A metagenomics workflow for SARS-CoV-2 identification, co-pathogen detection, and overall diversity

https://doi.org/10.1016/j.jcv.2021.105025Get rights and content
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Highlights

  • We describe the first study to apply a clinical metagenomic pipeline to identify SARS-CoV-2 variants of concern.

  • The SARS-CoV-2 variants of concern (B.1.1.7) and 2 variants of interest (P.2) were successfully identified.

  • Several bacterial co-pathogens were noted in the SARS-CoV-2 infected patients.

  • The bioinformatic and experimenal pipeline developed here presents an important advancement in unbiased diagnostic approaches to identify and define pandemic viruses.

Abstract

An unbiased metagenomics approach to virus identification can be essential in the initial phase of a pandemic. Better molecular surveillance strategies are needed for the detection of SARS-CoV-2 variants of concern and potential co-pathogens triggering respiratory symptoms. Here, a metagenomics workflow was developed to identify the metagenome diversity by SARS-CoV-2 diagnosis (npositive = 65; nnegative = 60), symptomatology status (nsymptomatic = 71; nasymptomatic = 54) and anatomical swabbing site (nnasopharyngeal = 96; nthroat = 29) in 125 individuals. Furthermore, the workflow was able to identify putative respiratory co-pathogens, and the SARS-CoV-2 lineage across 29 samples. The diversity analysis showed a significant shift in the DNA-metagenome by symptomatology status and anatomical swabbing site. Additionally, metagenomic diversity differed between SARS-CoV-2 infected and uninfected asymptomatic individuals. While 31 co-pathogens were identified in SARS-CoV-2 infected patients, no significant increase in pathogen or associated reads were noted when compared to SARS-CoV-2 negative patients. The Alpha SARS-CoV-2 VOC and 2 variants of interest (Zeta) were successfully identified for the first time using a clinical metagenomics approach. The metagenomics pipeline showed a sensitivity of 86% and a specificity of 72% for the detection of SARS-CoV-2. Clinical metagenomics can be employed to identify SARS-CoV-2 variants and respiratory co-pathogens potentially contributing to COVID-19 symptoms. The overall diversity analysis suggests a complex set of microorganisms with different genomic abundance profiles in SARS-CoV-2 infected patients compared to healthy controls. More studies are needed to correlate severity of COVID-19 disease in relation to potential disbyosis in the upper respiratory tract. A metagenomics approach is particularly useful when novel pandemic pathogens emerge.

Keywords

Metagenomics
SARS-CoV-2
COVID-19
Variants of Concern
Variants of Interest

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