Metagenomic Next-Generation Sequencing of the 2014 Ebola Virus Disease Outbreak in the Democratic Republic of the Congo

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.

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

FIG 1

Temporal signal and molecular clock phylogeny of the Zaire ebolavirus lineage. (Top left) Regression of sample collection dates against root-to-tip genetic distances obtained from an estimated maximum likelihood phylogeny. The phylogeny shown here was estimated using a Bayesian molecular clock approach from the complete coding genome sequences of 85 Zaire ebolaviruses, including 18 sequences collected from the 2014 outbreak in the Democratic Republic of the Congo. Black circles at phylogenetic nodes indicate Bayesian posterior probabilities of >0.75, and numbers below or above phylogenetic branches indicate branch-specific evolutionary rates estimated from the relaxed molecular clock model. Genome sequences generated in this study are in bold.