Integrating Culture-Based Antibiotic Resistance Profiles with Whole-Genome Sequencing Data for 11,087 Clinical Isolates
Author(s) -
Valentina Galata,
Cédric C. Laczny,
Christina Backes,
Georg HemmrichStanisak,
S. Schmolke,
André Franke,
Eckart Meese,
Mathias Herrmann,
Lutz von Müller,
Achim Plum,
Rolf Müller,
Cord Stähler,
Andreas E. Posch,
Andreas Keller
Publication year - 2019
Publication title -
genomics proteomics and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.114
H-Index - 49
eISSN - 2210-3244
pISSN - 1672-0229
DOI - 10.1016/j.gpb.2018.11.002
Subject(s) - biology , genome , acinetobacter baumannii , antibiotic resistance , gene , drug resistance , genetics , antibiotics , genotype , computational biology , bacteria , pseudomonas aeruginosa
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.
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