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

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624217/
https://www.ncbi.nlm.nih.gov/pubmed/31100356
http://dx.doi.org/10.1016/j.gpb.2018.11.002
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author 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
author_facet 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
author_sort Galata, Valentina
collection PubMed
description 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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spelling pubmed-66242172019-07-22 Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates 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 Genomics Proteomics Bioinformatics Original Research 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. Elsevier 2019-04 2019-05-14 /pmc/articles/PMC6624217/ /pubmed/31100356 http://dx.doi.org/10.1016/j.gpb.2018.11.002 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Original Research
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
Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
title Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
title_full Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
title_fullStr Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
title_full_unstemmed Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
title_short Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates
title_sort integrating culture-based antibiotic resistance profiles with whole-genome sequencing data for 11,087 clinical isolates
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624217/
https://www.ncbi.nlm.nih.gov/pubmed/31100356
http://dx.doi.org/10.1016/j.gpb.2018.11.002
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