Word-based GWAS harnesses the rich potential of genomic data for E. coli quinolone resistance
Quinolone resistance presents a growing global health threat. We employed word-based GWAS to explore genomic data, aiming to enhance our understanding of this phenomenon. Unlike traditional variant-based GWAS analyses, this approach simultaneously captures multiple genomic factors, including single...
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Published in | Frontiers in microbiology Vol. 14; p. 1276332 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
13.12.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Quinolone resistance presents a growing global health threat. We employed word-based GWAS to explore genomic data, aiming to enhance our understanding of this phenomenon. Unlike traditional variant-based GWAS analyses, this approach simultaneously captures multiple genomic factors, including single and interacting resistance mutations and genes. Analyzing a dataset of 92 genomic
samples from a wastewater treatment plant in Dresden, we identified 54 DNA unitigs significantly associated with quinolone resistance. Remarkably, our analysis not only validated known mutations in
and
genes and the results of our variant-based GWAS but also revealed new (mutated) genes such as
, the AcrEF-TolC multidrug efflux system,
, and
, implicated in antibiotic resistance. Furthermore, our study identified joint mutations in 14 genes including the known
gene, providing insights into potential synergistic effects contributing to quinolone resistance. These findings showcase the exceptional capabilities of word-based GWAS in unraveling the intricate genomic foundations of quinolone resistance. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Moataz Abd El Ghany, The University of Sydney, Australia; Jess Vergis, Kerala Veterinary and Animal Sciences University, India; Miquel Sánchez-Osuna, Instituto de Investigación e Innovación Parc Taulí (I3PT), Spain Edited by: Daniel Yero, Autonomous University of Barcelona, Spain |
ISSN: | 1664-302X 1664-302X |
DOI: | 10.3389/fmicb.2023.1276332 |