peripherally injected leptin (repeated 0.25 mg/kg, Suppl. Fig. 372 \n3A, B ) or insulin (acute, 0.5 U/kg) did not trigger any reduction in palatable food 373 \nconsumption when administered in bingeing animals (Fig. 3A). Then, we investigated 374 \nwhether gut-born satiety signals retained anorectic properties with a similar protocol. 375 \nGLP-1R agonists, exendin-4 (10 µg/kg) and liraglutide (100 µg/kg), successfully 376 \nreduced binge-consumption of palatable diet ( Fig. 3A). Moreover, pharmacological 377 \nactivation of GLP-1R, which did not alter spontaneous ambulatory activity, was also 378 \nassociated with a decrease in the anticipatory and consummatory locomotor phases 379 \n(Suppl. Fig. 3C, D ). Similarly, the cholecystokinin (CCK) analog CCK-8S (10 µg/kg) 380 \nacutely decreased palatable food intake ( Fig. 3A). Since only the anorectic action of 381 \ngut-born signals was efficient in counteracting binge-like consumption, we also 382 \ninvestigated the effect of endocannabinoids (eCBs) which are important signals in 383 \nrelaying nutrients-induced adaptive responses in the gut-brain axis [33, 34]. We 384 \nacutely inhibited the CB1R with the global acting antagonist/inverse agonist AM251 385 \n(3 mg/kg, i.p.) and observed a dramatic reduction of BE-like consumption ( Fig. 3A). 386 \nNext, we wondered whether bingeing was accompanied by alterations in circulating 387 \nperipheral eCBs [anandamide (AEA) and 2-arachidonoylglycerol (2-AG)] and eCBs-388 \nrelated species [docosahexanoyl ethanolamide (DHEA), oleoylethanolamide (OEA)]. 389 \nWhile circulating N-acylethanolamines (AEA, DHEA, OEA) remained unaffected, 390 \nbingeing induced a significant increase in circulating 2-AG ( Fig. 3B). No differences 391 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 14\nin central 2-AG levels were detected in key brain regions such as the hypothalamus, 392 \nVTA, DS and NAc (Suppl. Fig. 4A-D).   393 \nGiven the rise in peripheral 2-AG, we were eager to explore the role of peripheral 394 \nCB1R signaling in BE outputs. Thus, we used the bona fide peripherally restricted 395 \nCB1R neutral antagonist AM6545 (10 mg/kg, i.p.) or inverse agonist JD-5037 (3 396 \nmg/kg, i.p.), two compounds with poor blood brain barrier permeability [35–37]. 397 \nPretreatment (1h before bingeing) with AM6545 or JD-5037 induced a stark reduction 398 \nof BE consumption when administered acutely (Fig. 3C). Conversely, the increase of 399 \n2-AG, achieved through the pharmacological inhibition (JZL184, 8 mg/kg) of its 400 \ncatabolic enzyme monoacylglycerol lipase (MAGL) [38], resulted in an increase of 401 \npalatable food consumption that was fully prevented by AM6545 ( Fig. 3D ). This 402 \nbidirectional modulatory action of eCBs/CB1R on BE did not show signs of 403 \ndesensitization and remained efficient throughout 4 days of daily pharmacological 404 \nintervention (Fig. 3E). In the same line, thermogenic and locomotor activity analyses 405 \nrevealed that acute pretreatment with AM6545 strongly dampened both the 406 \nanticipatory and consummatory phases of BE ( Fig. 3F, Suppl. Fig. 4E ) as well as 407 \nthe activation of S6 and cFos in the DS and NAc of bingeing mice ( Fig. 3G) with no 408 \nsex-dependent differences ( Suppl. Fig. 4F ). These results indicate that peripheral 409 \nCB1R signaling is sufficient to control compulsive eating in BE and its reward-like 410 \nmolecular adaptations.  411 \n 412 \n We next explored how peripheral CB1R signaling modulates metabolic 413 \nefficiency in the context of BE. Pretreatment with AM6545 significantly increased fatty 414 \nacid oxidation (FAO) ( Fig. 3H, H 1). Importantly, this AM6545-induced FAO did not 415 \ndepend on reduced calorie intake (Binge session) or basal calorie contents (NoBinge 416 \nsession) (Fig. 3H2) nor on altered energy expenditure (EE) ( Suppl. Fig. 4G). These 417 \nresults indicate that acute manipulation of peripheral eCB tone affects nutrient 418 \npartitioning and promotes a shift towards whole body lipid-substrate utilization. 419 \nImportantly, oral administration (p.o.) of AM6545 did not blunt bingeing responses 420 \n(Fig. 3I) nor increase FAO ( Fig. 3J). These results suggest that, in our behavioral 421 \nmodel, CB1R-mediated homeostatic adaptations do not depend on the lumen-422 \noriented apical CB1R of endothelial or enteroendocrine intestinal cells [39, 40] but 423 \nrather on non-lumen-oriented CB1R.  424 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 15\nGiven these results, we investigated the anatomo-functional structures at the 425 \ninterface between peripheral and central systems. Compared to control and bingeing 426 \nmice, AM6545-pretreated bingeing mice showed a more pronounced neuronal 427 \nactivation in the caudal nucleus tractus solitarius (cNTS) and the area postrema (AP) 428 \n(Fig. 3K) as well as in the cNTS-projecting lateral parabrachial nucleus (lPBN) ( Fig. 429 \n3L), thus pointing the gut-brain vagal axis as potential mediator of our effects.   430 \n 431 \nThe gut-brain vagal axis is required for eCBs-mediated effects   432 \nRecent reports have indicated that CB1R is densely expressed in vagal afferent 433 \nneurons [41]. To discriminate between all vagal afferents, we performed a meta-434 \nanalysis on recent single-cell transcriptomic results [9] obtained through a path-435 \nspecific viral strategy of gut segments ( Fig. 4A). This analysis revealed that Cnr1 436 \n(gene encoding for CB1R), but not Cnr2, is highly enriched in all segments of the gut-437 \nbrain vagal axis ( Fig. 4B, Suppl. Fig. 4H, I ) and that, together with well-known 438 \nafferent markers (Slc17a6 , Scn10a, Htr3a, Cartpt, Grin1, Phox2b), Cnr1 may be 439 \nconsidered as a constitutive marker of vagal sensory neurons. Thus, we took 440 \nadvantage of subdiaphragmatic vagotomy (VGX) to investigate whether the eCBs-441 \nvagus axis was necessary/sufficient to mediate the modulatory effects of eCBs on 442 \nBE.  443 \nFirst, we tested whether the pro-bingeing effects of the MAGL inhibitor JZL184 ( Fig. 444 \n3D, E) required an intact vagal transmission. Although vagotomy per se  was 445 \nassociated with a decrease in time-locked hedonic feeding (see Fig. 4C, E ) and 446 \nconsequent BE-derived compensatory homeostatic adaptations ( Suppl. Fig. 5 ), 447 \nrepeated inhibition (4 days) of MAGL (JZL184, 8 mg/kg) induced a significant 448 \nincrease of palatable food consumption only in sham animals (Fig. 4C). 449 \nSecond, we tested whether the anti-bingeing effects of AM6545 were also routed by 450 \nthe vagus nerve. In sham mice, acute AM6545 led to a strong increase of cFos-451 \npositive neurons in the cNTS, AP and cNTS-projecting lPBN, while the signal was 452 \nabolished in VGX mice (Fig. 4D, D 1, D2). Of note, blockade of peripheral CB1R did 453 \nnot activate the rostral NTS (rNTS) (Suppl. Fig. 4J), thus indicating and further 454 \nconfirming that gut-to-brain vagal inputs are necessary to mediate the action of 455 \nAM6545.     456 \nWe also observed that the integrity of the vagus nerve was essential to mediate the 457 \nanorectic action of AM6545 on BE behavior since the peripheral CB1R antagonist did 458 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 16\nnot trigger anti-bingeing responses in VGX mice compared to sham mice ( Fig. 4E). 