Viral genomics in Ebola virus research

Abstract

Filoviruses such as Ebola virus continue to pose a substantial health risk to humans. Advances in the sequencing and functional characterization of both pathogen and host genomes have provided a wealth of knowledge to clinicians, epidemiologists and public health responders during outbreaks of high-consequence viral disease. Here, we describe how genomics has been historically used to investigate Ebola virus disease outbreaks and how new technologies allow for rapid, large-scale data generation at the point of care. We highlight how genomics extends beyond consensus-level sequencing of the virus to include intra-host viral transcriptomics and the characterization of host responses in acute and persistently infected patients. Similar genomics techniques can also be applied to the characterization of non-human primate animal models and to known natural reservoirs of filoviruses, and metagenomic sequencing can be the key to the discovery of novel filoviruses. Finally, we outline the importance of reverse genetics systems that can swiftly characterize filoviruses as soon as their genome sequences are available.

Fig. 1. Geographical overview of filovirus discovery.

a | Outbreaks of Ebola virus disease (EVD) in Africa, including the number of confirmed cases, the case fatality rates and the number of publicly available Ebola virus (EBOV) draft genome sequences per outbreak, are depicted. Circles represent the relative size (in terms of the number of cases) of the outbreaks. Documented accidental laboratory-acquired infections have been excluded from this figure. b | Overview of global filovirus distribution, excluding EBOV. The place of isolation, known or suspected reservoir host and year of discovery are shown. The description of the distribution of non-EBOV filovirus disease outbreaks includes the total number of confirmed cases and the case fatality rate. BDBV, Bundibugyo virus; BOMV, Bombali virus; HUJV, Huángjiāo virus; LLOV, Lloviu virus; MARV, Marburg virus; MLAV, Měnglà virus; RAVV, Ravn virus; RESTV, Reston virus; SUDV, Sudan virus; TAFV, Taï Forest virus; XILV, Xīlǎng virus.

Fig. 2. Filovirus host reservoirs.

Complete or coding-complete filovirus genome sequences have been obtained from cave-dwelling and house-dwelling bats and highly diverse fish on the African, Asian and European continents (see Fig. 1 for continental distribution). The pathogenic potential of most filoviruses remains unclear, as does the transmission route of pathogenic filoviruses proven to infect humans and pigs or of pathogenic filoviruses suspected to infect chimpanzees, duikers and gorillas. Animals that have been proven to be infected by filoviruses are indicated in black; grey animals are suspected but unproven reservoirs of the indicated viruses. Solid arrows indicate highly likely transmission routes; dashed arrows indicate hypothesized transmission routes. BDBV, Bundibugyo virus; BOMV, Bombali virus; EBOV, Ebola virus; HUJV, Huángjiāo virus; LLOV, Lloviu virus; MARV, Marburg virus; MLAV, Měnglà virus; RAVV, Ravn virus; RESTV, Reston virus; SUDV, Sudan virus; TAFV, Taï Forest virus; XILV, Xīlàng virus.

Fig. 3. Ebola virus transmission.

Following a zoonotic transmission event, sequencing the Ebola virus (EBOV) genome in real-time can help epidemiologists pinpoint the likely route of infection and of transmission during an outbreak of Ebola virus disease (EVD). A theoretical median-joining haplotype network of the Nord-Kivu/Sud-Kivu/Ituri Province EVD outbreak caused by EBOV/“Itu” in the Democratic Republic of the Congo (provinces are indicated on the map) provides different hypotheses that may explain person-to-person transmission events. A consistent number of genomic changes occurring in a specific window of time can indicate acute transmission events (that is, transmission via close contact with an individual with EVD, bottom left). The detection of transmission depends on diagnostics and sampling frequency. When sampling frequency is low, flare-up cases of EVD can appear with limited epidemiological data and with an unexpectedly large number of differences to earlier sampled haplotypes, which may point to undetected transmission networks (middle left; indicated by dashed lines). When viral diversity cannot be explained by spillover and spatial–temporal estimations, a secondary spillover may be possible (top left). Persistent infections through sexual transmission present with low genetic diversity (that is, with a slow evolutionary rate) over periods (bottom right) that are much longer than expected for acute reintroduction at the expected evolutionary rate (top right). A similar analysis was performed during the first discovery of sexual transmission during the 2013–2016 Western African EVD outbreak, and a theoretical example is shown (bottom right). This example indicates the number of days after the initial presentation of symptoms at which an acutely infected male is sampled (day 4) and the day at which he recovers (day 20). On day 175, the sexual partner of this male becomes symptomatic owing to a very similar EBOV genotype, confirmed with epidemiological information and visualized using a median-joining haplotype network.

