A multi-hospital, clinician-initiated bacterial genomics program to investigate treatment failure in severe<i>Staphylococcus aureus</i>infections
Abstract Bacterial genomics is increasingly used for infectious diseases surveillance, outbreak control and prediction of antibiotic resistance. With expanding availability of rapid whole-genome sequencing, bacterial genomics data could become a valuable tool for clinicians managing bacterial infections, driving precision medicine strategies. Here, we present a novel clinician-driven bacterial genomics framework that applies within-patient evolutionary analysis to identify in real-time microbial genetic changes that have an impact on the outcome of severeStaphylococcus aureusinfections, a strategy that is increasingly used in cancer genomics. Our approach uses a combination of bacterial genomics and novel microbiological testing to identify and track bacterial adaptive mutations that underlie antibiotic treatment failure. We show real-life examples of the impact of our approach and propose a roadmap for the use of bacterial genomics to advance the management of severe bacterial infections..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 27. Okt. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Giulieri, Stefano G. [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2023.10.23.23297384 |
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| PPN (Katalog-ID): |
XBI041308530 |
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| 520 | |a Abstract Bacterial genomics is increasingly used for infectious diseases surveillance, outbreak control and prediction of antibiotic resistance. With expanding availability of rapid whole-genome sequencing, bacterial genomics data could become a valuable tool for clinicians managing bacterial infections, driving precision medicine strategies. Here, we present a novel clinician-driven bacterial genomics framework that applies within-patient evolutionary analysis to identify in real-time microbial genetic changes that have an impact on the outcome of severeStaphylococcus aureusinfections, a strategy that is increasingly used in cancer genomics. Our approach uses a combination of bacterial genomics and novel microbiological testing to identify and track bacterial adaptive mutations that underlie antibiotic treatment failure. We show real-life examples of the impact of our approach and propose a roadmap for the use of bacterial genomics to advance the management of severe bacterial infections. | ||
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