459 \nFurthermore, vagotomy abolished the increase in FAO following AM6545 460 \nadministration observed in sham mice ( Fig. 4F, F 1, G, G 1), indicating that the gut-461 \nbrain vagal communication routes feeding and the metabolic components associated 462 \nwith BE.  463 \nThese vagus-dependent homeostatic adaptations promoted by the peripheral 464 \nblockade of CB1R prompted us to investigate whether AM6545 was able to alter the 465 \nactivity of brainstem-projecting hypothalamic structures that control feeding. Indeed, 466 \nAM6545 induced a strong vagus-dependent increase of cFos-positive neurons in the 467 \nPVN and DMH regions (Fig. 4H, I), indicating that the metabolic adaptations induced 468 \nby peripheral blockade of CB1R require a vagus-mediated 469 \ncNTS→ PBN→ hypothalamus circuit whose nodes’ activation control feeding and 470 \nenergy homeostasis [42–44].      471 \n 472 \nPeripheral CB1R signaling routed by the vagus nerve controls the activity of 473 \nVTA dopamine neurons 474 \nPalatable bingeing also strongly relies on central DA-dependent mechanisms ( Fig. 475 \n2). Therefore, we explored the functional connection between peripheral eCBs and 476 \nthe gut-to-brain vagal axis in the modulation of the DA system. Since 477 \nhedonic/motivated spontaneous feeding is blunted in AM6545-treated mice ( Fig. 3, 478 \n4), a feature limiting further in vivo investigations of DA/reward events, we promoted 479 \nand gauged the activity of the DA system by using pharmacological tools. Naive mice 480 \nwere acutely pretreated with AM6545 (or JD-5037) or vehicle 1h before being 481 \nadministered with the DAT blocker GBR12909. Blockade of peripheral CB1R 482 \ndrastically reduced GBR-induced locomotor activity ( Fig. 5A, A 1, B, B 1) as well as 483 \nGBR-triggered cFos in the striatum ( Fig. 5C, C 1). To further study in vivo  DA 484 \ndynamics, we took advantage of the virally expressed DA biosensor dLight1.2 485 \ncoupled to in vivo  fiber photometry [22]. Importantly, pretreatment with AM6545 486 \nblunted GBR-evoked accumbal DA accumulation (Fig. 5D, D 1). Interestingly, unlike 487 \nthe brain penetrant CB1R antagonist/inverse agonist AM251, the peripheral AM6545 488 \nfailed in counteracting amphetamine-induced locomotor activity ( Fig. 5E, F, Suppl. 489 \nFig. 6A). This evidence indicates a clear difference in the action of peripheral vs 490 \ncentral CB1R and suggests that inhibition of peripheral CB1R may modulate the 491 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 17\nintrinsic spontaneous activity of DA-neurons rather than altering evoked DA release 492 \nevents.    493 \nAltogether, these results reveal that inhibition of peripheral CB1R, besides promoting 494 \nsatiety and FAO (Fig. 3, 4 ), may dampen reward-driven feeding also by 495 \nconcomitantly reducing DA-neurons spontaneous activity and consequent activation 496 \nof dopaminoceptive structures.  497 \nTo directly address this point, VGX mice were acutely pretreated with AM6545 1h 498 \nprior GBR12909. Remarkably, ablation of the vagus nerve abolished the blunting 499 \neffect of AM6545 on GBR-elicited locomotor activity ( Fig. 5G, G 1). Moreover, 500 \nconsistently with what observed for palatable bingeing (Fig. 3I ), this vagus-to-brain 501 \neffect was further highlighted by the lack of action of AM6545 when orally 502 \nadministered (Fig. 5H, Suppl. Fig. 6B).  503 \nFinally, to fully establish that peripheral inhibition of CB1R modulates the activity of 504 \nVTA DA-neurons, we performed cell type-specific in vivo  Ca 2+ imaging of DA-505 \nneurons in presence or absence of AM6545. We took advantage of Drd2-Cre mice to 506 \nvirally express GCaMP6f in VTA DA-neurons ( Fig. 6A) as they co-express the 507 \nautoreceptor D2R ( Suppl. Fig. 6C ). Indeed, using this mouse line we were able to 508 \ndetect activation and inhibition of VTA DA-neurons following rewarding (high-fat high-509 \nsugar pellet) or aversive (scruff restraint) events (Suppl. Fig. 6D, E), respectively. To 510 \ntrigger the activity of DA-neurons independently from food- or drugs-associated 511 \nstimuli, we used two paradigms that modulate DA-neurons: the tail suspension [45] 512 \nand exposure to a new environment [46] which promotes exploration ( Fig. 6B). 513 \nInhibition of peripheral CB1R led to a reduced activation of VTA DA-neurons during 514 \nboth paradigms (Fig. 6C, D). At the behavioral level, while AM6545 did not alter the 515 \ntime of immobility in the tail suspension test (Fig. 6E), it reduced the exploratory drive 516 \nin a vagus-dependent manner (Fig. 6F, F 1). Of note, the brain permeable AM251 517 \nreduced exploratory drive in a vagus-independent manner (Fig. 6G).  518 \nCollectively, these results reveal that peripheral CB1R signaling routed through the 519 \nvagal axis exerts an integrative control over metabolic/satietogenic (Fig. 3, 4) and DA 520 \npaths (Fig. 5, 6), both of which are pivotal for the establishment of BE.          521 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 18\nDiscussion  522 \n 523 \nA characteristic feature of feeding behavior is its key ability to dynamically adapt to 524 \nsensory and environmental stimuli signaling food availability. Such adaptive strategy 525 \nis even more pronounced when food is palatable and energy-dense. Indeed, the 526 \ncontrol of feeding strategies requires complex and highly interactive systems that can 527 \nhardly be unequivocally attributed to single structures, circuits or mediators.  528 \nIn our study, we observed that, first, palatable time-locked feeding mobilizes both 529 \nhomeostatic and hedonic components of feeding through fast, but yet physiological, 530 \nallostatic adaptations. Second, such allostatic adaptations require a concerted 531 \ninvolvement of central DA (hedonic drive) and peripheral eCBs signaling 532 \n(homeostatic and hedonic drive). Third, the permissive role of peripheral eCBs fully 533 \nrelies on the vagus nerve which, by a polysynaptic circuit, controls the activity of both 534 \nsatietogenic and reward (dopamine) structures. Fourth, our results point to peripheral 535 \nCB1R neutral antagonists as promising therapeutic tools to counteract eating as well 536 \nas reward-related disorders. 537 \nOverall, our study describes for the first time the fundamental role of eCB gut-brain 538 \ntransmission as a core component of binge eating and its behavioral, cellular and 539 \nmolecular adaptations. 540 \n 541 \nHere, by investigating the pathways involved in hedonic feeding in absence of 542 \nhunger or energy deprivation, we provide evidence that the hedonic drive to eat, as 543 \ntriggered by our intermittent time-locked model, promotes rapid homeostatic 544 \ncompensations leading to escalating consumption of palatable food and to allostatic 545 \nadaptations of energy metabolism. As such, caloric demands are fulfilled and 546 \nclassical energy-mediated homeostatic signals (leptin, insulin) do not seem to 547 \nspontaneously interfere, thus providing us the opportunity to study food intake-related 548 \nintegrative pathways with the abstraction of the homeostatic vs hedonic discrepancy. 