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dc.contributor.authorGalata, Valentina
dc.contributor.authorLaczny, Cédric C
dc.contributor.authorBackes, Christina
dc.contributor.authorHemmrich-Stanisak, Georg
dc.contributor.authorSchmolke, Susanne
dc.contributor.authorFranke, Andre
dc.contributor.authorMeese, Eckart
dc.contributor.authorHerrmann, Mathias
dc.contributor.authorvon Müller, Lutz
dc.contributor.authorPlum, Achim
dc.contributor.authorMüller, Rolf
dc.contributor.authorStähler, Cord
dc.contributor.authorPosch, Andreas E
dc.contributor.authorKeller, Andreas
dc.date.accessioned2019-07-03T13:46:00Z
dc.date.available2019-07-03T13:46:00Z
dc.date.issued2019-05-14
dc.identifier.citationGenomics Proteomics Bioinformatics. 2019 May 14. pii: S1672-0229(19)30092-0. doi: 10.1016/j.gpb.2018.11.002.en_US
dc.identifier.issn2210-3244
dc.identifier.pmid31100356
dc.identifier.doi10.1016/j.gpb.2018.11.002
dc.identifier.urihttp://hdl.handle.net/10033/621843
dc.description.abstractEmergingantibiotic resistanceis a major global health threat. The analysis of nucleic acidsequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistancedeterminants to inform molecular diagnostics and drug development. We collected genetic data(11,087 newly-sequenced whole genomes) and culture-based resistance profiles (10,991 out of the11,087 isolates comprehensively tested against 22 antibiotics in total) of clinical isolates including18 main species spanning a time period of 30 years. Species and drug specific resistance patternswere observed including increased resistance rates forAcinetobacter baumanniito carbapenemsand forEscherichia colito fluoroquinolones. Species-levelpan-genomeswere constructed to reflectthe genetic repertoire of the respective species, including conserved essential genes and known resis-tance factors. Integrating phenotypes and genotypes through species-level pan-genomes allowed toinfer gene–drug resistance associations using statistical testing. The isolate collection and the analysis results have been integrated into GEAR-base, a resource available for academic research use free of charge athttps://gear-base.comen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectAntibiotic resistanceen_US
dc.subjectBacteriaen_US
dc.subjectPan-genomeen_US
dc.subjectWhole-genome sequencingen_US
dc.titleIntegrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates.en_US
dc.typeArticleen_US
dc.contributor.departmentHIPS, Helmholtz-Institut für Pharmazeutische Forschung Saarland, Universitätscampus E8.1 66123 Saarbrücken, Germany.en_US
dc.identifier.journalGenomics Proteomics Bioinformaticsen_US
refterms.dateFOA2019-07-03T13:46:01Z
dc.source.journaltitleGenomics, proteomics & bioinformatics


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