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Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates

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Genomics, Proteomics & Bioinformatics 2019年第2期17卷 169-182页

作者： Valentina Galata Cédric C. Laczny Christina Backes Georg Hemmrich-Stanisak Susanne Schmolke Andre Franke Eckart Meese Mathias Herrmann Lutz von Müller Achim Plum Rolf Mü ller cord stahler Andreas E. Posch Andreas Keller Chair for Clinical Bioinformatics Saarland University 66123 Saarbrücken Germany Helmholtz Center for Infection Research and Pharmaceutical Biotechnology (HZI) Saarland University 66123 Saarbrücken Germany Institute of Clinical Molecular Biology Christian-Albrechts University of Kiel 24105 Kiel Germany Siemens Healthcare GmbH Strategy and Innovation 91052 Erlangen Germany Department of Human Genetics Saarland University 66421 Homburg Germany Institute of Medical Microbiology and Hygiene Saarland University 66421 Homburg Germany Ares Genetics GmbH 1030 Vienna Austria Curetis GmbH 71088 Holzgerlingen Germany Department of Pharmacy Pharmaceutical Biotechnology Saarland University 66123 Saarbrücken Germany Department of Microbial Natural Products Helmholtz-Institute for Pharmaceutical Research Saarland (HIPS) Saarland University 66123 Saarbrücken Germany

Emerging antibiotic resistance is a major global health threat. The analysis of nucleic acid sequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistance determinants 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 the 11,087 isolates comprehensively tested against 22 antibiotics in total) of clinical isolates including 18 main species spanning a time period of 30 years. Species and drug specific resistance patterns were observed including increased resistance rates for Acinetobacter baumannii to carbapenems and for Escherichia coli to fluoroquinolones. Species-level pan-genomes were constructed to reflect the 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 to infer 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 at https://***.

关键词： Antibiotic resistance Whole-genome sequencing Bacteria Pan-genome

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