A method to identify respiratory virus infections in clinical samples using next-generation sequencing

Scientific Reports
Talia KustinMichal Mandelboim

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.

References

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Citations

May 29, 2020·European Journal of Clinical Microbiology & Infectious Diseases : Official Publication of the European Society of Clinical Microbiology·Maria ReckziegelAndi Krumbholz
Feb 23, 2020·Viruses·Daniel KiselevKamil Khafizov
Sep 11, 2020·International Journal of Microbiology·Daniel Hussien RetaFisseha Alemu Reta
Sep 25, 2020·Journal of Translational Medicine·Francesca CaccuriArnaldo Caruso
Mar 7, 2021·Biosensors·Samantha J CourtneyJessica Z Kubicek-Sutherland
Jun 3, 2021·Nutrients·Glen Davison
Jan 20, 2020·The Science of the Total Environment·Sandra Martínez-PucholSílvia Bofill-Mas

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Methods Mentioned

BETA
PCR
Assay
RNA-Seq
Illumina sequencing

Software Mentioned

Velvet
blastn
OmniCleave
Bowtie
blastx
MiSeq
Tape Station
bowtie2
NucliSENS

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