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Genotypic anomaly in Ebola virus strain circulating in Magazine Wharf area, Freetown, Sierra Leone, 2015
Abstract
The Magazine Wharf area, Freetown, Sierra Leone was a focus of ongoing Ebola virus transmission from late June 2015. Viral genomes linked to this area contain a series of 13 T to C substitutions in a 150 base pair intergenic region downstream of viral protein 40 open reading frame, similar to the Ebolavirus/H.sapienswt/ SLE/2014/Makona-J0169 strain (J0169) detected in the same town in November 2014. This suggests that recently circulating viruses from Freetown descend from a J0169-like virus. © 2015, European Centre for Disease Prevention and Control (ECDC). All rights reserved.
... In another example, mouseadaptation of Ravn virus, which represents a distinct clade within the genus Marburgvirus, led to the accumulation of 30 A→G changes within sequences corresponding to the 600 nucleotide long 3'UTR of the glycoprotein (GP) mRNA (12). During the 2014-2016 West Africa EBOV outbreak varied A→G changes were identified in the negative-sense viral RNAs of different isolates, with sequences encoding the VP40 3'UTR being a hotspot for such changes (13)(14)(15)(16)(17)(18)(19). What functional impact ADAR1 editing of 3'UTRs may have on EBOV and MARV replication is unclear. ...
... During the 2014-2016 West Africa EBOV outbreak varied A→G changes were identified in the negative-sense viral RNAs of different isolates, with sequences encoding the VP40 3'UTR being a hotspot for such changes (13)(14)(15)(16)(17)(18)(19). A comprehensive analysis of 1086 publicly available fulllength EBOV-Makona genome sequences identified 49 with clusters of A→G substitutions (24). ...
... ADAR1 also appears to act on EBOV. During the 2014-2016 West Africa EBOV outbreak varied A→G changes were identified in the negative-sense viral RNAs of different isolates, with sequences encoding the VP40 3'UTR being a hotspot for such changes (13)(14)(15)(16)(17)(18)(19). During the 2014-. ...
The filovirus family includes deadly pathogens such as Ebola virus (EBOV) and Marburg virus (MARV). A substantial portion of filovirus genomes encode 5’ and 3’ untranslated regions (UTRs) of viral mRNAs. Select viral genomic RNA sequences corresponding to 3’UTRs are prone to editing by ADAR1. A reporter mRNA approach, in which different 5’ or 3’UTRs were inserted into luciferase encoding mRNAs, demonstrates that MARV 3’UTRs yield different levels of reporter gene expression suggesting modulation of translation. The modulation occurs in cells unable to produce miRNAs and can be recapitulated in a minigenome assay. Deletion mutants identified negative regulatory regions at end of the MARV NP and L 3’UTRs. Apparent ADAR1 editing mutants were previously identified within the MARV NP 3’UTR. Introduction of these changes into the MARV nucleoprotein (NP) 3’UTR or deletion of the region targeted for editing enhances translation, as indicated by reporter assays and polysome analysis. In addition, the parental NP 3’UTR, but not the edited or deletion mutant NP 3’UTRs, induce a type I interferon (IFN) response upon transfection into cells. Because some EBOV isolates from the West Africa outbreak exhibited ADAR1 editing of the VP40 3’UTR, VP40 3’UTRs with parental and edited sequences were similarly assayed. The EBOV VP40 3’UTR edits also enhanced translation but neither the wildtype nor the edited 3’UTRs induced IFN. These findings implicate filoviral mRNA 3’UTRs as negative regulators of translation that can be inactivated by innate immune responses that induce ADAR1.
Importance
UTRs comprise a large percentage of filovirus genomes and are apparent targets of editing by ADAR1, an enzyme with pro- and antiviral activities. However, the functional significance of the UTRs and of ADAR1 editing have been uncertain. This study demonstrates that MARV and EBOV 3’UTRs can modulate translation, in some cases negatively. ADAR1 editing or deletion of select regions within the translation suppressing 3’UTRs, relieves the negative effects of the UTRs. These data indicate that filovirus 3’UTRs contain translation regulatory elements that are modulated by activation of ADAR1, suggesting a complex interplay between filovirus gene expression and innate immunity.
... Previous research demonstrated that the hotspots for non-synonymous substitutions are likely located in regions with a lower level of functional constraint of the encoded viral proteins [3]. Moreover, the intra-host selection for EBOV to escape from a developing humoral immune response may drive the diversifying selection of glycoprotein (GP) mucin-like domain, as Biosafety and Health 1(1) (2019) [14][15][16][17][18][19][20][21][22][23][24] shown by the enrichment of mutations within the B-cell epitopes of GP [4], although this was not observed in Ni's study [15]. On the other hand, short stretches of intra-hostT to C (TNC) mutations were also observed [1,4]. ...
