A metagenomics study for the identification of respiratory viruses in mixed clinical specimens: an application of the iterative mapping approach

A metagenomics study for the identification of respiratory viruses in mixed clinical specimens:... Metagenomic approaches to detect viral genomes and variants in clinical samples have various challenges, including low viral titers and bacterial and human genome contamination. To address these limitations, we examined a next-generation sequencing (NGS) and iterative mapping approach for virus detection in clinical samples. We analyzed 40 clinical specimens from hospitalized children diagnosed with acute bronchiolitis, croup, or respiratory tract infections in which virus identification by viral culture or polymerase chain reaction (PCR) was unsuccessful. For our NGS data analysis pipeline, clinical samples were pooled into two NGS groups to reduce sequencing costs, and the depth and coverage of assembled contigs were effectively increased using an iterative mapping approach. PCR was individually performed for each specimen according to the NGS-predicted viral type. We successfully detected previously unidentified respiratory viruses in 26 of 40 specimens using our proposed NGS pipeline. Two dominant populations within the detected viruses were human rhinoviruses (HRVs; n = 14) and human coronavirus NL63 (n = 8), followed by human parainfluenza virus (HPIV), human parechovirus, influenza A virus, respiratory syncytial virus (RSV), and human metapneumovirus. This is the first study reporting the complete genome sequences of HRV-A101, HRV-C3, HPIV-4a, and RSV, as well as an analysis of their genetic variants, in Taiwan. These results demonstrate that this NGS pipeline allows to detect viruses which were not identified by routine diagnostic assays, directly from clinical samples. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Archives of Virology Springer Journals

A metagenomics study for the identification of respiratory viruses in mixed clinical specimens: an application of the iterative mapping approach

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Publisher
Springer Vienna
Copyright
Copyright © 2017 by Springer-Verlag Wien
Subject
Biomedicine; Virology; Medical Microbiology; Infectious Diseases
ISSN
0304-8608
eISSN
1432-8798
D.O.I.
10.1007/s00705-017-3367-4
Publisher site
See Article on Publisher Site

Abstract

Metagenomic approaches to detect viral genomes and variants in clinical samples have various challenges, including low viral titers and bacterial and human genome contamination. To address these limitations, we examined a next-generation sequencing (NGS) and iterative mapping approach for virus detection in clinical samples. We analyzed 40 clinical specimens from hospitalized children diagnosed with acute bronchiolitis, croup, or respiratory tract infections in which virus identification by viral culture or polymerase chain reaction (PCR) was unsuccessful. For our NGS data analysis pipeline, clinical samples were pooled into two NGS groups to reduce sequencing costs, and the depth and coverage of assembled contigs were effectively increased using an iterative mapping approach. PCR was individually performed for each specimen according to the NGS-predicted viral type. We successfully detected previously unidentified respiratory viruses in 26 of 40 specimens using our proposed NGS pipeline. Two dominant populations within the detected viruses were human rhinoviruses (HRVs; n = 14) and human coronavirus NL63 (n = 8), followed by human parainfluenza virus (HPIV), human parechovirus, influenza A virus, respiratory syncytial virus (RSV), and human metapneumovirus. This is the first study reporting the complete genome sequences of HRV-A101, HRV-C3, HPIV-4a, and RSV, as well as an analysis of their genetic variants, in Taiwan. These results demonstrate that this NGS pipeline allows to detect viruses which were not identified by routine diagnostic assays, directly from clinical samples.

Journal

Archives of VirologySpringer Journals

Published: Apr 19, 2017

References

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