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Metagenomic testing as a means of identifing the pathogens causing pneumonia
Identifier
026759
Type of Spiritual Experience
Background
A description of the experience
Antibiotics (Basel). 2017 Nov 29;6(4). pii: E30. doi: 10.3390/antibiotics6040030.
Establishing Genotype-to-Phenotype Relationships in Bacteria Causing Hospital-Acquired Pneumonia: A Prelude to the Application of Clinical Metagenomics.
Ruppé E1, Cherkaoui A2, Lazarevic V3, Emonet S4, Schrenzel J5,6,7.
Abstract
Clinical metagenomics (CMg), referred to as the application of next-generation sequencing (NGS) to clinical samples, is a promising tool for the diagnosis of hospital-acquired pneumonia (HAP). Indeed, CMg allows identifying pathogens and antibiotic resistance genes (ARGs), thereby providing the information required for the optimization of the antibiotic regimen. Hence, provided that CMg would be faster than conventional culture, the probabilistic regimen used in HAP could be tailored faster, which should lead to an expected decrease of mortality and morbidity.
While the inference of the antibiotic susceptibility testing from metagenomic or even genomic data is challenging, a limited number of antibiotics are used in the probabilistic regimen of HAP (namely beta-lactams, aminoglycosides, fluoroquinolones, glycopeptides and oxazolidinones).
Accordingly, based on the perspective of applying CMg to the early diagnostic of HAP, we aimed at reviewing the performances of whole genomic sequencing (WGS) of the main HAP-causing bacteria (Enterobacteriaceae, Pseudomonas aeruginosa, Acinetobacter baumannii, Stenotrophomonas maltophilia and Staphylococcus aureus) for the prediction of susceptibility to the antibiotic families advocated in the probabilistic regimen of HAP.
KEYWORDS:
antibiotic resistance; hospital-acquired pneumonia; next-generation sequencing; prediction; whole-genome sequencing
PMID:
29186015
The source of the experience
PubMedConcepts, symbols and science items
Concepts
Symbols
Science Items
Metagenomic testingActivities and commonsteps
Activities
Overloads
Bacterial infectionLung disease
Pneumonia
Pseudomonas aeruginosa infection
Staphylococcal infection