Metagenomic next-generation sequencing of the 2014 Ebola Virus disease outbreak in the Democratic Republic of the Congo

Tony Li, Placide Mbala-Kingebeni, Samia N Naccache, Julien Thézé, Jerome Bouquet, Scot Federman, Sneha Somasekar, Guixia Yu, Claudia Sanchez-San Martin, Asmeeta Achari, Bradley S Schneider, Anne W Rimoin, Andrew Rambaut, Justus Nsio, Prime Mulembakani, Steve Ahuka-Mundeke, Jimmy Kapetshi, Oliver G Pybus, Jean-Jacques Muyembe-Tamfum, Charles Y Chiu

Research output: Contribution to journalArticlepeer-review

Abstract

We applied metagenomic next-generation sequencing (mNGS) to detect Zaire Ebola virus (EBOV) and other potential pathogens from whole-blood samples from 70 patients with suspected Ebola hemorrhagic fever during a 2014 outbreak in Boende, Democratic Republic of the Congo (DRC) and correlated these findings with clinical symptoms. Twenty of 31 patients (64.5%) tested in Kinshasa, DRC, were EBOV positive by quantitative reverse transcriptase PCR (qRT-PCR). Despite partial degradation of sample RNA during shipping and handling, mNGS followed by EBOV-specific capture probe enrichment in a U.S. genomics laboratory identified EBOV reads in 22 of 70 samples (31.4%) versus in 21 of 70 (30.0%) EBOV-positive samples by repeat qRT-PCR (overall concordance = 87.1%). Reads from Plasmodium falciparum (malaria) were detected in 21 patients, of which at least 9 (42.9%) were coinfected with EBOV. Other positive viral detections included hepatitis B virus (n = 2), human pegivirus 1 (n = 2), Epstein-Barr virus (n = 9), and Orungo virus (n = 1), a virus in the Reoviridae family. The patient with Orungo virus infection presented with an acute febrile illness and died rapidly from massive hemorrhage and dehydration. Although the patient's blood sample was negative by EBOV qRT-PCR testing, identification of viral reads by mNGS confirmed the presence of EBOV coinfection. In total, 9 new EBOV genomes (3 complete genomes, and an additional 6 ≥50% complete) were assembled. Relaxed molecular clock phylogenetic analysis demonstrated a molecular evolutionary rate for the Boende strain 4 to 10× slower than that of other Ebola lineages. These results demonstrate the utility of mNGS in broad-based pathogen detection and outbreak surveillance.

Original languageEnglish
JournalJournal of Clinical Microbiology
Volume57
Issue number9
DOIs
Publication statusPublished - 26 Aug 2019

Keywords

  • 2014 Boende outbreak
  • Orungo virus
  • coinfection
  • Ebola virus
  • molecular clock analysis
  • next-generation sequencing
  • pathogen discovery
  • phylogenetic analysis
  • viral genome assembly
  • viral metagenomics

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