Genotyping Influenza Virus by Next-Generation Deep Sequencing in Clinical Specimens

ABSTRACT

Rapid and accurate identification of an influenza outbreak is essential for patient care and treatment. We describe a next-generation sequencing (NGS)-based, unbiased deep sequencing method in clinical specimens to investigate an influenza outbreak. Nasopharyngeal swabs from patients were collected for molecular epidemiological analysis. Total RNA was sequenced by using the NGS technology as paired-end 250 bp reads. Total of 7 to 12 million reads were obtained. After mapping to the human reference genome, we analyzed the 3-4% of reads that originated from a non-human source. A BLAST search of the contigs reconstructed de novo revealed high sequence similarity with that of the pandemic H1N1 virus. In the phylogenetic analysis, the HA gene of our samples clustered closely with that of A/Senegal/VR785/2010(H1N1), A/Wisconsin/11/2013(H1N1), and A/Korea/01/2009(H1N1), and the NA gene of our samples clustered closely with A/Wisconsin/11/2013(H1N1). This study suggests that NGS-based unbiased sequencing can be effectively applied to investigate molecular characteristics of nosocomial influenza outbreak by using clinical specimens such as nasopharyngeal swabs.