{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T16:52:30Z","timestamp":1792601550020,"version":"4.5.0"},"reference-count":95,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T00:00:00Z","timestamp":1701734400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Guayaquil","award":["FCI-016-2017"],"award-info":[{"award-number":["FCI-016-2017"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>Tuberculosis (TB) is among the deadliest diseases worldwide, and its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, nonadherence to treatment and circulation of previously resistant isolates of <jats:italic>Mycobacterium tuberculosis<\/jats:italic>. In this study, we evaluated the performance and functionalities of web-based tools, including Mykrobe, TB-profiler, PhyResSE, KvarQ, and SAM-TB, for detecting resistance in 88 Ecuadorian isolates of <jats:italic>Mycobacterium tuberculosis<\/jats:italic> drug susceptibility tested previously. Statistical analysis was used to determine the correlation between genomic and phenotypic analysis. Our results showed that with the exception of KvarQ, all tools had the highest correlation with the conventional drug susceptibility test (DST) for global resistance detection (98% agreement and 0.941 Cohen\u2019s kappa), while SAM-TB, PhyResSE, TB-profiler and Mykrobe had better correlations with DST for first-line drug analysis individually. We also identified that in our study, only 50% of mutations characterized by the web-based tools in the <jats:italic>rpoB<\/jats:italic>, <jats:italic>katG<\/jats:italic>, <jats:italic>embB<\/jats:italic>, <jats:italic>pncA<\/jats:italic>, <jats:italic>gyrA<\/jats:italic> and <jats:italic>rrs<\/jats:italic> regions were canonical and included in the World Health Organization (WHO) catalogue. Our findings suggest that SAM-TB, PhyResSE, TB-profiler and Mykrobe were efficient in determining canonical resistance-related mutations, but more analysis is needed to improve second-line detection. Improving surveillance programs using whole-genome sequencing tools for first-line drugs, MDR-TB and XDR-TB is essential to understand the molecular epidemiology of TB in Ecuador.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Importance<\/jats:title>\n<jats:p>Tuberculosis, an infectious disease caused by <jats:italic>Mycobacterium tuberculosis<\/jats:italic>, most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, patient adherence, long duration of treatment, and late diagnosis have reduced the effectiveness of therapy and increased drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, has highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying a more efficient and user-friendly web-based tool to characterize resistance in <jats:italic>Mycobacterium tuberculosis<\/jats:italic> by whole-genome sequencing, which will allow more routine application to improve TB strain surveillance programs locally.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0294670","type":"journal-article","created":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T18:24:15Z","timestamp":1701800655000},"page":"e0294670","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":12,"title":["A precision overview of genomic resistance screening in Ecuadorian isolates of Mycobacterium tuberculosis using web-based bioinformatics tools"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1824-8285","authenticated-orcid":true,"given":"Gabriel","family":"Morey-Le\u00f3n","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paulina M.","family":"Mej\u00eda-Ponce","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan Carlos","family":"Granda Pardo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karen","family":"Mu\u00f1oz-Mawyin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan Carlos","family":"Fern\u00e1ndez-Cadena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evelyn","family":"Garc\u00eda-Moreira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Derly","family":"Andrade-Molina","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0360-3945","authenticated-orcid":true,"given":"Cuauht\u00e9moc","family":"Licona-Cassani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9358-3414","authenticated-orcid":true,"given":"Luisa","family":"Bern\u00e1","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,12,5]]},"reference":[{"key":"pone.0294670.ref001","author":"World Health Organization","year":"2022","journal-title":"Global Tuberculosis Report"},{"issue":"6","key":"pone.0294670.ref002","doi-asserted-by":"crossref","first-page":"1547","DOI":"10.1111\/jam.14478","article-title":"Recent updates on drug resistance in Mycobacterium tuberculosis","volume":"128","author":"R Singh","year":"2020","journal-title":"J Appl Microbiol"},{"key":"pone.0294670.ref003","doi-asserted-by":"crossref","first-page":"102091","DOI":"10.1016\/j.tube.2021.102091","article-title":"Drug resistance, fitness and compensatory mutations in Mycobacterium tuberculosis","volume":"129","author":"AK Alame Emane","year":"2021","journal-title":"Tuberculosis"},{"issue":"5","key":"pone.0294670.ref004","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1080\/17843286.2021.1999588","article-title":"Retrospective evaluation of routine whole genome sequencing of Mycobacterium tuberculosis at the Belgian National Reference Center, 2019.","volume":"77","author":"K Soetaert","year":"2022","journal-title":"Acta Clin Belg."},{"issue":"6","key":"pone.0294670.ref005","doi-asserted-by":"crossref","first-page":"e00202","DOI":"10.1128\/JCM.00202-21","article-title":"A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches","volume":"59","author":"B Bogaerts","year":"2021","journal-title":"J Clin Microbiol"},{"key":"pone.0294670.ref006","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1186\/s12864-021-08139-3","article-title":"The whole-genome sequencing in predicting Mycobacterium tuberculosis drug susceptibility and resistance in Papua","volume":"22","author":"Y Maladan","year":"2021","journal-title":"Indonesia. 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