{"doi":"10.7554/elife.75064","title":"Mechanisms governing target search and binding dynamics of hypoxia-inducible factors","abstract":"Transcription factors (TFs) are classically attributed a modular construction, containing well-structured sequence-specific DNA-binding domains (DBDs) paired with disordered activation domains (ADs) responsible for protein-protein interactions targeting co-factors or the core transcription initiation machinery. However, this simple division of labor model struggles to explain why TFs with identical DNA-binding sequence specificity determined in vitro exhibit distinct binding profiles in vivo. The family of hypoxia-inducible factors (HIFs) offer a stark example: aberrantly expressed in several cancer types, HIF-1α and HIF-2α subunit isoforms recognize the same DNA motif in vitro - the hypoxia response element (HRE) - but only share a subset of their target genes in vivo, while eliciting contrasting effects on cancer development and progression under certain circumstances. To probe the mechanisms mediating isoform-specific gene regulation, we used live-cell single particle tracking (SPT) to investigate HIF nuclear dynamics and how they change upon genetic perturbation or drug treatment. We found that HIF-α subunits and their dimerization partner HIF-1β exhibit distinct diffusion and binding characteristics that are exquisitely sensitive to concentration and subunit stoichiometry. Using domain-swap variants, mutations, and a HIF-2α specific inhibitor, we found that although the DBD and dimerization domains are important, another main determinant of chromatin binding and diffusion behavior is the AD-containing intrinsically disordered region (IDR). Using Cut&Run and RNA-seq as orthogonal genomic approaches, we also confirmed IDR-dependent binding and activation of a specific subset of HIF target genes. These findings reveal a previously unappreciated role of IDRs in regulating the TF search and binding process that contribute to functional target site selectivity on chromatin.","journal":"eLife","year":2022,"id":236886,"datarank":1.6013186583512624,"base_score":4.189654742026425,"endowment":4.189654742026425,"self_citation_contribution":0.6284482113039639,"citation_network_contribution":0.9728704470472986,"self_endowment_contribution":0.6284482113039639,"citer_contribution":0.9728704470472986,"corpus_percentile":null,"corpus_rank":null,"citation_count":65,"citer_count":50,"citers_with_citation_signal":38,"citers_with_endowment":38,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9536,"is_data_producer":true,"deposit_databanks":{"GEO":["GSE207575"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":109372,"name":"Claudia Cattoglio","orcid":"0000-0001-6100-0491","position":1,"is_corresponding":false},{"id":649431,"name":"Gina M. Dailey","orcid":"0000-0002-8988-963X","position":2,"is_corresponding":false},{"id":810428,"name":"Qiulin Zhu","orcid":"0000-0003-2809-7652","position":3,"is_corresponding":false},{"id":109375,"name":"Robert Tjian","orcid":"0000-0003-0539-8217","position":4,"is_corresponding":false},{"id":109376,"name":"Xavier Darzacq","orcid":"0000-0003-2537-8395","position":5,"is_corresponding":false},{"id":550186,"name":"Yu Chen","orcid":"0000-0001-7856-4648","position":0,"is_corresponding":true}],"reference_count":78,"raw_metadata":null,"created_at":"2026-07-19T00:22:03.686498Z","pmid":"36322456","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":[]}