Open AccessNanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples
Author(s) -
Nick P G Gauthier,
Cassidy Nelson,
Michael B. Bonsall,
Kerstin Locher,
Marthe Charles,
Clayton MacDonald,
Mel Krajden,
Samuel D. Chorlton,
Amee R. Manges
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0259712
Subject(s) - metagenomics , covid-19 , computational biology , nanopore sequencing , biology , dna sequencing , virology , medicine , genetics , infectious disease (medical specialty) , gene , outbreak , disease , pathology
Objectives The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies. Metagenomic Next-Generation Sequencing (mNGS) may allow for the detection of pathogens that can be missed in targeted assays. The goal of this study was to assess the performance of nanopore-based Sequence-Independent Single Primer Amplification (SISPA) for the detection and characterization of SARS-CoV-2. Methods We performed mNGS on clinical samples and designed a diagnostic classifier that corrects for barcode crosstalk between specimens. Phylogenetic analysis was performed on genome assemblies. Results Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-PCR cycle threshold value less than 30. We assembled 10 complete, and one near-complete genomes from 20 specimens that were classified as positive by mNGS. Phylogenetic analysis revealed that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. We found 100% concordance between phylogenetic lineage assignment and Variant of Concern (VOC) PCR results. Our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with the current standard VOC PCR being used in British Columbia. Conclusions This study supports future work examining the broader feasibility of nanopore mNGS as a diagnostic strategy for the detection and characterization of viral pathogens.