{"doi":"10.1101/2025.11.19.689141","title":"Locally stimulating cell migration in living tissues drives long range collective motion through cell-cell adhesion leading to accelerated migration, healing, and growth","abstract":"Collective cell migration is critical in a range of biophysical processes spanning wound healing to tumor metastasis. It is therefore important to develop techniques for regulating cell motion, but while we have developed powerful migration tools from optogenetics and bioelectricity, the complex mechanics of collective systems make it difficult to determine where and when to apply these stimuli. For example, here we begin with a circular sheet of skin cells with a central hole, or “wound”, and show that globally stimulating all cells to migrate radially inwards to close the gap through electrotaxis causes catastrophic mechanical damage, emerging from strong cell-cell adhesion, which we explain with an active elasticity model. We propose a solution inspired by sheepherding based on using local stimulation to learn the collective perturbation-response of the group and then drive tissue motion. First, we induce local electrotaxis to characterize the impulse-response function of quasi-1D strips of skin tissue, discovering that hyper-local stimulation triggers long-range tissue response over a length scale set by cell-cell adhesion also predicted by our model. Based on this, we apply local, concentric ring fields to in vitro circular wounds. Continuously driving cells towards the wound core kinetically traps the tissue in a jammed state and freezes healing. Pulsing the stimuli allows the tissue to relax and fluidize again, accelerating migration. Finally, we integrate the key length and timescales of tissue mechanics into a biophysically-informed continuum control model. The model’s predictive framework helps determine where and when to apply stimulation for optimal tissue growth which, when tested, accelerates healing 5-fold.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":581707,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9539,"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":1262897,"name":"Yubin Lin","orcid":"0000-0003-4476-9383","position":1,"is_corresponding":false},{"id":1493271,"name":"Sumit Sinha","orcid":"0000-0002-8364-5175","position":2,"is_corresponding":false},{"id":1493272,"name":"Vishaal Krishnan","orcid":"0000-0002-2279-8848","position":3,"is_corresponding":false},{"id":274615,"name":"L. Mahadevan","orcid":"0000-0002-5114-0519","position":4,"is_corresponding":false},{"id":250262,"name":"Daniel J. Cohen","orcid":"0000-0001-5819-1135","position":5,"is_corresponding":false},{"id":1459804,"name":"Jeremy S. Yodh","orcid":"0009-0006-2425-2335","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-19T02:58:51.328454Z","pmid":"41332547","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":[]}