{"doi":"10.3389/fmedt.2020.00002","title":"Robust Formation of an Epithelial Layer of Human Intestinal Organoids in a Polydimethylsiloxane-Based Gut-on-a-Chip Microdevice","abstract":"Polydimethylsiloxane (PDMS) is a silicone polymer that has been predominantly used in a human organ-on-a-chip microphysiological system. The hydrophobic surface of a microfluidic channel made of PDMS often results in poor adhesion of the extracellular matrix (ECM) as well as cell attachment. The surface modification by plasma or UV/ozone treatment in a PDMS-based device produces a hydrophilic surface that allows robust ECM coating and the reproducible attachment of human intestinal immortalized cell lines. However, these surface-activating methods have not been successful in forming a monolayer of the biopsy-derived primary organoid epithelium. Several existing protocols to grow human intestinal organoid cells in a PDMS microchannel are not always reproducibly operative due to the limited information. Here, we report an optimized methodology that enables robust and reproducible attachment of the intestinal organoid epithelium in a PDMS-based gut-on-a-chip. Among several reported protocols, we optimized a method by performing polyethyleneimine-based surface functionalization followed by the glutaraldehyde cross linking to activate the PDMS surface. Moreover, we discovered that the post-functionalization step contributes to provide uniform ECM deposition that allows to produce a robust attachment of the dissociated intestinal organoid epithelium in a PDMS-based microdevice. We envision that our optimized protocol may disseminate an enabling methodology to advance the integration of human organotypic cultures in a human organ-on-a-chip for patient-specific disease modeling.","journal":"Frontiers in Medical Technology","year":2020,"id":75174,"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":27,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.954,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":291189,"name":"Yoko M. Ambrosini","orcid":"0000-0002-9543-2660","position":1,"is_corresponding":false},{"id":291185,"name":"Yong Cheol Shin","orcid":"0000-0002-1418-5929","position":2,"is_corresponding":false},{"id":291188,"name":"Alexander Wu","orcid":"0000-0001-5106-132X","position":3,"is_corresponding":false},{"id":291190,"name":"So‐Youn Min","orcid":"0000-0002-5436-6089","position":4,"is_corresponding":false},{"id":291187,"name":"Domin Koh","orcid":"0000-0002-6515-5543","position":5,"is_corresponding":false},{"id":291194,"name":"Sowon Park","orcid":"0000-0002-2498-8004","position":6,"is_corresponding":false},{"id":291193,"name":"Seung Kim","orcid":"0000-0003-4373-9828","position":7,"is_corresponding":false},{"id":291195,"name":"Hong Koh","orcid":"0000-0002-3660-7483","position":8,"is_corresponding":false},{"id":291197,"name":"Hyun Jung Kim","orcid":"0000-0001-5342-2870","position":9,"is_corresponding":false},{"id":291186,"name":"Woojung Shin","orcid":"0000-0002-1780-0317","position":0,"is_corresponding":true}],"reference_count":59,"raw_metadata":null,"created_at":"2026-07-18T21:46:33.313355Z","pmid":"33532747","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":[]}