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

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.

Fig. 1

Read classification by BLASTN searches

Fig. 2

Read distributions of viral genomes. Read distributions of the viral genomes revealed by read mapping: (A) HCoV-NL63, (B) HPeV-1, (C) HPIV-4a, (D-K) from PB2 to NS gene of IAV, (L) HRV-A101, (M) HRV-C3, (N) HRV-C4, and (O) HRV-C40 in NGS 1; (P) HCoV-NL63, (Q) HPeV-1, (R) HPIV-4a, (S) RSV, (T) HRV-B92, (U) HRV-C6, (V) HRV-C40, and (W) PA gene of IAV in NGS 2. Read distributions in NGS 1 showed >77.0% coverage and average depths from 7.1 to 7001.1, and in NGS 2 showed >83.0% coverage and average depths from 38.1 to 773.8, except for HPeV-1, HRV-C6, and IAV. The read distribution of IAV PB1 gene in NGS 2 was not shown, due to only one read mapping to this gene