... This was speculated as a result of adenosine deaminases acting on RNA (ADARs), which is yet unclear [16]. It has been reported that viruses with the 13 TNC mutations (genome positions 5512-5631) continued to circulate in the Magazine Wharf area, Freetown, Sierra Leone, causing several infections [17]. ...
... In particular, ten strains possessed the 13 TNC mutations within positions 5512-5631 ( Figure 5C). The prototype strain with the 13 TNC mutations was J0169 (KP759706), sequenced from the Magazine Wharf area, Freetown, Sierra Leone in November 2014 [17]. It has been reported that J0169-like EBOV continued to circulate in this region and had infected at least three additional patients by July 2015. ...
The onsite next generation sequencing (NGS) of Ebola virus (EBOV) genomes during the 2013–2016 Ebola epidemic in Western Africa provides an opportunity to trace the origin, transmission, and evolution of this virus. Herein, we have diagnosed a cohort of EBOV patients in Sierra Leone in 2015, during the late phase of the outbreak. The surviving EBOV patients had a recovery process characterized by decreasing viremia, fever, and biochemical parameters. EBOV genomes sequenced through the longitudinal blood samples of these patients showed dynamic intra-host substitutions of the virus during acute infection, including the previously described short stretches of 13 serial T>C mutations. Remarkably, within individual patients, samples collected during the early phase of infection possessed Ts at these nucleotide sites, whereas they were replaced by Cs in samples collected in the later phase, suggesting that these short stretches of T>C mutations could emerge independently. In addition, up to a total of 35 nucleotide sites spanning the EBOV genome were mutated coincidently. Our study showed the dynamic intra-host adaptation of EBOV during patient recovery and gave more insight into the complex EBOV-host interactions.
... Until recently, genomic studies of infectious disease outbreaks were necessarily retrospective, occurring after the pathogen had either been eradicated or developed endemic transmission in the host population [8][9][10][11][12] . However, recent developments in high-throughput next generation sequencing (NGS) [13][14][15][16] enabled rapid and in-depth viral genomic surveillance during the 2013-2016 EVD epidemic [1][2][3][17][18][19][20][21][22][23][24][25][26] . Indeed, with the advent of NGS it is now possible to generate pathogen genomic data directly from diagnostic patient samples 2,3,17-27 within days or hours of the sample being taken 25,26 , and in challenging field situations 19,23,25,26 . ...
... However, recent developments in high-throughput next generation sequencing (NGS) [13][14][15][16] enabled rapid and in-depth viral genomic surveillance during the 2013-2016 EVD epidemic [1][2][3][17][18][19][20][21][22][23][24][25][26] . Indeed, with the advent of NGS it is now possible to generate pathogen genomic data directly from diagnostic patient samples 2,3,17-27 within days or hours of the sample being taken 25,26 , and in challenging field situations 19,23,25,26 . The resulting large-scale sequence data sets provide new opportunities for the epidemiological investigation of transmission chains and the improvement of outbreak responses 28 . ...
... Indeed, the 2013-2016 EVD epidemic is arguably the first in which genomic data have been used directly in a real-time public health setting, helping to inform policies and infection control 2,7,25,26 . That some of these studies were undertaken under difficult field conditions 19,23,25,26 highlights the potential for portable genomic sequencing to transform outbreak responses 7,25 . ...
The 2013-2016 epidemic of Ebola virus disease in West Africa was of unprecedented magnitude and changed our perspective on this lethal but sporadically emerging virus. This outbreak also marked the beginning of large-scale real-time molecular epidemiology. Here, we show how evolutionary analyses of Ebola virus genome sequences provided key insights into virus origins, evolution and spread during the epidemic. We provide basic scientists, epidemiologists, medical practitioners and other outbreak responders with an enhanced understanding of the utility and limitations of pathogen genomic sequencing. This will be crucially important in our attempts to track and control future infectious disease outbreaks.
... Indeed, some such clustered changes, localized within the Bcell epitope, were observed in a handful of patient sequences (Park et al. 2015;Dudas et al. 2017), though such changes can also be introduced by a biased RNA polymerase (Park et al. 2015) or be selected through strong immune pressure. Of the currently identified putatively ADAR-hypermutated sequences, they appear to be capable of human-to-human transmission (Smits et al. 2015;Dudas et al. 2017), although they seem not to possess any fitness advantages over other lineages (Smits et al. 2015). Nonetheless, the surveillance of such variants is important, particularly for large-scale outbreaks or epidemics, as some such variants may re-emerge from Ebola virus disease survivors (Whitmer et al. 2018). ...
