{"doi":"10.1016/j.ymthe.2024.02.019","title":"Defining the activity of pro-reparative extracellular vesicles in wound healing based on miRNA payloads and cell type-specific lineage mapping","abstract":"Small extracellular vesicles (EVs) are released by cells and deliver biologically active payloads to coordinate the response of multiple cell types in cutaneous wound healing. Here we used a cutaneous injury model as a donor of pro-reparative EVs to treat recipient diabetic obese mice, a model of impaired wound healing. We established a functional screen for microRNAs (miRNAs) that increased the pro-reparative activity of EVs and identified a down-regulation of miR-425-5p in EVs in vivo and in vitro associated with the regulation of adiponectin. We tested a cell type-specific reporter of a tetraspanin CD9 fusion with GFP to lineage map the release of EVs from macrophages in the wound bed, based on the expression of miR-425-5p in macrophage-derived EVs and the abundance of macrophages in EV donor sites. Analysis of different promoters demonstrated that EV release under the control of a macrophage-specific promoter was most abundant and that these EVs were internalized by dermal fibroblasts. These findings suggested that pro-reparative EVs deliver miRNAs, such as miR-425-5p, that stimulate the expression of adiponectin that has insulin-sensitizing properties. We propose that EVs promote intercellular signaling between cell layers in the skin to resolve inflammation, induce proliferation of basal keratinocytes, and accelerate wound closure.","journal":"Molecular Therapy","year":2024,"id":430940,"datarank":0.6145358404190562,"base_score":2.8903717578961645,"endowment":2.8903717578961645,"self_citation_contribution":0.4335557636844247,"citation_network_contribution":0.18098007673463143,"self_endowment_contribution":0.4335557636844247,"citer_contribution":0.18098007673463143,"corpus_percentile":null,"corpus_rank":null,"citation_count":17,"citer_count":9,"citers_with_citation_signal":7,"citers_with_endowment":7,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9544,"is_data_producer":true,"deposit_databanks":{"GEO":["GSE242496","GSE242497"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1213160,"name":"Wooil Choi","orcid":"0000-0001-7311-8171","position":1,"is_corresponding":false},{"id":1234315,"name":"Sakeef Sayeed","orcid":"0009-0002-6454-3760","position":2,"is_corresponding":false},{"id":463762,"name":"Robert A. Dorschner","orcid":"0000-0002-4773-4461","position":3,"is_corresponding":false},{"id":473568,"name":"Joseph Rainaldi","orcid":"0000-0003-4123-0008","position":4,"is_corresponding":false},{"id":871852,"name":"Kayla Ho","orcid":null,"position":5,"is_corresponding":false},{"id":1103683,"name":"Jenny Kezios","orcid":null,"position":6,"is_corresponding":false},{"id":226806,"name":"John P. Nolan","orcid":"0000-0001-5845-3764","position":7,"is_corresponding":false},{"id":62764,"name":"Prashant Mali","orcid":"0000-0002-3383-1287","position":8,"is_corresponding":false},{"id":463765,"name":"Todd W. Costantini","orcid":"0000-0002-0215-5327","position":9,"is_corresponding":false},{"id":463767,"name":"Brian P. Eliceiri","orcid":"0000-0003-1811-1916","position":10,"is_corresponding":false},{"id":871079,"name":"Dong Jun Park","orcid":"0000-0002-8361-984X","position":0,"is_corresponding":true}],"reference_count":97,"raw_metadata":null,"created_at":"2026-07-19T01:59:20.861374Z","pmid":"38379282","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":[]}