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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.

SUBMITTER: Li T

PROVIDER: S-EPMC6711896 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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

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

Journal of clinical microbiology 20190826 9

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 d ...[more]

PMID: 31315955

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Project description:BackgroundThe 2018-2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces in the Democratic Republic of the Congo (DRC) is the largest ever recorded in the DRC. It has been declared a Public Health Emergency of International Concern. The outbreak emerged in a region of chronic conflict and insecurity, and directed attacks against health care workers may have interfered with disease response activities. Our study characterizes and quantifies the broader conflict dynamics over the course of the outbreak by pairing epidemiological and all available spatial conflict data.MethodsWe build a set of conflict variables by mapping the spatial locations of all conflict events and their associated deaths in each of the affected health zones in North Kivu and Ituri, eastern DRC, before and during the outbreak. Using these data, we compare patterns of conflict before and during the outbreak in affected health zones and those not affected. We then test whether conflict is correlated with increased EVD transmission at the health zone level.FindingsThe incidence of conflict events per capita is ~?600 times more likely in Ituri and North Kivu than for the rest of the DRC. We identified 15 time periods of substantial uninterrupted transmission across 11 health zones and a total of 120 bi-weeks. We do not find significant short-term associations between the bi-week reproduction numbers and the number of conflicts. However, we do find that the incidence of conflict per capita was correlated with the incidence of EVD per capita at the health zone level for the entire outbreak (Pearson's r?=?0.33, 95% CI 0.05-0.57). In the two provinces, the monthly number of conflict events also increased by a factor of 2.7 in Ebola-affected health zones (p value <?0.05) compared to 2.0 where no transmission was reported and 1.3 in the rest of the DRC, in the period between February 2019 and July 2019.ConclusionWe characterized the association between variables documenting broad conflict levels and EVD transmission. Such assessment is important to understand if and how such conflict variables could be used to inform the outbreak response. We found that while these variables can help characterize long-term challenges and susceptibilities of the different regions they provide little insight on the short-term dynamics of EVD transmission.

Project description:As the epidemiological epicenter of the human immunodeficiency virus (HIV) pandemic, the Democratic Republic of the Congo (DRC) is a reservoir of circulating HIV strains exhibiting high levels of diversity and recombination. In this study, we characterized HIV specimens collected in two rural areas of the DRC between 2001 and 2003 to identify rare strains of HIV. The env gp41 region was sequenced and characterized for 172 HIV-positive specimens. The env sequences were predominantly subtype A (43.02%), but 7 other subtypes (33.14%), 20 circulating recombinant forms (CRFs; 11.63%), and 20 unclassified (11.63%) sequences were also found. Of the rare and unclassified subtypes, 18 specimens were selected for next-generation sequencing (NGS) by a modified HIV-switching mechanism at the 5' end of the RNA template (SMART) method to obtain full-genome sequences. NGS produced 14 new complete genomes, which included pure subtype C (n = 2), D (n = 1), F1 (n = 1), H (n = 3), and J (n = 1) genomes. The two subtype C genomes and one of the subtype H genomes branched basal to their respective subtype branches but had no evidence of recombination. The remaining 6 genomes were complex recombinants of 2 or more subtypes, including subtypes A1, F, G, H, J, and K and unclassified fragments, including one subtype CRF25 isolate, which branched basal to all CRF25 references. Notably, all recombinant subtype H fragments branched basal to the H clade. Spatial-geographical analysis indicated that the diverse sequences identified here did not expand globally. The full-genome and subgenomic sequences identified in our study population significantly increase the documented diversity of the strains involved in the continually evolving HIV-1 pandemic.IMPORTANCE Very little is known about the ancestral HIV-1 strains that founded the global pandemic, and very few complete genome sequences are available from patients in the Congo Basin, where HIV-1 expanded early in the global pandemic. By sequencing a subgenomic fragment of the HIV-1 envelope from study participants in the DRC, we identified rare variants for complete genome sequencing. The basal branching of some of the complete genome sequences that we recovered suggests that these strains are more closely related to ancestral HIV-1 strains than to previously reported strains and is evidence that the local diversification of HIV in the DRC continues to outpace the diversity of global strains decades after the emergence of the pandemic.

