{"doi":"10.1210/endocr/bqaa005","title":"A Dual Reporter EndoC-βH1 Human β-Cell Line for Efficient Quantification of Calcium Flux and Insulin Secretion","abstract":"Human in vitro model systems of diabetes are critical to both study disease pathophysiology and offer a platform for drug testing. We have generated a set of tools in the human β-cell line EndoC-βH1 that allows the efficient and inexpensive characterization of β-cell physiology and phenotypes driven by disruption of candidate genes. First, we generated a dual reporter line that expresses a preproinsulin-luciferase fusion protein along with GCaMP6s. This reporter line allows the quantification of insulin secretion by measuring luciferase activity and calcium flux, a critical signaling step required for insulin secretion, via fluorescence microscopy. Using these tools, we demonstrate that the generation of the reporter human β-cell line was highly efficient and validated that luciferase activity could accurately reflect insulin secretion. Second, we used a lentiviral vector carrying the CRISPR-Cas9 system to generate candidate gene disruptions in the reporter line. We also show that we can achieve gene disruption in ~90% of cells using a CRISPR-Cas9 lentiviral system. As a proof of principle, we disrupt the β-cell master regulator, PDX1, and show that mutant EndoC-βH1 cells display impaired calcium responses and fail to secrete insulin when stimulated with high glucose. Furthermore, we show that PDX1 mutant EndoC-βH1 cells exhibit decreased expression of the β-cell-specific genes MAFA and NKX6.1 and increased GCG expression. The system presented here provides a platform to quickly and easily test β-cell functionality in wildtype and cells lacking a gene of interest.","journal":"Endocrinology","year":2020,"id":87255,"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":11,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8904,"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":444689,"name":"Karla F. Leavens","orcid":null,"position":1,"is_corresponding":false},{"id":443803,"name":"Siddharth Kishore","orcid":"0000-0002-7547-7650","position":2,"is_corresponding":false},{"id":444690,"name":"Catherine Osorio-Quintero","orcid":null,"position":3,"is_corresponding":false},{"id":443804,"name":"Yi–Ju Chen","orcid":"0000-0001-8932-5095","position":4,"is_corresponding":false},{"id":106462,"name":"Ben Z. Stanger","orcid":"0000-0003-0410-4037","position":5,"is_corresponding":false},{"id":443805,"name":"Pei Wang","orcid":"0000-0003-2373-7315","position":6,"is_corresponding":false},{"id":443806,"name":"Deborah L. French","orcid":"0000-0002-7535-1716","position":7,"is_corresponding":false},{"id":443807,"name":"Paul Gadue","orcid":"0000-0003-4344-048X","position":8,"is_corresponding":false},{"id":443802,"name":"Fabian L. Cardenas‐Diaz","orcid":"0000-0002-6504-478X","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-18T21:59:31.247492Z","pmid":"31960055","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":[]}