<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Agathe Jouet</style></author><author><style face="normal" font="default" size="100%">Cyril Gaudin</style></author><author><style face="normal" font="default" size="100%">Nelly Badalato</style></author><author><style face="normal" font="default" size="100%">Allix-Béguec, Caroline</style></author><author><style face="normal" font="default" size="100%">Stéphanie Duthoy</style></author><author><style face="normal" font="default" size="100%">Alice Ferré</style></author><author><style face="normal" font="default" size="100%">Maren Diels</style></author><author><style face="normal" font="default" size="100%">Yannick Laurent</style></author><author><style face="normal" font="default" size="100%">Sandy Contreras</style></author><author><style face="normal" font="default" size="100%">Silke Feuerriegel</style></author><author><style face="normal" font="default" size="100%">Stefan Niemann</style></author><author><style face="normal" font="default" size="100%">Emmanuel André</style></author><author><style face="normal" font="default" size="100%">Michel K Kaswa</style></author><author><style face="normal" font="default" size="100%">Elisa Tagliani</style></author><author><style face="normal" font="default" size="100%">Andrea Cabibbe</style></author><author><style face="normal" font="default" size="100%">Vanessa Mathys</style></author><author><style face="normal" font="default" size="100%">Daniela Cirillo</style></author><author><style face="normal" font="default" size="100%">Bouke C de Jong</style></author><author><style face="normal" font="default" size="100%">Rigouts, Leen</style></author><author><style face="normal" font="default" size="100%">Supply, Philip</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deep amplicon sequencing for culture-free prediction of susceptibility or resistance to 13 anti-tuberculous drugs.</style></title><secondary-title><style face="normal" font="default" size="100%">Eur Respir J</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 Sep 17</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Conventional molecular tests for detecting complex (MTBC) drug resistance on clinical samples cover a limited set of mutations. Whole genome sequencing (WGS) typically requires culture. Here, we evaluated the Deeplex Myc-TB targeted deep sequencing assay for prediction of resistance to 13 anti-tuberculous drugs/drug classes, directly applicable on sputum. With MTBC DNA tests, the limit of detection was 100-1000 genome copies for fixed resistance mutations. Deeplex Myc-TB captured in silico 97.1-99.3% of resistance phenotypes correctly predicted by WGS from 3651 MTBC genomes. On 429 isolates, the assay predicted 92.2% of 2369 first- and second-line phenotypes, with a sensitivity of 95.3% and specificity of 97.4%. Fifty-six of 69 (81.2%) residual discrepancies with phenotypic results involved pyrazinamide, ethambutol, and ethionamide, and low-level rifampicin- or isoniazid-resistance mutations, all notoriously prone to phenotypic testing variability. Only 2 of 91 (2.2%) resistance phenotypes undetected by Deeplex Myc-TB had known resistance-associated mutations by WGS analysis outside Deeplex Myc-TB targets. Phenotype predictions from Deeplex Myc-TB analysis directly on 109 sputa from a Djibouti survey matched those of MTBSeq/PhyResSE/Mykrobe, fed with WGS data from subsequent cultures, with a sensitivity of 93.5/98.5/93.1% and specificity of 98.5/97.2/95.3%. Most residual discordances involved gene deletions/indels and 3-12% heteroresistant calls undetected by WGS analysis, or natural pyrazinamide resistance of globally rare &quot; strains then unreported by Deeplex Myc-TB. On 1494 arduous sputa from a Democratic Republic of the Congo survey, 14 902 of 19 422 (76.7%) possible susceptible or resistance phenotypes could be predicted culture-free. Deeplex Myc-TB may enable fast, tailored tuberculosis treatment.&lt;/p&gt;
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