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

Daniel Castañeda-Mogollón; Claire Kamaliddin; Lisa Oberding; Yan Liu; Abu Naser Mohon; Rehan Mujeeb Faridi; Faisal Khan; Dylan R Pillai

doi:10.1016/j.jcv.2021.105025

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

J Clin Virol. 2021 Dec:145:105025. doi: 10.1016/j.jcv.2021.105025. Epub 2021 Nov 3.

Authors

Daniel Castañeda-Mogollón¹, Claire Kamaliddin¹, Lisa Oberding¹, Yan Liu¹, Abu Naser Mohon¹, Rehan Mujeeb Faridi², Faisal Khan², Dylan R Pillai³

Affiliations

¹ Cumming School of Medicine, Department of Pathology & Laboratory Medicine, the University of Calgary, AB, Canada; Cumming School of Medicine, Department of Microbiology, Immunology, and Infectious Diseases, the University of Calgary, Canada; Calvin, Phoebe & Joan Snyder Institute for Chronic Diseases, the University of Calgary, Calgary, AB, Canada.
² Alberta Precision Laboratories, Diagnostic & Scientific Centre, Calgary, AB, Canada; Hematology Translational Lab, University of Calgary, Calgary, AB, Canada; Arnie Charbonneau Cancer Institute, the University of Calgary, Calgary, AB, Canada.
³ Cumming School of Medicine, Department of Pathology & Laboratory Medicine, the University of Calgary, AB, Canada; Cumming School of Medicine, Department of Microbiology, Immunology, and Infectious Diseases, the University of Calgary, Canada; Calvin, Phoebe & Joan Snyder Institute for Chronic Diseases, the University of Calgary, Calgary, AB, Canada; Alberta Precision Laboratories, Diagnostic & Scientific Centre, Calgary, AB, Canada. Electronic address: drpillai@ucalgary.ca.

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 (n_positive = 65; n_negative = 60), symptomatology status (n_symptomatic = 71; n_asymptomatic = 54) and anatomical swabbing site (n_{nasopharyngeal} = 96; n_throat = 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: COVID-19; Metagenomics; SARS-CoV-2; Variants of Concern; Variants of Interest.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19 Testing
COVID-19*
Humans
Metagenomics
SARS-CoV-2*
Workflow

Supplementary concepts

SARS-CoV-2 variants