Metagenomic Sequencing To Detect Respiratory Viruses in Persons under Investigation for COVID-19

Abstract

Broad testing for respiratory viruses among persons under investigation (PUIs) for SARS-CoV-2 has been performed inconsistently, limiting our understanding of alternative viral infections and coinfections in these patients. RNA metagenomic next-generation sequencing (mNGS) offers an agnostic tool for the detection of both SARS-CoV-2 and other RNA respiratory viruses in PUIs. Here, we used RNA mNGS to assess the frequencies of alternative viral infections in SARS-CoV-2 RT-PCR-negative PUIs (n = 30) and viral coinfections in SARS-CoV-2 RT-PCR-positive PUIs (n = 45). mNGS identified all viruses detected by routine clinical testing (influenza A [n = 3], human metapneumovirus [n = 2], and human coronavirus OC43 [n = 2], and human coronavirus HKU1 [n = 1]). mNGS also identified both coinfections (1, 2.2%) and alternative viral infections (4, 13.3%) that were not detected by routine clinical workup (respiratory syncytial virus [n = 3], human metapneumovirus [n = 1], and human coronavirus NL63 [n = 1]). Among SARS-CoV-2 RT-PCR-positive PUIs, lower cycle threshold (C_T ) values correlated with greater SARS-CoV-2 read recovery by mNGS (R², 0.65; P < 0.001). Our results suggest that current broad-spectrum molecular testing algorithms identify most respiratory viral infections among SARS-CoV-2 PUIs, when available and implemented consistently.

Keywords: COVID-19; SARS-CoV-2; diagnostics; metagenomic sequencing; respiratory viruses.

FIG 1

Correlation of SARS-CoV-2 RT-PCR C_T and log-transformed reads per million for PUI samples testing positive (n = 44). C_T, cycle threshold; RPM, reads per million.