549 \nIn line with clinical data [47, 48], we observed that binge-like feeding in lean animals 550 \nis not necessarily associated with overweight gain. The allostatic adaptations 551 \nobserved, ranging from increased anticipatory feeding phase to pre-feeding 552 \nincreased corticosterone levels and food intake maximization, all represent key 553 \nhallmarks of the compulsive and emotional states of BE patients [49–51]. The 554 \nanticipatory feeding phase was associated with decreased levels of plasma TG and 555 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 19\ninsulin, whereas both anticipatory and consummatory phases were characterized by 556 \nincreased energy expenditure, core temperature and metabolic efficiency, thereby 557 \nsuggesting a metabolic shift of nutrients’ use. This observation perfectly mirrors the 558 \nallostatic theory, which stands on the fact that an organism anticipates and adapts to 559 \nenvironmental changes while accordingly adjusting several physiological parameters 560 \nto maintain stable physiological states [52, 53]. Allostatic mechanisms have 561 \nclassically been discussed in terms of stress-related regulatory events. However, the 562 \nhedonic value of a stimulus (food, recreational drugs) can function as a feed-forward 563 \nallostatic factor [4].  564 \n 565 \nIn line with this notion, analysis of key DA-activated downstream targets in the 566 \nDS and NAc highlighted specific patterns of molecular activation. Notably, while the 567 \nanticipatory phase was associated with an increase in ERK and S6 Ser235/236 568 \nphosphorylations, the consummatory phase was also accompanied by a robust 569 \nincrease in mTOR-mediated S6 Ser240/244 activation. Such signaling events, which did 570 \nnot depend on a single episode of palatable food intake, required the dopamine D1R. 571 \nWhether this molecular regulation reflects the full establishment of BE or the amount 572 \nof ingested palatable food remains to be established. Nevertheless, this D1R 573 \nmechanism is of interest since, contrary to the well-known molecular insights of drugs 574 \nof abuse also requiring the D1R [54–56], food-related disorders have usually been 575 \npredominantly associated with altered D2R signaling [57, 58]. Our results reveal that 576 \nbinge eating, characterized by transients and sudden urges of hedonic drive, 577 \nrequires, at least in its early phases, a D1R-mediated transmission. This D1R-578 \ndependent mechanism is in line with the affinity and time-dependent dynamics of 579 \ndopamine effects [54] as well as with the molecular action of released DA which, by 580 \nbinding to Gα (olf)-coupled D1R, would trigger the activation of the aforementioned 581 \npathways, while activation of the Gi-coupled D2R would lead to their inhibition. 582 \nHowever, in clear opposition to psychostimulants, which directly act at central DA 583 \nsynapses, food and food-mediated behaviors impact on DA transmission through a 584 \nplethora of indirect and often peripherally born long-range acting mediators. Notably, 585 \nnutrients, as demonstrated by intragastric infusion of fat and sugar [14, 59–61], or 586 \ngut-born signals [62–64], are sufficient to modulate DA release in reward-related 587 \nstructures. Here, we observed that gut-born signals such as CCK, GLP1 and 588 \nendocannabinoids (eCBs) are essential in gating bingeing. In particular, we found 589 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 20\nthat time-locked consumption of palatable food was associated with a rise in 590 \nperipheral endogenous eCBs, notably 2-AG. Furthermore, inhibition of the 2-AG-591 \ndegrading enzyme MAG lipase resulted in a potentiation of palatable food 592 \nconsumption. Thus, by taking advantage of low brain permeant CB1R 593 \nantagonists/inverse agonists, we observed that blockade of CB1R was able to fully 594 \nabolish both anticipatory and consummatory phases of hedonic feeding as well as 595 \nthe potentiated feeding induced by the MAG lipase inhibitor. These effects agree with 596 \nthe literature showing that endogenous peripheral eCBs are highly and dynamically 597 \nmodulated in eating disorders, and act as powerful mediators of the gut-to-brain 598 \nintegration [17].  599 \n 600 \nPrevious studies have shown that (chronic) administration of AM6545 601 \npromoted long-term maintenance of weight loss and reduction of dyslipidemia in 602 \nobesity [35, 37]. Here, we show that a single, as well as repeated (4 days), 603 \nadministration of AM6545 potently inhibits binge eating and its molecular 604 \nadaptations. The anorectic effects of peripheral blockade of CB1R have been, at 605 \nleast in part, attributed to the property of global CB1R antagonists to promote fatty 606 \nacid oxidation (FAO). In agreement with these studies, we have observed that acute 607 \nadministration of AM6545 was able to dramatically increase FAO independently of 608 \nfood intake. However, here we also demonstrate that such effects require the vagus 609 \nnerve. The action of endogenous eCBs as well as of AM6545 on CB1R-expressing 610 \nvagal afferents [41] may explain our results. In fact, an increase in endogenous eCBs 611 \nduring palatable feeding would slow the vagus nerve activity through the inhibitory 612 \nGi-coupled signaling of CB1R, thus delaying cNTS-reaching satiety signals and 613 \npromoting food intake. On the contrary, peripheral blockade of CB1R, especially 614 \nwhen peripheral eCB levels are endogenously high ( i.e. binge eating, bulimia, 615 \nobesity), would lead to a prompt disinhibition and to the concomitant activation of 616 \nsatietogenic brain pathways (cNTS → PBN→ PVN). Moreover, it is worth to mention 617 \nthat under fasting or lipoprivic conditions the systemic CB1R inverse agonist 618 \nSR141716A modulated feeding by the vagal and sympathetic systems [65]. Another 619 \nsite of action for peripheral eCBs is represented by CB1R-expressing gut cells [40, 620 \n66]. Interestingly, oral administration of a peripheral CB1R antagonist resulted in a 621 \nreduction of alcohol intake via a ghrelin-dependent and vagus-mediated mechanism 622 \n[66]. However, in our reward-driven feeding model, oral administration of AM6545 623 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 21\nfailed to modulate metabolic efficiency as well as to prevent bingeing behavior, thus 624 \nsuggesting that lumen-oriented apical CB1R may not be involved in our mechanism. 625 \nIntriguingly, recent studies have uncovered that sensory neuropod cells in the gut 626 \n[67] can synaptically signal with the juxtaposed vagal afferents using, among other 627 \npossible mediators [68], the fast-acting neurotransmitter glutamate [10]. Whether this 628 \nspecialized gut-to-nerve synapse also mobilizes eCBs, as it occurs at most central 629 \nexcitatory synapses, remains to be determined. In addition, it is important to highlight 630 \nthe key role of peripheral CB1R in adipocytes in the regulation of energy balance 631 \n[69]. However, whether and how adipocytes may, indeed indirectly, influence the 632 \nvagal axis is yet unclear. 