... Indeed, some such clustered changes, localized within the Bcell epitope, were observed in a handful of patient sequences (Park et al. 2015;Dudas et al. 2017), though such changes can also be introduced by a biased RNA polymerase (Park et al. 2015) or be selected through strong immune pressure. Of the currently identified putatively ADAR-hypermutated sequences, they appear to be capable of human-to-human transmission (Smits et al. 2015;Dudas et al. 2017), although they seem not to possess any fitness advantages over other lineages (Smits et al. 2015). Nonetheless, the surveillance of such variants is important, particularly for large-scale outbreaks or epidemics, as some such variants may re-emerge from Ebola virus disease survivors (Whitmer et al. 2018). ...
Adenosine Deaminases that Act on RNA (ADARs) are RNA editing enzymes that play a dynamic and nuanced role in regulating transcriptome and proteome diversity. This editing can be highly selective, affecting a specific site within a transcript, or nonselective, resulting in hyperediting. ADAR editing is important for regulating neural functions and autoimmunity, and has a key role in the innate immune response to viral infections, where editing can have a range of pro- or antiviral effects and can contribute to viral evolution. Here we examine the role of ADAR editing across a broad range of viral groups. We propose that the effect of ADAR editing on viral replication, whether pro- or antiviral, is better viewed as an axis rather than a binary, and that the specific position of a given virus on this axis is highly dependent on virus- and host-specific factors, and can change over the course of infection. However, more research needs to be devoted to understanding these dynamic factors and how they affect virus-ADAR interactions and viral evolution. Another area which warrants significant attention is the effect of virus-ADAR interactions on host-ADAR interactions, particularly in light of the crucial role of ADAR in regulating neural functions. Answering these questions will be essential to developing our understanding of the relationship between ADAR editing and viral infection. In turn, this will further our understanding of the effects of viruses such as SARS-CoV-2, as well as many others, and thereby influence our approach to treating these deadly diseases.
... Apparent ADAR1 editing of the VP40 39 UTR from EBOV Makona isolates results in increased translation. During the 2014 to 2016 West Africa EBOV outbreak, various A!G changes were identified in the negative-sense viral RNAs of different isolates, with sequences encoding the VP40 39 UTR being a hot spot for such changes (13)(14)(15)(16)(17)(18)(19). A comprehensive analysis of 1,086 publicly available full-length EBOV-Makona genome sequences identified 49 with clusters of A!G substitutions (25). ...
... ADAR1 also appears to act on EBOV. During the 2014 to 2016 West Africa EBOV outbreak, varied A!G changes were identified in the negative-sense viral RNAs of different isolates, with sequences encoding the VP40 39 UTR being a hot spot for such changes (13)(14)(15)(16)(17)(18)(19)25). Of these, 30 had A!G clusters in sequences corresponding to 39 UTRs, and 15 of these had clusters in sequences corresponding to the VP40 39 UTR. ...
The filovirus family includes deadly pathogens such as Ebola virus (EBOV) and Marburg virus (MARV). A substantial portion of filovirus genomes encode 5’ and 3’ untranslated regions (UTRs) of viral mRNAs. Select viral genomic RNA sequences corresponding to 3’UTRs are prone to editing by ADAR1. A reporter mRNA approach, in which different 5’ or 3’UTRs were inserted into luciferase encoding mRNAs, demonstrates that MARV 3’UTRs yield different levels of reporter gene expression suggesting modulation of translation. The modulation occurs in cells unable to produce miRNAs and can be recapitulated in a MARV minigenome assay. Deletion mutants identified negative regulatory regions at end of the MARV NP and L 3’UTRs. Apparent ADAR1 editing mutants were previously identified within the MARV NP 3’UTR. Introduction of these changes into the MARV nucleoprotein (NP) 3’UTR or deletion of the region targeted for editing enhances translation, as indicated by reporter assays and polysome analysis. In addition, the parental NP 3’UTR, but not the edited or deletion mutant NP 3’UTRs, induce a type I interferon (IFN) response upon transfection into cells. Because some EBOV isolates from the West Africa outbreak exhibited ADAR1 editing of the VP40 3’UTR, VP40 3’UTRs with parental and edited sequences were similarly assayed. The EBOV VP40 3’UTR edits also enhanced translation but neither the wildtype nor the edited 3’UTRs induced IFN. These findings implicate filoviral mRNA 3’UTRs as negative regulators of translation that can be inactivated by innate immune responses that induce ADAR1.
