Rapid metagenomic characterization of a case of imported COVID-19 in Cambodia

Jessica E. Manning; Jennifer A. Bohl; Sreyngim Lay; Sophana Chea; Ly Sovann; Yi Sengdoeurn; Seng Heng; Chan Vuthy; Katrina Kalantar; Vida Ahyong; Michelle Tan; Jonathan Sheu; Cristina M. Tato; Joseph L. DeRisi; Laurence Baril; Veasna Duong; Philippe Dussart; Erik A. Karlsson

Here, we demonstrate that unbiased mNGS is a feasible and efficient means to detect pathogens in the midst of an outbreak of a novel virus. The index Cambodian SARS-CoV-2 sequence data uploaded to public databases represent one of the only sequences generated in a low-to-middle income country close to the outbreak epicenter. Despite major advances in mNGS technologies and significant decreases in costs associated with sequencing, preparation of sequencing libraries and sufficient bioinformatics capabilities for timely analysis still present a challenge in the developing world. 8 As cases of COVID-19 spread globally in mid-January, initial real-time PCR protocols took into account that the genetic diversity of SARS-CoV-2 in humans and animals was not completely known. Non-specificity combined with variable sample quality can hinder ability to detect the pathogen in question. In this scenario, our metagenomics approach demonstrated a first-pass high coverage of the N gene, closely aligning to diagnostic protocols utilizing both the E and N author/funder. All rights reserved. No reuse allowed without permission.