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Abstract
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.
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Details
1 George S. Wise Faculty of Life Sciences Tel Aviv University, School of Molecular Cell Biology and Biotechnology, Tel Aviv, Israel (GRID:grid.12136.37) (ISNI:0000 0004 1937 0546)
2 Ministry of Health, Chaim Sheba Medical Center, Tel-Hashomer, Central Virology Laboratory, Ramat-Gan, Israel (GRID:grid.413795.d) (ISNI:0000 0001 2107 2845); School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Department of Epidemiology and Preventive Medicine, Tel-Aviv, Israel (GRID:grid.12136.37) (ISNI:0000 0004 1937 0546)
3 Ministry of Health, Chaim Sheba Medical Center, Tel-Hashomer, Central Virology Laboratory, Ramat-Gan, Israel (GRID:grid.413795.d) (ISNI:0000 0001 2107 2845)
4 School of Public Health, Sackler Faculty of Medicine, Tel-Aviv University, Department of Epidemiology and Preventive Medicine, Tel-Aviv, Israel (GRID:grid.12136.37) (ISNI:0000 0004 1937 0546); Israel Ministry of Health, The Israel Center for Disease Control, Tel-Hashomer, Israel (GRID:grid.414840.d) (ISNI:0000 0004 1937 052X)