Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates.
dc.contributor.author | Galata, Valentina | |
dc.contributor.author | Laczny, Cédric C | |
dc.contributor.author | Backes, Christina | |
dc.contributor.author | Hemmrich-Stanisak, Georg | |
dc.contributor.author | Schmolke, Susanne | |
dc.contributor.author | Franke, Andre | |
dc.contributor.author | Meese, Eckart | |
dc.contributor.author | Herrmann, Mathias | |
dc.contributor.author | von Müller, Lutz | |
dc.contributor.author | Plum, Achim | |
dc.contributor.author | Müller, Rolf | |
dc.contributor.author | Stähler, Cord | |
dc.contributor.author | Posch, Andreas E | |
dc.contributor.author | Keller, Andreas | |
dc.date.accessioned | 2019-07-03T13:46:00Z | |
dc.date.available | 2019-07-03T13:46:00Z | |
dc.date.issued | 2019-05-14 | |
dc.identifier.citation | Genomics Proteomics Bioinformatics. 2019 May 14. pii: S1672-0229(19)30092-0. doi: 10.1016/j.gpb.2018.11.002. | en_US |
dc.identifier.issn | 2210-3244 | |
dc.identifier.pmid | 31100356 | |
dc.identifier.doi | 10.1016/j.gpb.2018.11.002 | |
dc.identifier.uri | http://hdl.handle.net/10033/621843 | |
dc.description.abstract | Emergingantibiotic 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.com | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | * |
dc.subject | Antibiotic resistance | en_US |
dc.subject | Bacteria | en_US |
dc.subject | Pan-genome | en_US |
dc.subject | Whole-genome sequencing | en_US |
dc.title | Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates. | en_US |
dc.type | Article | en_US |
dc.contributor.department | HIPS, Helmholtz-Institut für Pharmazeutische Forschung Saarland, Universitätscampus E8.1 66123 Saarbrücken, Germany. | en_US |
dc.identifier.journal | Genomics Proteomics Bioinformatics | en_US |
refterms.dateFOA | 2019-07-03T13:46:01Z | |
dc.source.journaltitle | Genomics, proteomics & bioinformatics |