Importance
UTRs comprise a large percentage of filovirus genomes and are apparent targets of editing by ADAR1, an enzyme with pro- and antiviral activities. However, the functional significance of the UTRs and of ADAR1 editing have been uncertain. This study demonstrates that MARV and EBOV 3’UTRs can modulate translation, in some cases negatively. ADAR1 editing or deletion of select regions within the translation suppressing 3’UTRs, relieves the negative effects of the UTRs. These data indicate that filovirus 3’UTRs contain translation regulatory elements that are modulated by activation of ADAR1, suggesting a complex interplay between filovirus gene expression and innate immunity.
... U-to-C hyper-editing is not unique to SAVS, similar patterns have also been observed within AAVS (Dudas et al., 2017;Ni et al., 2016;Park et al., 2015;Smits et al., 2015;Tong et al., 2015), however, it is currently unknown whether acute-and persistence-specific hyper-edited genomic regions exist. Here, we observed that most acute editing occurred within non-coding regions and the highest rates of hyper-editing were on the 3 0 untranslated NP and VP40 transcripts. ...
... Most strikingly, U-to-C and G-to-A hyper-editing has been observed following persistent measles infections in the brain 4 and 6 months after initial disease (Baczko et al., 1993;Cattaneo et al., 1988), and a similar pattern of U-to-C edits were observed on the NP 3 0 untranslated region during in vitro Marburg infection (Shabman et al., 2014). Viral genomes with hyperedits in the VP40 5 0 (viral genome orientation) tail were observed in the Magazine Wharf area of SLE after a disease-free 2-week period, potentially representing re-emergence from an EVD survivor, although both of these cases were also associated with ''multiple high-risk contacts'' (Smits et al., 2015;WHO, 2015). While there are some established links between ADAR and interferon signaling (George and Samuel, 1999;Pfaller et al., 2011;Rice et al., 2012), teasing apart the pro-and anti-viral interactions, along with their relationship to viral persistence, will be an important area for future research. ...
Following cessation of continuous Ebola virus (EBOV) transmission within Western Africa, sporadic EBOV disease (EVD) cases continued to re-emerge beyond the viral incubation period. Epidemiological and genomic evidence strongly suggests that this represented transmission from EVD survivors. To investigate whether persistent infections are characterized by ongoing viral replication, we sequenced EBOV from the semen of nine EVD survivors and a subset of corresponding acute specimens. EBOV evolutionary rates during persistence were either similar to or reduced relative to acute infection rates. Active EBOV replication/transcription continued during convalescence, but decreased over time, consistent with viral persistence rather than viral latency. Patterns of genetic divergence suggest a moderate relaxation of selective constraints within the sGP carboxy-terminal tail during persistent infections, but do not support widespread diversifying selection. Altogether, our data illustrate that EBOV persistence in semen, urine, and aqueous humor is not a quiescent or latent infection.
... We detect a total of 15 hypermutation patterns with up to 13 T-to-C mutations within 35 to 145 nucleotides. Of these patterns, 11 are unique to a single genome and 4 are shared across multiple isolates, suggesting that occasionally viruses survive hypermutation are transmitted (Smits et al., 2015). Putative tracts of T-to-C hypermutation almost exclusively occur within non-coding intergenic regions, where their effects on viral fitness are presumably minimal. ...
The 2013-2016 epidemic of Ebola virus disease in West Africa was of unprecedented magnitude, duration and impact. Extensive collaborative sequencing projects have produced a large collection of over 1600 Ebola virus genomes, representing over 5% of known cases, unmatched for any single human epidemic. In this comprehensive analysis of this entire dataset, we reconstruct in detail the history of migration, proliferation and decline of Ebola virus throughout the region. We test the association of geography, climate, administrative boundaries, demography and culture with viral movement among 56 administrative regions. Our results show that during the outbreak viral lineages moved according to a classic ‘gravity’ model, with more intense migration between larger and more proximate population centers. Notably, we find that despite a strong attenuation of international dispersal after border closures, localized cross-border transmission beforehand had already set the seeds for an international epidemic, rendering these measures relatively ineffective in curbing the epidemic. We use this empirical evidence to address why the epidemic did not spread into neighboring countries, showing that although these regions were susceptible to developing significant outbreaks, they were also at lower risk of viral introductions. Finally, viral genome sequence data uniquely reveals this large epidemic to be a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help inform approaches to intervention in such epidemics in the future.
