{"doi":"10.1101/2025.11.06.687071","title":"Next-generation enhancer AAVs for selective interspecies targeting of midbrain dopaminergic neurons","abstract":"Abstract Using single-nucleus multiomic profiling of the marmoset midbrain, we develop and benchmark enhancer–AAVs to selectively access dopamine (DA) neurons in wild-type animals without combinatorial systems. In vivo candidate screenings identified one highly specific DA enhancer, cjDAE8, in both mice and marmosets. To overcome low-level off-target (leaky) expression, a common limitation for enhancer AAVs, we engineered next-generation AAV backbones that strengthen expression while minimizing leakiness. Quantitative histology comparing natural versus antibody-amplified fluorescence defined AAV doses to achieve high labeling efficiency with greater than 90–95% DA-neuron specificity across species and injection routes. We further demonstrate applications of DA-enhancer-AAVs for (i) retrograde targeting of projection-defined DA populations in marmoset, (ii) fiber-photometric recording of divergent DA-axonal dynamics in striatal subregions, and (iii) optogenetic VTA-DA self-stimulation in mice. Our results establish a resource for cross-species DA targeting and two practical guidelines: backbone context critically shapes enhancer performance, and antibody-amplified readouts rigorously assess specificity.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":556885,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9467,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1450200,"name":"Ke Chen","orcid":"0000-0002-6914-6257","position":1,"is_corresponding":false},{"id":640861,"name":"Martin Wienisch","orcid":"0000-0002-5599-8205","position":2,"is_corresponding":false},{"id":1453104,"name":"Yongqi Wang","orcid":null,"position":3,"is_corresponding":false},{"id":1456999,"name":"Ruoyang Chai","orcid":null,"position":4,"is_corresponding":false},{"id":1457000,"name":"In-Hye Kang","orcid":null,"position":5,"is_corresponding":false},{"id":1457001,"name":"Cindy Szyin Chen","orcid":null,"position":6,"is_corresponding":false},{"id":640860,"name":"Ricardo C.H. del Rosario","orcid":"0000-0002-7038-9598","position":7,"is_corresponding":false},{"id":30828,"name":"Fenna M. Krienen","orcid":"0000-0002-1400-6820","position":8,"is_corresponding":false},{"id":1456571,"name":"Fan Wang","orcid":"0000-0002-3278-4319","position":9,"is_corresponding":false},{"id":244369,"name":"Guoping Feng","orcid":"0000-0002-8021-277X","position":10,"is_corresponding":false},{"id":1204881,"name":"Kian A. Caplan","orcid":null,"position":0,"is_corresponding":true}],"reference_count":66,"raw_metadata":null,"created_at":"2026-07-19T02:55:13.130091Z","pmid":"41279020","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}