Fig. 4. Persistent Ebola virus infection in immune-privileged sites.

a | Ebola virus (EBOV) can break down the blood–brain barrier and persist in microglial cells. b | EBOV has been detected in aqueous humour extracted from the anterior chamber of the eye of human survivors. However, EBOV is mainly detected in the vitreous chamber and in the inner limiting membrane of the retina to which it is adjacent in rhesus monkeys that survive experimental infection with EBOV. c | The blood–testis barrier created by tight junctions between Sertoli cells protects sperm from immune recognition in seminiferous tubules, the main site of EBOV persistence in testis. Sertoli cells are the main cellular reservoir of EBOV persistence. Image courtesy of W. Discher.

Fig. 5. Reverse functional genomics for characterizing authentic Ebola virus isolates.

Reverse functional genomics facilitates external support in the response to outbreaks of Ebola virus disease (EVD) that occur in remote areas that lack in-house resources to test available medical countermeasures. Rapid, high accuracy, complete genome sequences determined in-country are shared with out-of-country collaborators to evaluate key genomic and proteomic changes in Ebola virus (EBOV) that may affect the efficacy of available therapeutics (part a). For example, changes in the double-stranded RNA (dsRNA)-binding site of the EBOV polymerase cofactor viral protein 35 (VP35), a protein targeted by several therapeutics, can be identified from the sequencing data obtained for a new EBOV isolate. Changes in this region of VP35 may compromise the efficacy of treatments. Indeed, if two available therapeutic agents (hypothetical treatment A and hypothetical treatment B) target VP35, reverse genetic systems can produce replicative EBOVs de novo that contain the changes identified in VP35 (part b). These replicative EBOVs can then be used for the in vitro and in vivo therapeutic evaluation of both hypothetical treatments; data obtained using this approach can inform on which treatment is potentially more efficacious against the EBOV isolate causing the outbreak.

Fig. 6. Therapeutic and phylodynamic perspectives of the emergence of treatment-resistant Ebola virus mutants.

a | During an Ebola virus (EBOV) infection, the low-fidelity viral RNA-directed RNA polymerase creates replication errors that lead to increasing intra-host variation through successive replications (that is, genetic drift occurs). Therapeutic monoclonal antibodies, such as MB-003, neutralize EBOV, and infected patients subsequently recover. However, such treatment can also create a ‘therapeutic bottleneck’ in which intra-host diversity alters to select genotypes that only harbour the escape variant that continues to replicate in current and future hosts. b | The evolution of EBOV intra-host populations over time, pre-treatment and post-treatment, and the genomic bottleneck, can be visualized by estimating a phylogenetic tree (notable events along the tree are indicated by colourless circles). Samples can be characterized using next-generation sequencing (NGS) at various time points. Each coloured circle represents a finished EBOV genome from an individual patient. After an inter-host bottleneck, viral diversity should be low in the earliest phase of infection (1). As EBOV continually replicates, expanding intra-host diversity can create heterogeneous subpopulations (2, blue circles). Once exposed to treatment (3, dashed line), EBOV intra-host populations may be countered and eliminated, demonstrating an effective treatment without further intra-host replication or diversification (green circles). However, a small subpopulation surviving the therapeutic bottleneck may allow escape mutants to subvert treatment (4) and continue diversifying into novel, treatment-resistant genotypes (5, red circles).