633 \nOverall, it would not be hazardous to suggest that peripheral eCBs may impact 634 \nfeeding patterns through different integrative mechanisms which, depending on the 635 \nlocation of peripheral CB1R, may strongly modulate distinct hedonic and homeostatic 636 \nfunctional outputs. These results call for cell-type and tissue-type-specific strategies 637 \nto selectively delete CB1R and/or eCBs-producing enzymes in distinct compartments 638 \nof the gastrointestinal tract and in the neuronal gut-brain axis.      639 \nTo anatomically provide an explanatory gut-to-brain circuit able to support the vagus-640 \nmediated action of AM6545, we found a stark increase of cFos, a marker of neuronal 641 \nactivity, in key brain regions of the satietogenic neuronal pathway. Importantly, we 642 \nreveal that blockade of peripheral CB1R signaling resulted in a strong vagus-643 \ndependent activation of the cNTS as well as of its downstream projecting structures, 644 \nnotably the lPBN and the hypothalamic PVN. This segmented activation of the 645 \ngut→ brainstem→ hypothalamus path is most likely responsible for the AM6545-646 \ninduced effects on bingeing and energy homeostasis since structure-specific 647 \nactivation of these nodes has been shown to reduce food intake and alters energy 648 \nhomeostasis [43, 70–72]. In addition to this satietogenic path and given the strong 649 \nreward component of our paradigm, we also uncover that AM6545-mediated vagus 650 \nactivation results in a dampened activation of VTA DA-neurons. However, such effect 651 \ndid not depend on the releasing capabilities of DA-neurons since AM6545 failed to 652 \nalter amphetamine-evoked locomotor activity. In addition, taking advantage of virally 653 \nmediated GCaMP6f-mediated in vivo Ca2+ imaging of putative VTA DA-neurons, here 654 \nwe demonstrate that peripheral blockade of CB1R clearly reduced both basal and 655 \nevoked activity of DA-neurons, a feature resembling some neurochemical effects of 656 \nvagal nerve stimulation [73, 74].  657 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 22\nThe VTA is characterized by a highly heterogeneous connectivity [75], and a single 658 \nand monosynaptic circuit responsible for the inhibition of DA-neurons through the 659 \nAM6545-activated vagus nerve cannot be selectively sorted out yet. However, 660 \nseveral satiety-related structures in the brainstem and hypothalamus are known to 661 \nproject and modulate, directly and/or indirectly, VTA DA-neurons [13, 76–79]. Among 662 \nthese circuits, the PBN → VTA relay is of particular interest since excitatory PBN 663 \nneurons also largely contact VTA GABA-neurons [78, 80] which in turn may drive the 664 \ninhibition of VTA DA-neurons and consequent dampening of motivated 665 \nbehaviors.        666 \n 667 \nHere, we show that DA-dependent adaptations require orchestrated inputs 668 \namong which peripheral endocannabinoids, through the vagus nerve, allostatically 669 \nscale the homeostatic and hedonic components of feeding and act as mandatory 670 \ngatekeepers for adaptive responses of the reward circuit. The gut-brain axis is 671 \nincreasingly incriminated as a key player of the regulation of energy metabolism [81], 672 \nand we show for the first time that BE is under the control of the vagus-mediated 673 \nperipheral inputs. Pointing to peripheral eCBs as permissive actors of this eating 674 \ndisorder certainly brings novelty to the clinical investigations aimed at identifying 675 \ninnovative and non-invasive therapeutic strategies. Importantly, this study further 676 \npoints to the gut-brain axis as a privileged target to modulate brain structures that are 677 \nfunctionally responsible for processing cognitive and reward events in an integrative 678 \nmanner. 679 \nIn conclusion, while further studies are warranted to fully untangle the key enteric 680 \nactors responsible for this phenomenon, our study identifies a novel integrative 681 \nmechanism by which peripheral endocannabinoids through the gut-brain vagal axis 682 \ngate allostatic feeding by controlling satiety and reward events, thus also paving the 683 \nway to target peripheral elements for brain disorders.  684 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 23\nAcknowledgments  685 \nWe thank Chloé Morel, Rim Hassouna, Anne-Sophie Delbes, Daniela Herrera Moro 686 \nand Raphaël Denis for technical advice and support. Adrien Paquot 687 \n(BPBL/UCLouvain) is acknowledged for his help with eCB quantification. We thank 688 \nOlja Kacanski for administrative support, Isabelle Le Parco, Ludovic Mai ngault, 689 \nAngélique Dauvin, Aurélie Djemat, Florianne Michel, Magguy Boa and Daniel 690 \nQuintas for animals’ care and Sabria Allithi for genotyping. We acknowledge the 691 \ntechnical platform Functional and Physiological Exploration platform (FPE) of the 692 \nUniversité de Paris (BFA-UMR 8251) and the animal core facility Buffon of the 693 \nUniversité de Paris/Institut Jacques Monod. This work was supported by the Fyssen 694 \nFoundation, Nutricia Research Foundation, Allen Foundation Inc., Université de Paris 695 \nand CNRS. CB and EM we re supported by fello wships from the Fondation pour la 696 \nRecherche Médicale  (FRM). Telemetry experiments were supported by the 697 \nContinuous Glucose Telemetry Award 2018 (Dr. Denis) and sponsored by Data 698 \nSciences International.   699 \n 700 \nAuthor Contributions 701 \nC.B. and G.G. conceived, designed, performed and analyzed most of the 702 \nexperiments. J.C. performed surgeries and behavioral experiments. E.M. helped with 703 \nmolecular studies. E.F. performed vagotomy. C.M. helped with fiber photometry 704 \nexperiments. G.G.M. and R.T. analyzed endocannabinoids levels. S.L. provided 705 \nscientific guidance and critical feedback. G.G. supervised the whole project, 706 \ninterpreted the data and wrote the manuscript with contribution from all coauthors.     707 \n 708 \nCompeting interests 709 \nThe authors declare no competing interests.   710 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 24\nReferences  711 \n1.  Berthoud H-R, Münzberg H, Morrison CD. Blaming the Brain for Obesity: 712 \nIntegration of Hedonic and Homeostatic Mechanisms. Gastroenterology. 713 \n2017;152:1728–1738. 714 \n2.  Lenard NR, Berthoud H-R. Central and peripheral regulation of food intake 715 \nand physical activity: pathways and genes. Obesity (Silver Spring). 2008;16 Suppl 716 \n3:S11-22. 717 \n3.  McEwen BS, Wingfield JC. The concept of allostasis in biology and 718 \nbiomedicine. Horm Behav. 2003;43:2–15. 719 \n4.  George O, Le Moal M, Koob GF. Allostasis and addiction: role of the 720 \ndopamine and corticotropin-releasing factor systems. Physiol Behav. 2012;106:58–721 \n64. 722 \n5.  Volkow ND, Wang G-J, Baler RD. Reward, dopamine and the control of food 723 \nintake: implications for obesity. Trends Cogn Sci (Regul Ed). 2011;15:37–46. 724 \n6.  Mazier W, Saucisse N, Simon V, Cannich A, Marsicano G, Massa F, et al. 725 \nmTORC1 and CB1 receptor signaling regulate excitatory glutamatergic inputs onto 726 \nthe hypothalamic paraventricular nucleus in response to energy availability. Mol 727 \nMetab. 2019;28:151–159. 728 \n7.  Rossi MA, Basiri ML, McHenry JA, Kosyk O, Otis JM, van den Munkhof HE, et 729 \nal. Obesity remodels activity and transcriptional state of a lateral hypothalamic brake 730 \non feeding. Science. 2019;364:1271–1274. 731 \n8.  