{"doi":"10.7171/jbt.21-3203-006","title":"Homebrew reagents for low-cost RT-LAMP","abstract":"Reverse transcription-loop-mediated isothermal amplification (RT-LAMP) has gained popularity for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The high specificity, sensitivity, simple protocols, and potential to deliver results without the use of expensive equipment has made it an attractive alternative to RT-PCR. However, the high cost per reaction, the centralized manufacturing of required reagents, and their distribution under cold chain shipping limit RT-LAMP's applicability in low-income settings. The preparation of assays using homebrew enzymes and buffers has emerged worldwide as a response to these limitations and potential shortages. Here, we describe the production of Moloney murine leukemia virus reverse transcriptase and BstLF DNA polymerase for the local implementation of RT-LAMP reactions at low cost. These reagents compared favorably to commercial kits, and optimum concentrations were defined in order to reduce time to threshold, increase ON/OFF range, and minimize enzyme quantities per reaction. As a validation, we tested the performance of these reagents in the detection of SARS-CoV-2 from RNA extracted from clinical nasopharyngeal samples, obtaining high agreement between RT-LAMP and RT-PCR clinical results. The in-house preparation of these reactions results in an order of magnitude reduction in costs; thus, we provide protocols and DNA to enable the replication of these tests at other locations. These results contribute to the global effort of developing open and low-cost diagnostics that enable technological autonomy and distributed capacities in viral surveillance.","journal":"Journal of Biomolecular Techniques JBT","year":2021,"id":175017,"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":23,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9532,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":308429,"name":"Isaac Núñez","orcid":"0000-0002-4439-3745","position":1,"is_corresponding":false},{"id":396921,"name":"Maira Rivera","orcid":"0000-0002-2771-9248","position":2,"is_corresponding":false},{"id":716095,"name":"Javiera Reyes","orcid":null,"position":3,"is_corresponding":false},{"id":715320,"name":"Paula Blázquez‐Sánchez","orcid":"0000-0003-3232-909X","position":4,"is_corresponding":false},{"id":715321,"name":"Aníbal Arce","orcid":"0000-0001-8134-6385","position":5,"is_corresponding":false},{"id":715322,"name":"Alexander J. Brown","orcid":"0000-0002-9638-7400","position":6,"is_corresponding":false},{"id":715323,"name":"Chiara Gandini","orcid":"0000-0001-5536-3608","position":7,"is_corresponding":false},{"id":715324,"name":"Jennifer K. Molloy","orcid":"0000-0003-3519-6632","position":8,"is_corresponding":false},{"id":413562,"name":"César A. Ramírez‐Sarmiento","orcid":"0000-0003-4647-903X","position":9,"is_corresponding":false},{"id":308434,"name":"Fernán Federici","orcid":"0000-0001-9200-5383","position":10,"is_corresponding":false},{"id":308428,"name":"Tamara Matúte","orcid":"0000-0002-0486-985X","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-18T23:47:11.249697Z","pmid":"35027869","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":[]}