A Male Mouse Model of WIN 55,212-2 Self-Administration to Study Cannabinoid Addiction

Despite substantial progress in preclinical cannabinoid research, translational studies on cannabis use disorders (CUD) are still insufficient due to the absence of robust, validated animal models that fully recapitulate the multifactorial clinical phenotype of human CUD. The complex nature of CUD and the incomplete understanding of its underlying neurobiological mechanisms contribute to the limited availability of effective treatments. To address this gap, we developed an operant conditioning-based mouse model that enables the identification of individual vulnerability or resilience to CUD development. This highly translational model is based on the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for substance use disorders. The model allows the assessment of addiction-like behaviors by evaluating three behavioral domains: 1) persistence of responding during periods of cannabinoid unavailability, 2) motivation for cannabinoid seeking measured using a progressive ratio schedule, and 3) compulsivity, assessed when cannabinoid reward is paired with an aversive consequence such as a mild electric foot shock. A major strength of this paradigm is its ability to quantify two phenotypic traits proposed as predisposing factors for addiction vulnerability and two parameters related to craving. In addition, the model is specifically designed to evaluate genetic and circuit-level manipulations using chemogenetic approaches, with minor modifications required by surgical viral-vector delivery. Using this protocol, we can determine whether altering the excitability of specific neural networks promotes resilience or vulnerability to developing cannabinoid addiction. Elucidating these mechanisms is expected to facilitate the identification of novel and more effective therapeutic interventions for CUD. Key features • Operant conditioning-based mouse model to study cannabis use disorders (CUD) based on DSM-5 substance use disorder criteria. • Enables assessment of addiction-like behaviors across persistence, motivation (progressive ratio), and compulsivity under punishment, allowing stratification of vulnerable versus resilient individuals. • Quantifies phenotypic traits linked to cannabinoid addiction vulnerability and behavioral signatures associated with craving for cannabinoids. • Compatible with genetic and circuit-level manipulations to test how specific neural networks modulate CUD-related behaviors.