Rapid metagenomic identification of viral pathogens in clinical samples by real-time nanopore sequencing analysis

Alexander L. Greninger(Abbott (United States)), Samia N. Naccache(Global Viral), Scot Federman(Global Viral), Guixia Yu(University of California, San Francisco), Placide Mbala(National Institute of Biomedical Research), Vanessa Brès(Hologic (United States)), Doug Stryke(Global Viral), Jérôme Bouquet(Global Viral), Sneha Somasekar(Abbott (United States)), Jeffrey M. Linnen(Hologic (United States)), Roger Y. Dodd(American Red Cross), Prime Mulembakani(Metabiota (United States)), Bradley S. Schneider(Metabiota (United States)), Jean‐Jacques Muyembé‐Tamfum(National Institute of Biomedical Research), Susan L. Stramer(American Red Cross), Charles Y. Chiu(Abbott (United States))
Genome Medicine
September 23, 2015
Cited by 584Open Access
Full Text

Abstract

We report unbiased metagenomic detection of chikungunya virus (CHIKV), Ebola virus (EBOV), and hepatitis C virus (HCV) from four human blood samples by MinION nanopore sequencing coupled to a newly developed, web-based pipeline for real-time bioinformatics analysis on a computational server or laptop (MetaPORE). At titers ranging from 10(7)-10(8) copies per milliliter, reads to EBOV from two patients with acute hemorrhagic fever and CHIKV from an asymptomatic blood donor were detected within 4 to 10 min of data acquisition, while lower titer HCV virus (1 × 10(5) copies per milliliter) was detected within 40 min. Analysis of mapped nanopore reads alone, despite an average individual error rate of 24 % (range 8-49 %), permitted identification of the correct viral strain in all four isolates, and 90 % of the genome of CHIKV was recovered with 97-99 % accuracy. Using nanopore sequencing, metagenomic detection of viral pathogens directly from clinical samples was performed within an unprecedented <6 hr sample-to-answer turnaround time, and in a timeframe amenable to actionable clinical and public health diagnostics.


Related Papers

No related papers found

Powered by citation graph analysis