Project description:BackgroundThe Democratic Republic of the Congo has had 15 Ebola virus disease (EVD) outbreaks, from 1976 to 2023. On June 1, 2020, the Democratic Republic of the Congo declared an outbreak of EVD in the western Équateur Province (11th outbreak), proximal to the 2018 Tumba and Bikoro outbreak and concurrent with an outbreak in the eastern Nord Kivu Province. In this Article, we assessed whether the 11th outbreak was genetically related to previous or concurrent EVD outbreaks and connected available epidemiological and genetic data to identify sources of possible zoonotic spillover, uncover additional unreported cases of nosocomial transmission, and provide a deeper investigation into the 11th outbreak.MethodsWe analysed epidemiological factors from the 11th EVD outbreak to identify patient characteristics, epidemiological links, and transmission modes to explore virus spread through space, time, and age groups in the Équateur Province, Democratic Republic of the Congo. Trained field investigators and health professionals recorded data on suspected, probable, and confirmed cases, including demographic characteristics, possible exposures, symptom onset and signs and symptoms, and potentially exposed contacts. We used blood samples from individuals who were live suspected cases and oral swabs from individuals who were deceased to diagnose EVD. We applied whole-genome sequencing of 87 available Ebola virus genomes (from 130 individuals with EVD between May 19 and Sept 16, 2020), phylogenetic divergence versus time, and Bayesian reconstruction of phylogenetic trees to calculate viral substitution rates and study viral evolution. We linked the available epidemiological and genetic datasets to conduct a genomic and epidemiological study of the 11th EVD outbreak.FindingsBetween May 19 and Sept 16, 2020, 130 EVD (119 confirmed and 11 probable) cases were reported across 13 Équateur Province health zones. The individual identified as the index case reported frequent consumption of bat meat, suggesting the outbreak started due to zoonotic spillover. Sequencing revealed two circulating Ebola virus variants associated with this outbreak-a Mbandaka variant associated with the majority (97%) of cases and a Tumba-like variant with similarity to the ninth EVD outbreak in 2018. The Tumba-like variant exhibited a reduced substitution rate, suggesting transmission from a previous survivor of EVD.InterpretationIntegrating genetic and epidemiological data allowed for investigative fact-checking and verified patient-reported sources of possible zoonotic spillover. These results demonstrate that rapid genetic sequencing combined with epidemiological data can inform responders of the mechanisms of viral spread, uncover novel transmission modes, and provide a deeper understanding of the outbreak, which is ultimately needed for infection prevention and control during outbreaks.FundingWHO and US Centers for Disease Control and Prevention.

Project description:Data collected during the 2012 Ebola virus disease (EVD) epidemic in the Democratic Republic of the Congo were analysed for clinical signs, symptoms and case fatality of EVD caused by Bundibugyo virus (BDBV), establishment of differential diagnoses, description of medical treatment and evaluation of the quality of clinical documentation. In a quantitative observational prospective study, global epidemiological data from 52 patients (34 patients within the community, 18 patients treated in the Ebola Treatment Centre) were entered anonymously into a database, subsequently matched and analysed. Relevant findings include an over-representation of females among community EVD cases (85.3%) and of community EVD cases in the age group of 15-54 years (82.4%). All ETC patients had fever (55.6% of all 18 ETC patients during their hospital stay) or self-reported fever (88.2% upon admission) at some point of time during their illness. Major symptoms of ETC patients during hospital stay included asthenia (82.4%), anorexia (82.4%), myalgia (70.6%), sore throat/difficulty swallowing (70.6%), arthralgia (76.5%) and nausea (70.6%). Gastrointestinal signs and symptoms (nausea, diarrhoea, vomiting) (76.4%) as well as general pain (94.1%) were frequent in ETC patients. The median duration of EVD was 18 days, while the mean incubation period was 11.3 days. Differential diagnosis of EVD included malaria (28.3%), intestinal parasitosis (10.9%), and infectious syndrome (10.9%). There was also an important variation in clinical evolvement. Quality of documentation was adversely affected by the way patient file contents were transferred from inside to outside the high-risk zone, entailing a mean mismatch value of 27.3% between patient file contents inside vs. outside the high-risk zone. This study adds further description of EVD (frequently non-specific signs and symptoms, non frequent bleeding, a long incubation period, long duration of disease) and emphasizes the need for improving clinical monitoring and documentation in EVD outbreak settings.

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

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

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