... A publicly available dataset of 1610 Ebola virus genomes sequenced by various groups (Baize et al., 2014;Gire et al., 2014;Park et al., 2015;Carroll et al., 2015;Kugelman et al., 2015;Ladner et al., 2015;Simon-Loriere et al., 2015;Tong et al., 2015;Arias et al., 2016;Smits et al., 2015;Quick et al., 2015) and systematised in Dudas et al. (2017) was filtered to remove sequences where over 1% of the genome sequence was ambiguous or the precise location down to administrative division was not available, leaving 943 genomes. A set of 600 viral genomes were randomly sampled from the filtered dataset of 943 high quality genomes. ...
Inexpensive pathogen genome sequencing has had a transformative effect on the field of phylodynamics, where ever increasing volumes of data have promised real-time insight into outbreaks of infectious disease. As well as the sheer volume of pathogen isolates being sequenced, the sequencing of whole pathogen genomes, rather than select loci, has allowed phylogenetic analyses to be carried out at finer time scales, often approaching serial intervals for infections caused by rapidly evolving RNA viruses. Despite its utility, whole genome sequencing of pathogens has not been adopted universally and targeted sequencing of loci is common in some pathogen-specific fields. In this study we aim to highlight the utility of sequencing whole genomes of pathogens by re-analysing a well-characterised collection of Ebola virus sequences in the form of complete viral genomes (~19kb long) or the rapidly evolving glycoprotein (GP, ~2kb long) gene. We quantify changes in phylogenetic, temporal, and spatial inference resolution as a result of this reduction in data and compare these to theoretical expectations. We propose a simple intuitive metric for quantifying temporal resolution, i.e. the time scale over which sequence data might be informative of various processes as a quick back-of-the-envelope calculation of statistical power available to molecular clock analyses.
... This epidemic is the largest EVD epidemic on record with over 28,000 infections and more than 11,000 deaths [2]. EBOV replication generated thousands of mutations over numerous rounds of human-to-human transmission [3][4][5][6][7][8][9][10][11][12][13][14], but only a handful of mutations became common enough to have had a sizeable impact on the epidemic [3][4][5][6][7][8][9]. One key mutation, C6283U, results in an A82V substitution in the EBOV glycoprotein (GP-A82V) and has been studied extensively through well-established BSL-2 surrogate model systems and live virus BSL-4 studies. ...
For highly pathogenic viruses, reporter assays that can be rapidly performed are critically needed to identify potentially functional mutations for further study under maximal containment (e.g., biosafety level 4 [BSL-4]). The Ebola virus nucleoprotein (NP) plays multiple essential roles during the viral life cycle, yet few tools exist to study the protein under BSL-2 or equivalent containment. Therefore, we adapted reporter assays to measure NP oligomerization and virion-like particle (VLP) production in live cells and further measured transcription and replication using established minigenome assays. As a proof-of-concept, we examined the NP-R111C substitution, which emerged during the 2013-2016 Western African Ebola virus disease epidemic and rose to high frequency. NP-R111C slightly increased NP oligomerization and VLP budding but slightly decreased transcription and replication. By contrast, a synthetic charge-reversal mutant, NP-R111E, greatly increased oligomerization but abrogated transcription and replication. These results are intriguing in light of recent structures of NP oligomers, which reveal that the neighboring residue, K110, forms a salt bridge with E349 on adjacent NP molecules. By developing and utilizing multiple Viruses 2020, 12, 105 2 of 27 reporter assays, we find that the NP-111 position mediates a complex interplay between NP's roles in protein structure, virion budding, and transcription and replication.
... A publicly available dataset of 1610 Ebola virus genomes sequenced by various groups [19,20,33,[48][49][50][51][52][53][54][55] and systematised in [11] was filtered to remove sequences where over 1% of the genome sequence was ambiguous or the precise location down to administrative division was not available leaving 943 genomes. A set of 600 viral genomes were randomly sampled from the filtered dataset of 943 high quality genomes. ...
Background:
Inexpensive pathogen genome sequencing has had a transformative effect on the field of phylodynamics, where ever increasing volumes of data have promised real-time insight into outbreaks of infectious disease. As well as the sheer volume of pathogen isolates being sequenced, the sequencing of whole pathogen genomes, rather than select loci, has allowed phylogenetic analyses to be carried out at finer time scales, often approaching serial intervals for infections caused by rapidly evolving RNA viruses. Despite its utility, whole genome sequencing of pathogens has not been adopted universally and targeted sequencing of loci is common in some pathogen-specific fields.
Results:
In this study we highlighted the utility of sequencing whole genomes of pathogens by re-analysing a well-characterised collection of Ebola virus sequences in the form of complete viral genomes (≈19 kb long) or the rapidly evolving glycoprotein (GP, ≈2 kb long) gene. We have quantified changes in phylogenetic, temporal, and spatial inference resolution as a result of this reduction in data and compared these to theoretical expectations.