Beutler LR, Corpuz TV, Ahn JS, Kosar S, Song W, Chen Y, et al. Obesity 732 \ncauses selective and long-lasting desensitization of AgRP neurons to dietary fat. 733 \nElife. 2020;9. 734 \n9.  Bai L, Mesgarzadeh S, Ramesh KS, Huey EL, Liu Y, Gray LA, et al. Genetic 735 \nIdentification of Vagal Sensory Neurons That Control Feeding. Cell. 2019;179:1129-736 \n1143.e23. 737 \n10.  Kaelberer MM, Buchanan KL, Klein ME, Barth BB, Montoya MM, Shen X, et 738 \nal. A gut-brain neural circuit for nutrient sensory transduction. Science. 2018;361. 739 \n11.  de Lartigue G. Role of the vagus nerve in the development and treatment of 740 \ndiet-induced obesity. J Physiol. 2016;594:5791–5815. 741 \n12.  Fernandes AB, Alves da Silva J, Almeida J, Cui G, Gerfen CR, Costa RM, et 742 \nal. Postingestive Modulation of Food Seeking Depends on Vagus-Mediated 743 \nDopamine Neuron Activity. Neuron. 2020;106:778-788.e6. 744 \n13.  Han W, Tellez LA, Perkins MH, Perez IO, Qu T, Ferreira J, et al. A Neural 745 \nCircuit for Gut-Induced Reward. Cell. 2018;175:665-678.e23. 746 \n14.  Hankir MK, Seyfried F, Hintschich CA, Diep T-A, Kleberg K, Kranz M, et al. 747 \nGastric Bypass Surgery Recruits a Gut PPAR-α -Striatal D1R Pathway to Reduce Fat 748 \nAppetite in Obese Rats. Cell Metab. 2017;25:335–344. 749 \n15.  Argueta DA, DiPatrizio NV. Peripheral endocannabinoid signaling controls 750 \nhyperphagia in western diet-induced obesity. Physiol Behav. 2017;171:32–39. 751 \n16.  DiPatrizio NV, Joslin A, Jung K-M, Piomelli D. Endocannabinoid signaling in 752 \nthe gut mediates preference for dietary unsaturated fats. FASEB J. 2013;27:2513–753 \n2520. 754 \n17.  Gómez R, Navarro M, Ferrer B, Trigo JM, Bilbao A, Del Arco I, et al. A 755 \nperipheral mechanism for CB1 cannabinoid receptor-dependent modulation of 756 \nfeeding. J Neurosci. 2002;22:9612–9617. 757 \n18.  Monteleone P, Matias I, Martiadis V, De Petrocellis L, Maj M, Di Marzo V. 758 \nBlood levels of the endocannabinoid anandamide are increased in anorexia nervosa 759 \nand in binge-eating disorder, but not in bulimia nervosa. Neuropsychopharmacology. 760 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 25\n2005;30:1216–1221. 761 \n19.  Monteleone AM, Piscitelli F, Dalle Grave R, El Ghoch M, Di Marzo V, Maj M, 762 \net al. Peripheral Endocannabinoid Responses to Hedonic Eating in Binge-Eating 763 \nDisorder. Nutrients. 2017;9. 764 \n20.  Kuipers EN, Kantae V, Maarse BCE, van den Berg SM, van Eenige R, Nahon 765 \nKJ, et al. High Fat Diet Increases Circulating Endocannabinoids Accompanied by 766 \nIncreased Synthesis Enzymes in Adipose Tissue. Front Physiol. 2018;9:1913. 767 \n21.  Berland C, Montalban E, Perrin E, Di Miceli M, Nakamura Y, Martinat M, et al. 768 \nCirculating Triglycerides Gate Dopam ine-Associated Beha viors through DRD2-769 \nExpressing Neurons. Cell Metab. 2020;31:773-790.e11. 770 \n22.  Patriarchi T, Cho JR, Merten K, Howe MW, Marley A, Xiong W-H, et al. 771 \nUltrafast neuronal imaging of dopamine dynamics with designed genetically encoded 772 \nsensors. Science. 2018;360. 773 \n23.  Avena NM. The study of food addiction using animal models of binge eating. 774 \nAppetite. 2010;55:734–737. 775 \n24.  DiFeliceantonio AG, Coppin G, Rigoux L, Edwin Thanarajah S, Dagher A, 776 \nTittgemeyer M, et al. Supra-Additive Effects of Combining Fat and Carbohydrate on 777 \nFood Reward. Cell Metab. 2018;28:33-44.e3. 778 \n25.  Oosterman JE, Koekkoek LL, Foppen E, Unmehopa UA, Eggels L, Verheij J, 779 \net al. Synergistic Effect of Feeding Time and Diet on Hepatic Steatosis and Gene 780 \nExpression in Male Wistar Rats. Obesity (Silver Spring). 2020;28 Suppl 1:S81–S92. 781 \n26.  Wang G-J, Geliebter A, Volkow ND, Telang FW, Logan J, Jayne MC, et al. 782 \nEnhanced striatal dopamine release during food stimulation in binge eating disorder. 783 \nObesity (Silver Spring). 2011;19:1601–1608. 784 \n27.  Spierling S, de Guglielmo G, Kirson D, Kreisler A, Roberto M, George O, et al. 785 \nInsula to ventral striatal projections mediate compulsive eating produced by 786 \nintermittent access to palatable food. Neuropsychopharmacology. 2020;45:579–588. 787 \n28.  Biever A, Puighermanal E, Nishi A, David A, Panciatici C, Longueville S, et al. 788 \nPKA-dependent phosphorylation of ribosomal protein S6 does not correlate with 789 \ntranslation efficiency in striatonigral and striatopallidal medium-sized spiny neurons. J 790 \nNeurosci. 2015;35:4113–4130. 791 \n29.  Gangarossa G, Perroy J, Valjent E. Combinatorial topography and cell-type 792 \nspecific regulation of the ERK pathway by dopaminergic agonists in the mouse 793 \nstriatum. Brain Struct Funct. 2013;218:405–419. 794 \n30.  Radl D, Chiacchiaretta M, Lewis RG, Brami-Cherrier K, Arcuri L, Borrelli E. 795 \nDifferential regulation of striatal motor behavior and related cellular responses by 796 \ndopamine D2L and D2S isoforms. Proc Natl Acad Sci U S A. 2018;115:198–203. 797 \n31.  Reichelt AC, Westbrook RF, Morris MJ. Integration of reward signalling and 798 \nappetite regulating peptide systems in the control of food-cue responses. Br J 799 \nPharmacol. 2015;172:5225–5238. 800 \n32.  de Araujo IE, Schatzker M, Small DM. Rethinking Food Reward. Annual 801 \nReview of Psychology. 2020;71:139–164. 802 \n33.  DiPatrizio NV, Piomelli D. Intestinal lipid-derived signals that sense dietary fat. 803 \nJ Clin Invest. 2015;125:891–898. 804 \n34.  Lau BK, Cota D, Cristino L, Borgland SL. Endocannabinoid modulation of 805 \nhomeostatic and non-homeostatic feeding circuits. Neuropharmacology. 806 \n2017;124:38–51. 807 \n35.  Cluny NL, Vemuri VK, Chambers AP, Limebeer CL, Bedard H, Wood JT, et al. 808 \nA novel peripherally restricted cannabinoid receptor antagonist, AM6545, reduces 809 \nfood intake and body weight, but does not cause malaise, in rodents. Br J 810 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 26\nPharmacol. 2010;161:629–642. 811 \n36.  Tam J, Cinar R, Liu J, Godlewski G, Wesley D, Jourdan T, et al. Peripheral 812 \ncannabinoid-1 receptor inverse agonism reduces obesity by reversing leptin 813 \nresistance. Cell Metab. 2012;16:167–179. 814 \n37.  Tam J, Vemuri VK, Liu J, Bátkai S, Mukhopadhyay B, Godlewski G, et al. 815 \nPeripheral CB1 cannabinoid receptor blockade improves cardiometabolic risk in 816 \nmouse models of obesity. J Clin Invest. 2010;120:2953–2966. 817 \n38.  Long JZ, Li W, Booker L, Burston JJ, Kinsey SG, Schlosburg JE, et al. 818 \nSelective blockade of 2-arachidonoylglycerol hydrolysis produces cannabinoid 819 \nbehavioral effects. Nat Chem Biol. 2009;5:37–44. 820 \n39.  Sykaras AG, Demenis C, Case RM, McLaughlin JT, Smith CP. Duodenal 821 \nenteroendocrine I-cells contain mRNA transcripts encoding key endocannabinoid and 822 \nfatty acid receptors. PLoS One. 2012;7:e42373. 823 \n40.  Argueta DA, Perez PA, Makriyannis A, DiPatrizio NV. Cannabinoid CB1 824 \nReceptors Inhibit Gut-Brain Satiation Signaling in Diet-Induced Obesity. Front 825 \nPhysiol. 2019;10:704. 826 \n41.  Egerod KL, Petersen N, Timshel PN, Rekling JC, Wang Y, Liu Q, et al. 827 \nProfiling of G protein-coupled receptors in vagal afferents reveals novel gut-to-brain 828 \nsensing mechanisms. Mol Metab. 2018;12:62–75. 829 \n42.  Grill HJ, Hayes MR. Hindbrain neurons as an essential hub in the 830 \nneuroanatomically distributed control of energy balance. Cell Metab. 2012;16:296–831 \n309. 