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Detection of Bacterial Pathogens from Broncho-Alveolar Lavage by Next-Generation Sequencing

Emonet, Stéphane
Published in International Journal of Molecular Sciences. 2017, vol. 18, no. 9
Abstract The applications of whole-metagenome shotgun sequencing (WMGS) in routine clinical analysis are still limited. A combination of a DNA extraction procedure, sequencing, and bioinformatics tools is essential for the removal of human DNA and for improving bacterial species identification in a timely manner. We tackled these issues with a broncho-alveolar lavage (BAL) sample from an immunocompromised patient who had developed severe chronic pneumonia. We extracted DNA from the BAL sample with protocols based either on sequential lysis of human and bacterial cells or on the mechanical disruption of all cells. Metagenomic libraries were sequenced on Illumina HiSeq platforms. Microbial community composition was determined by k-mer analysis or by mapping to taxonomic markers. Results were compared to those obtained by conventional clinical culture and molecular methods. Compared to mechanical cell disruption, a sequential lysis protocol resulted in a significantly increased proportion of bacterial DNA over human DNA and higher sequence coverage of Mycobacterium abscessus, Corynebacterium jeikeium and Rothia dentocariosa, the bacteria reported by clinical microbiology tests. In addition, we identified anaerobic bacteria not searched for by the clinical laboratory. Our results further support the implementation of WMGS in clinical routine diagnosis for bacterial identification.
Keywords AdultBacteria/classification/genetics/isolation & purificationBronchoalveolar Lavage Fluid/microbiologyDNABacterial/chemistry/genetics/isolation & purificationHigh-Throughput Nucleotide Sequencing/methodsHumansMaleMetagenome/geneticsReproducibility of ResultsSpecies Specificity
PMID: 28930150
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Research group Analyse génomique et fonctionnelle du staphylocoque doré (604)
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LEO, Stefano et al. Detection of Bacterial Pathogens from Broncho-Alveolar Lavage by Next-Generation Sequencing. In: International Journal of Molecular Sciences, 2017, vol. 18, n° 9. doi: 10.3390/ijms18092011 https://archive-ouverte.unige.ch/unige:111073

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Deposited on : 2018-11-21

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