Conclusions:
We propose a simple intuitive metric for quantifying temporal resolution, i.e. the time scale over which sequence data might be informative of various processes as a quick back-of-the-envelope calculation of statistical power available to molecular clock analyses.
... 21 Initially, data were generated in laboratories outside of the affected countries, with the establishment of in-country sequencing later in the outbreak. [22][23][24] Within 10 days of the 2018 Équateur Province EVD outbreak declaration, the MinION platform was used to sequence a short amplicon from the first two samples that were transported back to INRB. 5 Less than 6 weeks after the declaration of the outbreak, a sequencing capacity incorporating the Illumina iSeq100 and protocols for generation of coding-complete EBOV genomes was established at INRB. As the outbreak was quickly contained, the near-complete viral genome data generated from the 2018 Équateur Province outbreak became part of a retrospective study. ...
Background
The 2018 Ebola virus disease (EVD) outbreak in Équateur Province, Democratic Republic of the Congo, began on May 8, and was declared over on July 24; it resulted in 54 documented cases and 33 deaths. We did a retrospective genomic characterisation of the outbreak and assessed potential therapeutic agents and vaccine (medical countermeasures).
Methods
We used target-enrichment sequencing to produce Ebola virus genomes from samples obtained in the 2018 Équateur Province outbreak. Combining these genomes with genomes associated with known outbreaks from GenBank, we constructed a maximum-likelihood phylogenetic tree. In-silico analyses were used to assess potential mismatches between the outbreak strain and the probes and primers of diagnostic assays and the antigenic sites of the experimental rVSVΔG-ZEBOV-GP vaccine and therapeutics. An in-vitro flow cytometry assay was used to assess the binding capability of the individual components of the monoclonal antibody cocktail ZMapp.
Findings
A targeted sequencing approach produced 16 near-complete genomes. Phylogenetic analysis of these genomes and 1011 genomes from GenBank revealed a distinct cluster, confirming a new Ebola virus variant, for which we propose the name “Tumba”. This new variant appears to have evolved at a slower rate than other Ebola virus variants (0·69 × 10−3 substitutions per site per year with “Tumba” vs 1·06 × 10−3 substitutions per site per year without “Tumba”). We found few sequence mismatches in the assessed assay target regions and antigenic sites. We identified nine amino acid changes in the Ebola virus surface glycoprotein, of which one resulted in reduced binding of the 13C6 antibody within the ZMapp cocktail.
Interpretation
Retrospectively, we show the feasibility of using genomics to rapidly characterise a new Ebola virus variant within the timeframe of an outbreak. Phylogenetic analysis provides further indications that these variants are evolving at differing rates. Rapid in-silico analyses can direct in-vitro experiments to quickly assess medical countermeasures.
Funding
Defense Biological Product Assurance Office.
... We detected a total of 15 hypermutation patterns with up to 13 T-to-C mutations within 35 to 145 nucleotides. Of these patterns, 11 are unique to a single genome and 4 are shared across multiple isolates, suggesting that occasionally viruses that survive hypermutation are transmitted 47 . Putative tracts of T-to-C hypermutation almost exclusively occur within non-coding intergenic regions, where their effects on viral fitness are presumably minimal. ...
The 2013–2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic ‘gravity’ model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics.
... as detected in this study), and the other in the east of Sierra Leone (lineage 3.1.2) [15]. The low case fatality rate observed in the new clade may reflect the decreased virulence of the virus and its consequential evasion of surveillance. ...
We performed Ebola virus disease diagnosis and viral load estimation for Ebola cases in Sierra Leone during the late stage of the 2014–2015 outbreak (January–March 2015) and analyzed antibody and cytokine levels and the viral genome sequences. Ebola virus disease was confirmed in 86 of 1001 (9.7%) patients, with an overall case fatality rate of 46.8%. Fatal cases exhibited significantly higher levels of viral loads, cytokines, and chemokines at late stages of infection versus early stage compared with survivors. The viruses converged in a new clade within sublineage 3.2.4, which had a significantly lower case fatality rate.
... Genetic sequences from 1031 human infections of EBOV in Sierra Leone were obtained from a openly accessible compilation 22 of previously-published sequencing data [25][26][27][28] . In Figure 1A and Figure S4, we show the time course of all confirmed EBOV cases (black trace) in Sierra Leone 24 compared with the number of sequenced virus genomes (red trace). ...
