Robert van de Weerd

Neural circuit interventions hold promise for treating nervous system disorders but are limited by lack of specificity, inadvertently affecting nearby neurons and causing side effects. Cis-regulatory elements (CREs) offer a promising strategy to restrict optogenetic or chemogenetic tool expression to specific neuron subtypes. However, CRE discovery faces significant challenges including low in vivo success, species-specific activity, difficulties with multiplexed AAV screening, and limited spatial resolution. Here, we developed ESCargoT (Engineered Specificity of Cargo Transcription), a platform combining machine learning-guided CRE prioritization, modular AAV assembly, and multiplexed in situ spatial screening focused on the spinal cord, a critical region for pain and itch. First, we trained CRE prioritizing ML models on cross-species chromatin accessibility data from 15 dorsal horn neural subtypes and identified Excit-1, enabling chemogenetic inhibition that reversed inflammatory mechanical allodynia. Subsequently, we accelerated CRE discovery by developing SPRA (spatial parallel reporter assay) for multiplexed screening of a 27-candidate library, identifying new candidates that drive cargo expression in oligodendrocytes and several neuronal subtypes. We then validated two CREs targeting Exc-LMO3 and Exc-SKOR2 neurons and demonstrate that the Exc-SKOR2 enhancer, unlike Excit-1, suppressed chemical itch in mice. Together, our platform enables multiplexed in vivo enhancer profiling that accelerates CRE discovery and gene therapy development.

Carnegie Melon University