832 \n43.  D’Agostino G, Lyons DJ, Cristiano C, Burke LK, Madara JC, Campbell JN, et 833 \nal. Appetite controlled by a cholecystokinin nucleus of the solitary tract to 834 \nhypothalamus neurocircuit. Elife. 2016;5. 835 \n44.  Cheng W, Gonzalez I, Pan W, Tsang AH, Adams J, Ndoka E, et al. Calcitonin 836 \nReceptor Neurons in the Mouse Nucleus Tractus Solitarius Control Energy Balance 837 \nvia the Non-aversive Suppression of Feeding. Cell Metab. 2020;31:301-312.e5. 838 \n45.  Kolata SM, Nakao K, Jeevakumar V, Farmer-Alroth EL, Fujita Y, Bartley AF, et 839 \nal. Neuropsychiatric Phenotypes Produced by GABA Reduction in Mouse Cortex and 840 \nHippocampus. Neuropsychopharmacology. 2018;43:1445–1456. 841 \n46.  Takeuchi T, Duszkiewicz AJ, Sonneborn A, Spooner PA, Yamasaki M, 842 \nWatanabe M, et al. Locus coeruleus and dopaminergic consolidation of everyday 843 \nmemory. Nature. 2016;537:357–362. 844 \n47.  Hutson PH, Balodis IM, Potenza MN. Binge-eating disorder: Clinical and 845 \ntherapeutic advances. Pharmacol Ther. 2018;182:15–27. 846 \n48.  Carr MM, Grilo CM. Examining heterogeneity of binge-eating disorder using 847 \nlatent class analysis. J Psychiatr Res. 2020;130:194–200. 848 \n49.  Naish KR, Laliberte M, MacKillop J, Balodis IM. Systematic review of the 849 \neffects of acute stress in binge eating disorder. Eur J Neurosci. 2019;50:2415–2429. 850 \n50.  Bake T, Murphy M, Morgan DGA, Mercer JG. Large, binge-type meals of high 851 \nfat diet change feeding behaviour and entrain food anticipatory activity in mice. 852 \nAppetite. 2014;77:60–71. 853 \n51.  Muñoz-Escobar G, Guerrero-Vargas NN, Escobar C. Random access to 854 \npalatable food stimulates similar addiction-like responses as a fixed schedule, but 855 \nonly a fixed schedule elicits anticipatory activation. Sci Rep. 2019;9:18223. 856 \n52.  Ramsay DS, Woods SC. Clarifying the roles of homeostasis and allostasis in 857 \nphysiological regulation. Psychol Rev. 2014;121:225–247. 858 \n53.  De Ridder D, Manning P, Leong SL, Ross S, Vanneste S. Allostasis in health 859 \nand food addiction. Sci Rep. 2016;6:37126. 860 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 27\n54.  Luo Z, Volkow ND, Heintz N, Pan Y, Du C. Acute cocaine induces fast 861 \nactivation of D1 receptor and progressive deactivation of D2 receptor striatal 862 \nneurons: in vivo optical microprobe [Ca2+]i imaging. J Neurosci. 2011;31:13180–863 \n13190. 864 \n55.  Kai N, Nishizawa K, Tsutsui Y, Ueda S, Kobayashi K. Differential roles of 865 \ndopamine D1 and D2 receptor-containing neurons of the nucleus accumbens shell in 866 \nbehavioral sensitization. J Neurochem. 2015;135:1232–1241. 867 \n56.  Bertran-Gonzalez J, Bosch C, Maroteaux M, Matamales M, Hervé D, Valjent 868 \nE, et al. Opposing patterns of signaling activation in dopamine D1 and D2 receptor-869 \nexpressing striatal neurons in response to cocaine and haloperidol. J Neurosci. 870 \n2008;28:5671–5685. 871 \n57.  Kenny PJ, Voren G, Johnson PM. Dopamine D2 receptors and striatopallidal 872 \ntransmission in addiction and obesity. Curr Opin Neurobiol. 2013;23:535–538. 873 \n58.  Caravaggio F, Raitsin S, Gerretsen P, Nakajima S, Wilson A, Graff-Guerrero 874 \nA. Ventral striatum binding of a dopamine D2/3 receptor agonist but not antagonist 875 \npredicts normal body mass index. Biol Psychiatry. 2015;77:196–202. 876 \n59.  Han W, Tellez LA, Niu J, Medina S, Ferreira TL, Zhang X, et al. Striatal 877 \nDopamine Links Gastrointestinal Rerouting to Altered Sweet Appetite. Cell Metab. 878 \n2016;23:103–112. 879 \n60.  Tellez LA, Han W, Zhang X, Ferreira TL, Perez IO, Shammah-Lagnado SJ, et 880 \nal. Separate circuitries encode the hedonic and nutritional values of sugar. Nat 881 \nNeurosci. 2016;19:465–470. 882 \n61.  Alhadeff AL, Goldstein N, Park O, Klima ML, Vargas A, Betley JN. Natural and 883 \nDrug Rewards Engage Distinct Pathways that Converge on Coordinated 884 \nHypothalamic and Reward Circuits. Neuron. 2019;103:891-908.e6. 885 \n62.  Cone JJ, McCutcheon JE, Roitman MF. Ghrelin acts as an interface between 886 \nphysiological state and phasic dopamine signaling. J Neurosci. 2014;34:4905–4913. 887 \n63.  Fulton S, Pissios P, Manchon RP, Stiles L, Frank L, Pothos EN, et al. Leptin 888 \nregulation of the mesoaccumbens dopamine pathway. Neuron. 2006;51:811–822. 889 \n64.  Reddy IA, Smith NK, Erreger K, Ghose D, Saunders C, Foster DJ, et al. Bile 890 \ndiversion, a bariatric surgery, and bile acid signaling reduce central cocaine reward. 891 \nPLoS Biol. 2018;16:e2006682. 892 \n65.  Bellocchio L, Soria-Gómez E, Quarta C, Metna-Laurent M, Cardinal P, Binder 893 \nE, et al. Activation of the sympathetic nervous system mediates hypophagic and 894 \nanxiety-like effects of CB ₁  receptor blockade. Proc Natl Acad Sci U S A. 895 \n2013;110:4786–4791. 896 \n66.  Godlewski G, Cinar R, Coffey NJ, Liu J, Jourdan T, Mukhopadhyay B, et al. 897 \nTargeting Peripheral CB1 Receptors Reduces Ethanol Intake via a Gut-Brain Axis. 898 \nCell Metab. 2019;29:1320-1333.e8. 899 \n67.  Bohórquez DV, Shahid RA, Erdmann A, Kreger AM, Wang Y, Calakos N, et al. 900 \nNeuroepithelial circuit formed by innervation of sensory enteroendocrine cells. J Clin 901 \nInvest. 2015;125:782–786. 902 \n68.  Haber AL, Biton M, Rogel N, Herbst RH, Shekhar K, Smillie C, et al. A single-903 \ncell survey of the small intestinal epithelium. Nature. 2017;551:333–339. 904 \n69.  Ruiz de Azua I, Mancini G, Srivastava RK, Rey AA, Cardinal P, Tedesco L, et 905 \nal. Adipocyte cannabinoid receptor CB1 regulates energy homeostasis and 906 \nalternatively activated macrophages. J Clin Invest. 2017;127:4148–4162. 907 \n70.  Roman CW, Derkach VA, Palmiter RD. Genetically and functionally defined 908 \nNTS to PBN brain circuits mediating anorexia. Nat Commun. 2016;7:11905. 909 \n71.  Carter ME, Soden ME, Zweifel LS, Palmiter RD. Genetic identification of a 910 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 28\nneural circuit that suppresses appetite. Nature. 2013;503:111–114. 911 \n72.  Li MM, Madara JC, Steger JS, Krashes MJ, Balthasar N, Campbell JN, et al. 912 \nThe Paraventricular Hypothalamus Regulates Satiety and Prevents Obesity via Two 913 \nGenetically Distinct Circuits. Neuron. 2019;102:653-667.e6. 914 \n73.  Manta S, El Mansari M, Debonnel G, Blier P. Electrophysiological and 915 \nneurochemical effects of long-term vagus nerve stimulation on the rat monoaminergic 916 \nsystems. Int J Neuropsychopharmacol. 2013;16:459–470. 917 \n74.  Perez SM, Carreno FR, Frazer A, Lodge DJ. Vagal nerve stimulation reverses 918 \naberrant dopamine system function in the methylazoxymethanol acetate rodent 919 \nmodel of schizophrenia. J Neurosci. 2014;34:9261–9267. 920 \n75.  Morales M, Margolis EB. Ventral tegmental area: cellular heterogeneity, 921 \nconnectivity and behaviour. Nat Rev Neurosci. 2017;18:73–85. 922 \n76.  Alhadeff AL, Rupprecht LE, Hayes MR. GLP-1 neurons in the nucleus of the 923 \nsolitary tract project directly to the ventral tegmental area and nucleus accumbens to 924 \ncontrol for food intake. Endocrinology. 2012;153:647–658. 925 \n77.  Nieh EH, Vander Weele CM, Matthews GA, Presbrey KN, Wichmann R, 926 \nLeppla CA, et al. Inhibitory Input from the Lateral Hypothalamus to the Ventral 927 \nTegmental Area Disinhibits Dopamine Neurons and Promotes Behavioral Activation. 