Containing the recent West African outbreak of Ebola virus (EBOV) required the deployment of substantial global resources. Operationally, health workers and surveillance teams treated cases, collected genetic samples, and tracked case contacts. Despite the substantial progress in analyzing and modeling EBOV epidemiological data, a complete characterization of the spatiotemporal spread of Ebola cases remains a challenge. In this work, we offer a novel perspective on the EBOV epidemic that utilizes virus genome sequences to inform population-level, spatial models. Calibrated to phylogenetic linkages, these dynamic spatial models provide unique insight into the disease mobility of EBOV in Sierra Leone. Further, we developed a model selection framework that identifies important epidemiological variables influencing the spatiotemporal propagation of EBOV. Consistent with other investigations, our results show that the spread of EBOV during the beginning and middle portions of the epidemic strongly depended on the size of and distance between populations. Our analysis also revealed a substantial decline in the dependence on population size at the end of the epidemic, coinciding with the large-scale intervention campaign: Operation Western Area Surge. More generally, we believe this framework, pairing molecular diagnostics with dynamic models, has the potential to be a powerful forecasting tool along with offering operationally-relevant guidance for surveillance and sampling strategies during an epidemic.
... We detect a total of 15 hypermutation patterns with up to 13 T-to-C mutations within 35 to 145 nucleotides. Of these patterns, 11 are unique to a single genome and 4 are shared across multiple isolates, suggesting that occasionally viruses survive hypermutation are transmitted (Smits et al., 2015). Putative tracts of T-to-C hypermutation almost exclusively occur within non-coding intergenic regions, where their effects on viral fitness are presumably minimal. ...
The 2013–2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic ‘gravity’ model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics.
... Forty-eight EBOV whole genome sequences from 44 patients were determined. The sequencing results of the last 4 patients detected in the Freetown laboratory, results were obtained and reported to WHO within two weeks of sample collections confirming a chain of transmission in Freetown's Magazine Warfs area [11]. ...
One of the pillars in the emergency response to the 2014-2016 Ebola virus epidemic in West Africa has been the local deployment of temporary laboratories by the international community in collaboration with local authorities. The Dutch Ministry of Foreign Affairs financed and supported the deployment of three mobile container laboratories to Sierra Leone (Freetown and Koidu) and Liberia (Sinje). We describe the organisation of the three laboratories, the biosafety aspects, the quality control, and the performance in Ebola virus and malaria diagnostics during the period of deployment.
1 2 To investigate how Ebola virus phenotypes changed during the 2013-2016 Western African 3 Ebola virus disease epidemic, we examined a key viral mutation that rose to high frequency: an 4 R111C substitution in the viral nucleoprotein (NP). Though NP plays many essential roles 5 during infection, there are a limited number of assays for studying these functions. We 6 developed new reporter assays to measure virion-like particle (VLP) production and NP 7 oligomerization in live cells under biosafety level 2 conditions. We found that NP-R111C 8 significantly enhanced VLP production and slightly increased NP oligomerization without 9 impairing viral transcription and replication. By contrast, a synthetic charge-reversal mutant, NP-10 R111E, greatly increased oligomerization but dramatically reduced transcription and replication. 11 We detected an interaction of NP with the cellular clathrin adaptor protein-1 (AP-1) complex, 12 which may explain how NP facilitates VLP production. Our study provides enhanced methods to 13 study NP and indicates a complex interplay between NP's roles in virion budding, protein 14 structure, and transcription and replication.
An epidemic of Ebola virus disease of unprecedented scale has been ongoing for more than a year in West Africa. As of 29 April 2015, there have been 26,277 reported total cases (of which 14,895 have been laboratory confirmed) resulting in 10,899 deaths. The source of the outbreak was traced to the prefecture of Guéckédou in the forested region of southeastern Guinea. The virus later spread to the capital, Conakry, and to the neighbouring countries of Sierra Leone, Liberia, Nigeria, Senegal and Mali. In March 2014, when the first cases were detected in Conakry, the Institut Pasteur of Dakar, Senegal, deployed a mobile laboratory in Donka hospital to provide diagnostic services to the greater Conakry urban area and other regions of Guinea. Through this process we sampled 85 Ebola viruses (EBOV) from patients infected from July to November 2014, and report their full genome sequences here. Phylogenetic analysis reveals the sustained transmission of three distinct viral lineages co-circulating in Guinea, including the urban setting of Conakry and its surroundings. One lineage is unique to Guinea and closely related to the earliest sampled viruses of the epidemic. A second lineage contains viruses probably reintroduced from neighbouring Sierra Leone on multiple occasions, while a third lineage later spread from Guinea to Mali. Each lineage is defined by multiple mutations, including non-synonymous changes in the virion protein 35 (VP35), glycoprotein (GP) and RNA-dependent RNA polymerase (L) proteins. The viral GP is characterized by a glycosylation site modification and mutations in the mucin-like domain that could modify the outer shape of the virion. These data illustrate the ongoing ability of EBOV to develop lineage-specific and potentially phenotypically important variation.
