The habenula controls the addictive properties of nicotine but also densely expresses opioid and cannabinoid receptors. As such, identification of strategies to manipulate habenular activity may yield new approaches to treat substance use disorders. Here we show that GPR151, an orphan G protein-coupled receptor (GPCR) highly enriched in the habenula of humans and rodents plays a critical role in regulating habenular function and behavioral responses to addictive drugs. We show that GPR151 is expressed on axonal and presynaptic membranes and synaptic vesicles, and regulates synaptic fidelity and plasticity. We find that GPR151 associates with synaptic components controlling vesicle release and ion transport and couples to the G-alpha inhibitory protein Gα o1 to reduce cAMP levels. Stable cell lines expressing GPR151 confirm that it signals via Gi/o and are amenable to ligand screens. Gpr151 null mice show diminished behavioral responses to nicotine, and self-administer greater quantities of the drug, phenotypes rescued by viral re-expression of Gpr151 in the habenula. Gpr151 null mice are also insensitive to the behavioral actions of morphine and cannabinoids. These data identify GPR151 as a critical modulator of habenular function that controls addiction vulnerability across different drug classes. 3 Highlights • Habenula neurons are enriched in nicotinic, opioid, cannabinoid and GPR151 receptors • GPR151 modulates synaptic fidelity and release probability at habenular terminals.• Habenular GPR151 plays a role in drug abuse and food intake/weight control • GPR151 couples to the G-alpha inhibitory protein Gα o1 to reduce cAMP levels. eTOC BlurbAntolin-Fontes at al. identify a G protein-coupled receptor, GPR151, which is highly enriched in human habenular neurons. These neurons are primarily enriched with nicotinic, opioid and cannabinoid receptors. We find that GPR151 modulates habenular synaptic vesicle release probability and behavioral responses to these drugs of abuse.

20 21 22 higher diversity with regard to indigenous combined with exotic breeds led to reduced numbers of infected 40 cattle compared to more homogenous cattle populations. 41 42 Rift Valley fever (RVF) is a zoonotic mosquito-borne disease caused by Rift Valley fever virus (RVFV;43 Phlebovirus: Bunyaviridae) that severely affects ungulate livestock and wildlife but can also affect humans in 44 RVF-endemic regions of sub-Saharan Africa and parts of the Arabian Peninsula [1,2]. The potential extreme 45 economic, and public and veterinary health burdens of epizootics/epidemics of RVF have been described 46 extensively [3]. Heavy rainfall and flooding are the most prominent precursors of RVF epizootics in savanna mosquitoes during blood feeding [2,4,5]. However, areas outside the recognized RVF epizootic regions, 50 especially in central Africa, may not experience transmissions linked to elevated rainfall [6]. In these areas, 51RVFV is most likely spread via movements of infected livestock from endemic areas with elevated rainfall: 52 livestock trading across different market areas may include infectious cattle that could disperse the virus and, 53 in the presence of suitable mosquito vectors, accelerate and expand the transmission of RVFV, especially when 54 cattle operations are distributed across large distances but linked by trade [7]. Patterns of recent RVF activity in 55 Uganda first described on 9 March 2016 support this hypothesis of RVFV spread linked to the cattle trade [8] 56 and underscore the need to develop effective operational surveillance and mitigation strategies to reduce 57 transmission and prevent spread among cattle operations. In this study we designed a network-based epidemic 58 transmission model to run simulations to quantitatively investigate the patterns of spread of RVFV across cattle 59 operations in Kabale District, Uganda, providing an opportunity to thus quantitatively investigate the potential 60 impact of various mitigation methods. 61 Scoglio et al. [9] recently published an individual-level RVF epidemic transmission model for cattle in Riley 62 County, Kansas, USA, structured on the susceptible-exposed-infected-recovered (SEIR) framework applied to 63 a cattle movement network. They used two separate kernel functions -exponential and power-law models -to 64 model cattle movement between and among farms in Riley County. Simulations with these kernel functions 65 revealed that more widespread epizootics resulted from the power law model, most likely because cattle were 66 allowed to move to distant farms. In contrast, the exponential model greatly restricted cattle movement to more 67 proximal farms, reducing spread of the virus. The message from the Scoglio et al. study is that restricting cattle 68 movement substantially reduces RVFV transmission and spread across the landscape of cattle operations. 69 Secondarily, they found that partitioning each farm into several clusters also results in less widespread RVF 70 epizootics. 71 In the present study, we built upon the Scoglio et al...