{"doi":"10.3389/fbioe.2022.826694","title":"A Portable Droplet Magnetofluidic Device for Point-of-Care Detection of Multidrug-Resistant Candida auris","abstract":"Candida auris is an emerging multidrug-resistant fungal pathogen that can cause severe and deadly infections. To date, C. auris has spurred outbreaks in healthcare settings in thirty-three countries across five continents. To control and potentially prevent its spread, there is an urgent need for point-of-care (POC) diagnostics that can rapidly screen patients, close patient contacts, and surveil environmental sources. Droplet magnetofluidics (DM), which leverages nucleic acid-binding magnetic beads for realizing POC-amenable nucleic acid detection platforms, offers a promising solution. Herein, we report the first DM device—coined POC.auris—for POC detection of C. auris . As part of POC.auris, we have incorporated a handheld cell lysis module that lyses C. auris cells with 2 min hands-on time. Subsequently, within the palm-sized and automated DM device, C. auris and control DNA are magnetically extracted and purified by a motorized magnetic arm and finally amplified via a duplex real-time quantitative PCR assay by a miniaturized rapid PCR module and a miniaturized fluorescence detector—all in ≤30 min. For demonstration, we use POC.auris to detect C. auris isolates from 3 major clades, with no cross reactivity against other Candida species and a limit of detection of ∼300 colony forming units per mL. Taken together, POC.auris presents a potentially useful tool for combating C. auris .","journal":"Frontiers in Bioengineering and Biotechnology","year":2022,"id":280670,"datarank":0.3453877639491069,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.0,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9566,"is_data_producer":false,"deposit_databanks":null,"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":955148,"name":"Marissa Totten","orcid":"0000-0003-2205-7182","position":1,"is_corresponding":false},{"id":246685,"name":"Liben Chen","orcid":"0000-0002-0648-2456","position":2,"is_corresponding":false},{"id":636187,"name":"Fan‐En Chen","orcid":"0000-0001-6970-4370","position":3,"is_corresponding":false},{"id":246687,"name":"Alexander Y. Trick","orcid":"0000-0003-3997-9669","position":4,"is_corresponding":false},{"id":636188,"name":"Kushagra Shah","orcid":"0000-0003-1791-8873","position":5,"is_corresponding":false},{"id":482410,"name":"Hoan T. Ngo","orcid":"0000-0001-8609-1123","position":6,"is_corresponding":false},{"id":955531,"name":"Mei Jin","orcid":null,"position":7,"is_corresponding":false},{"id":246684,"name":"Kuangwen Hsieh","orcid":"0000-0003-3730-4406","position":8,"is_corresponding":false},{"id":525242,"name":"Sean X. Zhang","orcid":"0000-0003-1166-2563","position":9,"is_corresponding":false},{"id":246688,"name":"Tza‐Huei Wang","orcid":"0000-0002-3540-9354","position":10,"is_corresponding":false},{"id":363485,"name":"Pei‐Wei Lee","orcid":"0000-0001-7491-4057","position":0,"is_corresponding":true}],"reference_count":41,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:29:03.247347Z","pmid":"35425764","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":[]}