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Detection of hidden antibiotic resistance through real-time genomics.
Nat. Commun. 15:5494 (2024)
Real-time genomics through nanopore sequencing holds the promise of fast antibiotic resistance prediction directly in the clinical setting. However, concerns about the accuracy of genomics-based resistance predictions persist, particularly when compared to traditional, clinically established diagnostic methods. Here, we leverage the case of a multi-drug resistant Klebsiella pneumoniae infection to demonstrate how real-time genomics can enhance the accuracy of antibiotic resistance profiling in complex infection scenarios. Our results show that unlike established diagnostics, nanopore sequencing data analysis can accurately detect low-abundance plasmid-mediated resistance, which often remains undetected by conventional methods. This capability has direct implications for clinical practice, where such "hidden" resistance profiles can critically influence treatment decisions. Consequently, the rapid, in situ application of real-time genomics holds significant promise for improving clinical decision-making and patient outcomes.
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Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
2041-1723
e-ISSN
2041-1723
Journal
Nature Communications
Quellenangaben
Volume: 15,
Issue: 1,
Article Number: 5494
Publisher
Nature Publishing Group
Publishing Place
London
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
Helmholtz Pioneer Campus (HPC)
Helmholtz Pioneer Campus (HPC)
Grants
Projekt DEAL
Bavarian Ministry of Commerce
C.P.dC.'s DZIF grant
Helmholtz Principal Investigator Grant
Bavarian Ministry of Commerce
C.P.dC.'s DZIF grant
Helmholtz Principal Investigator Grant