928 \nNeuron. 2016;90:1286–1298. 929 \n78.  Faget L, Osakada F, Duan J, Ressler R, Johnson AB, Proudfoot JA, et al. 930 \nAfferent Inputs to Neurotransmitter-Defined Cell Types in the Ventral Tegmental 931 \nArea. Cell Rep. 2016;15:2796–2808. 932 \n79.  Wang X-F, Liu J-J, Xia J, Liu J, Mirabella V, Pang ZP. Endogenous Glucagon-933 \nlike Peptide-1 Suppresses High-Fat Food Intake by Reducing Synaptic Drive onto 934 \nMesolimbic Dopamine Neurons. Cell Rep. 2015;12:726–733. 935 \n80.  Beier KT, Steinberg EE, DeLoach KE, Xie S, Miyamichi K, Schwarz L, et al. 936 \nCircuit Architecture of VTA Dopamine Neurons Revealed by Systematic Input-Output 937 \nMapping. Cell. 2015;162:622–634. 938 \n81.  Clemmensen C, Müller TD, Woods SC, Berthoud H-R, Seeley RJ, Tschöp 939 \nMH. Gut-Brain Cross-Talk in Metabolic Control. Cell. 2017;168:758–774. 940 \n   941 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 29\nFigure legends 942 \n 943 \nFig. 1: Allostatic adaptations of metabolic efficiency to time-locked access to 944 \npalatable diet. (A) Experimental design. Control (Ctr) or bingeing animals (Binge) 945 \nhad daily intermittent access to water or a palatable lipids/sucrose mixture for 1 946 \nhour/day during 10-14 consecutive days. Regular chow pellets were provided ad 947 \nlibitum throughout the entire experiment. ( B) Daily binge consumption (ml) of 948 \npalatable mixture during a 14-days protocol. Statistics: ***p<0.001 Binge vs  Control. 949 \n(C) 24 hrs locomotor activity in calorimetric chambers (average of 3 consecutive 950 \ndays). Red dotted rectangles indicate the locomotor activity 2-hrs prior and after 951 \npalatable food access. (C1) Cumulative locomotor activity 2-hrs prior and after 952 \npalatable food access. Results are expressed as beam breaks (bb). Statistics: 953 \n*p<0.05 and ***p<0.001 Binge vs Control. (D) Temporal pattern of regular chow food 954 \nintake (FI, kcal/h) during 24 hrs (average of 3 consecutive days). Statistics: **p<0.01 955 \nBinge vs Control. (D1) Cumulative chow food intake during the dark period. Statistics: 956 \n***p<0.001 Binge vs Control. (E) 24 hrs food intake considering all calories: standard 957 \ndiet (SD) and palatable food (PF). Statistics: ***p<0.001 Binge(SD) vs Control(SD), 958 \n###p<0.001 Binge(SD+PF) vs Binge(SD). ( F) Body weight throughout the 14-days 959 \nexperimental procedure. (G) Longitudinal profile of the respiratory energy ratio (RER) 960 \nfrom indirect calorimetry (average of 3 consecutive days) and ( G1) averaged RER 961 \nvalues 2-hrs prior and after palatable food access. Statistics: **p<0.01 and 962 \n***p<0.001 Binge vs Control. (H) Longitudinal profile of energy expenditure (EE) from 963 \nindirect calorimetry (average of 3 consecutive days) and ( H1) averaged EE values 2-964 \nhrs prior and after palatable food access. Statistics: *p<0.05 and **p<0.01 Binge vs 965 \nControl. ( I) Brown adipose tissue (BAT) temperature during bingeing. Statistics: 966 \n*p<0.05 and **p<0.01 Binge vs Control. ( J) Real-time core temperature recording 967 \nduring 24 hrs and ( J1) averaged values 2-hrs prior and after palatable food access. 968 \nStatistics: ***p<0.001 Binge vs Control. (K ) Matching locomotor activity from core 969 \ntemperature measurements. Statistics: ***p<0.001 Binge vs Control. For number of 970 \nmice/group and statistical details see Suppl. Table 1.  971 \n 972 \nFig. 2:  Binge eating induces dopamine D1R-related molecular modifications . 973 \n(A, B) Protein quantification of phospho-ERK, S6 S235/236 and S6S240/244 in the DS ( A) 974 \nand NAc ( B). For immunoblot pictures see Suppl. Fig. 2C. Statistics: *p<0.05, 975 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 30\n**p<0.01 and ***p<0.001, comparisons to control mice. ( C, D) Temporal profile of 976 \nlocomotor activity and cumulative locomotor response (C1 and D1) of animals treated 977 \nwith the dopamine transporter blocker GBR during the anticipatory phase ( C, C1) or 978 \n1-hour after intermittent access to water (Ctr + GBR) or palatable diet (Binge + GBR) 979 \n(D, D1). Results are expressed as beam breaks (bb). Statistics: **p<0.01 Binge+GBR 980 \nvs Control+GBR. ( E) Palatable diet intake after vehicle (Veh+Binge) or D1R 981 \nantagonist SCH23390 (SCH+Binge) pretreatment. Note: SCH23390 was acutely 982 \nadministered 30 min before binge session. Statistics: ***p<0.001 SCH+Binge vs 983 \nVeh+Binge. ( F) Palatable diet intake after vehicle (Veh+Binge) or D2R antagonist 984 \nhaloperidol 0.25 mg/kg or 0.5 mg/kg (H 0.25+Binge and H 0.5+Binge) treatment. Note: 985 \nhaloperidol was acutely administered 30 min before binge session. ( G) 986 \nImmunolabeling of phospho-S6 in the DS and NAc (for immunolabeling images of 987 \nNAc see Suppl. Fig. 2E) and their associated quantifications (G1, G2, H1, H2) in mice 988 \npretreated with SCH23390 or vehicle and exposed to time-locked palatable diet. 989 \nScale bar: 50 μ m. Statistics: ***p<0.001 Veh+Binge vs Veh+Control, ###p<0.001 990 \nSCH+Binge vs Veh+Binge. ( I) Temporal profile of locomotor activity and cumulative 991 \nlocomotor response ( I1) of animals receiving SCH (SCH+Binge) or vehicle 992 \n(Veh+Binge) (red arrow) and access to palatable diet (black arrow). Statistics: 993 \n**p<0.01 SCH+Binge vs Veh+Binge. ( J) Cumulative regular chow diet intake 994 \nfollowing acute SCH23390 (SCH+Binge) or vehicle (Veh+Binge). Statistics: **p<0.01 995 \nSCH+Binge vs Veh+Binge. (K) Temporal profile of locomotor activity and cumulative 996 \nlocomotor response (2 hrs and 30 min, K1) induced by the D1R agonist SKF81297 997 \nadministered 1 hour after access to time-locked water (Ctr+SKF) or palatable diet 998 \n(Binge+SKF). Statistics: *p<0.05 and **p<0.01 Binge+SKF vs Control+SKF. For 999 \nnumber of mice/group and statistical details see Suppl. Table 1. 1000 \n 1001 \nFig. 3: Peripheral endocannabinoids (eCBs) govern binge eating. (A) Palatable 1002 \nbingeing in animals pretreated (1h prior binge session) with vehicle (Veh), leptin, 1003 \ninsulin, GLP1 agonists exendin-4 (Exe4) and liraglutide (Lira), CCK octapeptide 1004 \nsulfated (CCK-8S) or CB1R inverse agonist AM251. Aside leptin (2 injections/day for 1005 \n2 consecutive days, Suppl. Fig. 3A, B), drugs were administered acutely. Statistics: 1006 \n***p<0.001 Exe4-, Lira-, CCK-8S- & AM251-treated Bingeing mice vs Veh+Binge 1007 \nmice, ###p<0.001 AM251-treated vs Exe4-, Lira & CCK-8S-treated bingeing mice. (B) 1008 \nDosage of peripheral and circulating endocannabinoids: anandamide (AEA), 1009 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 31\ndiacylglycerol (2-AG), docosahexanoyl ethanolamide (DHEA) and 1010 \noleoylethanolamide (OEA) 1 hour before and after palatable bingeing. ( C) Palatable 1011 \nbingeing in mice (3 males and females/group) pre-treated with a single i.p. injection 1012 \nof vehicle (Veh), peripheral CB1R antagonist AM6545 (10 mg/kg) and peripheral 1013 \nCB1R inverse agonist JD-5037 (3 mg/kg). Statistics: ***p<0.001 AM6545 and JD-1014 \n5037 vs Veh-Binge.  (D) Palatable bingeing in mice pre-treated with a single i.p. 1015 \ninjection of vehicle (Veh), peripheral CB1R antagonist AM6545 (10 mg/kg), and/or 1016 \nmonoacylglycerol lipase inhibitor JZL184 (8 mg/kg). Statistics: ***p<0.001 AM6545, 1017 \nJZL184, AM6545+JZL184 vs Veh-Binge. ( E) Chronic (4 days) administration of 1018 \nJZL184 and AM6545 on palatable bingeing. Statistics: ***p<0.001 AM6545-Binge vs 1019 \nVeh-Binge, ###p<0.001 JZL184-Binge vs Veh-Binge. (F ) Effects of acute AM6545 on 1020 \ncore temperature. Statistics: **p<0.01 AM6545-Binge vs  Veh-Binge. Note: black and 1021 \nred arrows indicate administration of AM6545 and palatable food access, 1022 \nrespectively. (G) Immunolabeling and quantifications of phospho-S6 and cFos in the 1023 \nDS and NAc of control or bingeing animals (males and females) acutely pretreated 1024 \nwith Veh or AM6545. Scale bars: 50 μ m. Statistics: ***p<0.001 and *p<0.005 1025 \nVeh+Binge or AM6545+Binge vs Ctr, ###p<0.001 AM6545+Binge vs Veh+Binge. (H) 1026 \nLongitudinal measurement of fatty acid oxidation (FAO) following administration of 1027 \nAM6545 during a Binge session and a NoBinge session. ( H1) Averaged FAO from 1028 \ntime of injection (11h00) till the end of light phase (19h00). ( H2) Ratio of FAO and 1029 \nfood intake (FI) to discriminate between the effect of AM6545 and calories intake. 1030 \nStatistics: ***p<0.001 AM6545 vs Veh (in both Binge and NoBinge sessions). ( I) 1031 \nPalatable bingeing after acute oral gavage of AM6545 (10 mg/kg, p.o.) and (J) 1032 \nassociated fatty acid oxidation. ( K, L) Immunolabeling and quantifications of cFos in 1033 \nthe cNTS/AP regions ( K) and in the lPBN (L ) of control or bingeing animals (males 1034 \nand females) acutely pretreated with Veh or AM6545. Scale bars: 250 μ m. Statistics: 1035 \n***p<0.001, **p<0.01 and *p<0.005 Veh+Binge or AM6545+Binge vs Ctr, ###p<0.001 1036 \nAM6545+Binge vs Veh+Binge. For number of mice/group and statistical details see 1037 \nSuppl. Table 1.  1038 \n 1039 \nFig. 4: The gut-brain vagal axis is required for eCBs-mediated effects. (A) The 1040 \nscheme indicates gut-originated afferent paths that were virally targeted to perform 1041 \nsingle-cell transcriptomic analysis [9]. ( B) Enrichment of different vagal markers 1042 \n(SLC17a6, Scn10a, Htr3a, Cartpt, Grin1, Phox2b) and comparison with Cnr1 and 1043 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 32\nCnr2 in sensory vagal neurons labeled from microinjections in the stomach, proximal 1044 \nand middle intestines. Note: for other gut-brain vagal segments see Suppl. Fig. 3H, 1045 \nI. (C) Palatable food consumption in sham and vagotomized (VGX) animals pre-1046 \ntreated with Veh (Day 10) or JZL184 (Day 11-14) 2-hrs before bingeing sessions. 1047 \nStatistics: ***p<0.001 Sham+JZL184 vs Sham+Veh, ###p<0.001 VGX+JZL184 vs 1048 \nSham+JZL184. (D) cFos immunolabeling in the area postrema (AP), caudal nucleus 1049 \ntractus solitarius (cNTS), lateral parabrachial nucleus (lPBN) and medial parabrachial 1050 \nnucleus (mPBN) in sham and vagotomized animals treated with the peripheral CB1R 1051 \nantagonist AM6545 (10 mg/kg). Scale bars: 250 μ m. ( D1) Scheme indicates the 1052 \ncentral vagus → cNTS→ PBN→ target regions path in sham and VGX mice. (D 2) 1053 \nQuantification of cFos-positive neurons in the AP, cNTS and lPBN in sham and VGX 1054 \nmice injected with AM6545. Statistics: ***p<0.001 VGX+AM6545 vs Sham+AM6545. 1055 \n(E) Palatable bingeing in sham and vagotomized (VGX) animals pre-treated with 1056 \nAM6545 (A) or vehicle (V), and associated measurements of fatty acid oxidation ( F, 1057 \nF1 and G, G 1). Statistics: ***p<0.001 Sham+AM6545 vs Sham+Veh. (H, I ) cFos 1058 \nimmunolabeling in the paraventricular nucleus (PVN) and dorsomedial nucleus of the 1059 \nhypothalamus (DMH) of sham or VGX animals acutely treated with vehicle or 1060 \nAM5646 and associated counting. Scale bars: 250 μ m. Statistics: ***p<0.001 1061 \nSham+AM6545 vs Veh, ###p<0.001 VGX+AM6545 vs Sham+AM6545. For number of 1062 \nmice/group and statistical details see Suppl. Table 1.  1063 \n 1064 \nFig. 5: Peripheral CB1R signaling modulates dopamine dynamics. (A, A1) Effect 1065 \nof AM6545 or Veh on GBR-induced locomotor activity (beam breaks, bb). Statistics: 1066 \n**p<0.01 AM6545+GBR vs  Veh+GBR. ( B, B 1) Effect of JD-5037 or Veh on GBR-1067 \ninduced locomotor activity. Statistics: **p<0.01, *p<0.05 AM6545+GBR vs Veh+GBR. 1068 \n(C) Effect of AM6545 on GBR-triggered cFos expression in the striatum. Scale bar: 1069 \n50 μm. Statistics: ***p<0.001 AM6545+GBR vs Veh+GBR. ( D) Longitudinal profile 1070 \nand heat maps of GBR-induced accumbal DA accumulation (dLight1.2) in mice pre-1071 \ntreated with Veh or AM6545 1h before GBR12909 (red arrow). ( D1) Quantification of 1072 \nbulk fluorescence (AUC) in Veh+GBR and AM6545+GBR groups. Statistics: 1073 \n***p<0.001 AM6545+GBR vs Veh+GBR. (E) Cumulative locomotor activity response 1074 \nin mice pretreated with vehicle (Veh+Amph) or AM6545 (AM6545+Amph). For 1075 \ntemporal locomotor activity see Suppl. Fig. 6A. ( F) Cumulative locomotor activity 1076 \nresponse in mice pretreated with vehicle (Veh+Amph) or AM251 (AM251+Amph). 1077 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n 33\nStatistics: ***p<0.001 AM251+Amph vs Veh+Amph. ( G) GBR-induced locomotor 1078 \nactivity, cumulative locomotor response ( G1) in VGX mice pretreated with vehicle 1079 \n(VGX/Veh+GBR) or AM6545 (VGX/AM6545+GBR). ( H) Cumulative locomotor 1080 \nresponse in mice pretreated with oral gavage (po) of vehicle (Veh (po)+GBR) or 1081 \nAM6545 (AM6545 (po)+GBR). For temporal locomotor activity see Suppl. Fig. 6B.  1082 \n 1083 \nFig. 6: Peripheral CB1R signaling routed by the vagus nerve controls VTA DA-1084 \nneurons activity. (A) Expression of GCaMP6f in VTA DA-neurons of virally injected 1085 \nDrd2-Cre mice. Please, note ( i) colocalization with TH and GCaMP6f-positive 1086 \nneurons and (ii) projecting terminals in the DS and NAc. See also, Suppl. Fig. 6C for 1087 \nTH expression in the VTA of Drd2 -eGFP mice. (B ) Behavioral paradigms used to 1088 \ntrigger the activity of VTA DA-neurons: tail suspension and exposure to a new 1089 \nenvironment (NE). [For validation of in vivo recording of Ca2+ transients in VTA D2R-1090 \n(DA)-neurons see Suppl. Fig. 6D, E ]. (C, D) Temporal dynamics and corresponding 1091 \nheat maps of DA-neurons activity during the during the tail suspension test ( C) and 1092 \nexposure to a new environment ( D). Statistics: *p<0.05, **p<0.01 AM6545 vs Veh. 1093 \n(E) Immobility time (sec) of sham and VGX mice acutely pretreated with Veh or 1094 \nAM6545 1 hour before tail suspension (6 min). ( F) Effect of AM6545 or Veh in sham 1095 \nand VGX mice on novel environment-induced locomotor activity. ( F1) Cumulative 1096 \nlocomotor activity response in sham and VGX mice pretreated with vehicle or 1097 \nAM6545. Statistics: **p<0.01 Sham/AM6545 vs Sham/Veh. (G) Cumulative locomotor 1098 \nactivity response in sham and VGX mice pretreated with vehicle or AM251. Statistics: 1099 \n**p<0.01 Sham+AM251 vs Sham+Veh, and ##p<0.01 VGX+AM251 vs VGX+AM251. 1100 \nFor number of mice/group and statistical details see Suppl. Table 1. 1101 \n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint \n\n.CC-BY-NC-ND 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted October 14, 2021. ; https://doi.org/10.1101/2020.11.14.382291doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}