A method to identify respiratory virus infections in clinical samples using next-generation sequencing.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
22 02 2019
22 02 2019
Historique:
received:
22
01
2018
accepted:
26
11
2018
entrez:
24
2
2019
pubmed:
24
2
2019
medline:
10
9
2020
Statut:
epublish
Résumé
Respiratory virus infections are very common. Such infections impose an enormous economic burden and occasionally lead to death. Furthermore, every few decades, respiratory virus pandemics emerge, putting the entire world population at risk. Thus, there is an urgent need to quickly and precisely identify the infecting agent in a clinical setting. However, in many patients with influenza-like symptoms (ILS) the identity of the underlying pathogen remains unknown. In addition, it takes time and effort to individually identify the virus responsible for the ILS. Here, we present a new next-generation sequencing (NGS)-based method that enables rapid and robust identification of pathogens in a pool of clinical samples without the need for specific primers. The method is aimed at rapidly uncovering a potentially common pathogen affecting many samples with an unidentified source of disease.
Identifiants
pubmed: 30796243
doi: 10.1038/s41598-018-37483-w
pii: 10.1038/s41598-018-37483-w
pmc: PMC6384955
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
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