Please use this identifier to cite or link to this item: doi:10.22028/D291-33737
Title: Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
Author(s): Galata, Valentina
Laczny, Cédric C.
Backes, Christina
Hemmrich-Stanisak, Georg
Schmolke, Susanne
Franke, Andre
Meese, Eckart
Herrmann, Mathias
von Müller, Lutz
Plum, Achim
Müller, Rolf
Stähler, Cord
Posch, Andreas E.
Keller, Andreas
Language: English
Title: Genomics, Proteomics & Bioinformatics
Volume: 17
Issue: 2
Pages: 169-182
Publisher/Platform: Elsevier
Year of Publication: 2019
Free key words: Antibiotic resistance
Whole-genome sequencing
Bacteria
Pan-genome
DDC notations: 500 Science
600 Technology
Publikation type: Journal Article
Abstract: 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 resistance 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://gear-base.com.
DOI of the first publication: 10.1016/j.gpb.2018.11.002
Link to this record: urn:nbn:de:bsz:291--ds-337376
hdl:20.500.11880/31075
http://dx.doi.org/10.22028/D291-33737
ISSN: 1672-0229
Date of registration: 7-Apr-2021
Description of the related object: Supplementary material
Related object: https://doi.org/10.1016/j.gpb.2018.11.002
Faculty: M - Medizinische Fakultät
NT - Naturwissenschaftlich- Technische Fakultät
Department: M - Humangenetik
M - Medizinische Biometrie, Epidemiologie und medizinische Informatik
NT - Pharmazie
Professorship: M - Prof. Dr. Eckhart Meese
M - Univ.-Prof. Dr. Andreas Keller
NT - Prof. Dr. Rolf Müller
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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