The 2013-2015 Ebola virus disease (EVD) epidemic is caused by the Makona variant of Ebola virus (EBOV). Early in the epidemic, genome sequencing provided insights into virus evolution and transmission and offered important information for outbreak response. Here, we analyze sequences from 232 patients sampled over 7 months in Sierra Leone, along with 86 previously released genomes from earlier in the epidemic. We confirm sustained human-to-human transmission within Sierra Leone and find no evidence for import or export of EBOV across national borders after its initial introduction. Using high-depth replicate sequencing, we observe both host-to-host transmission and recurrent emergence of intrahost genetic variants. We trace the increasing impact of purifying selection in suppressing the accumulation of nonsynonymous mutations over time. Finally, we note changes in the mucin-like domain of EBOV glycoprotein that merit further investigation. These findings clarify the movement of EBOV within the region and describe viral evolution during prolonged human-to-human transmission.
West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded 1–3. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/ Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral hae-morrhagic fever outbreak. We used a deep sequencing approach to gain insight into the evolution of Ebola virus (EBOV) in Guinea from the ongoing West African outbreak. This was an approach based on analysis pipelines developed
A novel Ebola virus (EBOV) first identified in March 2014 has infected more than 25,000 people in West Africa, resulting in more than 10,000 deaths. Preliminary analyses of genome sequences of 81 EBOV collected from March to June 2014 from Guinea and Sierra Leone suggest that the 2014 EBOV originated from an independent transmission event from its natural reservoir followed by sustained human-to-human infections. It has been reported that the EBOV genome variation might have an effect on the efficacy of sequence-based virus detection and candidate therapeutics. However, only limited viral information has been available since July 2014, when the outbreak entered a rapid growth phase. Here we describe 175 full-length EBOV genome sequences from five severely stricken districts in Sierra Leone from 28 September to 11 November 2014. We found that the 2014 EBOV has become more phylogenetically and genetically diverse from July to November 2014, characterized by the emergence of multiple novel lineages. The substitution rate for the 2014 EBOV was estimated to be 1.23 × 10(-3) substitutions per site per year (95% highest posterior density interval, 1.04 × 10(-3) to 1.41 × 10(-3) substitutions per site per year), approximating to that observed between previous EBOV outbreaks. The sharp increase in genetic diversity of the 2014 EBOV warrants extensive EBOV surveillance in Sierra Leone, Guinea and Liberia to better understand the viral evolution and transmission dynamics of the ongoing outbreak. These data will facilitate the international efforts to develop vaccines and therapeutics.
To support Liberia’s response to the ongoing Ebola virus (EBOV) disease epidemic in Western Africa, we established in-country advanced genomic capabilities to monitor EBOV evolution. Twenty-five EBOV genomes were sequenced at the Liberian Institute for Biomedical Research, which provided an in-depth view of EBOV diversity in Liberia during September 2014–February 2015. These sequences were consistent with a single virus introduction to Liberia; however, shared ancestry with isolates from Mali indicated at least 1 additional instance of movement into or out of Liberia. The pace of change is generally consistent with previous estimates of mutation rate. We observed 23 nonsynonymous mutations and 1 nonsense mutation. Six of these changes are within known binding sites for sequence-based EBOV medical countermeasures; however, the diagnostic and therapeutic impact of EBOV evolution within Liberia appears to be low.
Unlabelled:
Deep sequencing of RNAs produced by Zaire ebolavirus (EBOV) or the Angola strain of Marburgvirus (MARV-Ang) identified novel viral and cellular mechanisms that diversify the coding and noncoding sequences of viral mRNAs and genomic RNAs. We identified previously undescribed sites within the EBOV and MARV-Ang mRNAs where apparent cotranscriptional editing has resulted in the addition of non-template-encoded residues within the EBOV glycoprotein (GP) mRNA, the MARV-Ang nucleoprotein (NP) mRNA, and the MARV-Ang polymerase (L) mRNA, such that novel viral translation products could be produced. Further, we found that the well-characterized EBOV GP mRNA editing site is modified at a high frequency during viral genome RNA replication. Additionally, editing hot spots representing sites of apparent adenosine deaminase activity were found in the MARV-Ang NP 3'-untranslated region. These studies identify novel filovirus-host interactions and reveal production of a greater diversity of filoviral gene products than was previously appreciated.
Importance:
This study identifies novel mechanisms that alter the protein coding capacities of Ebola and Marburg virus mRNAs. Therefore, filovirus gene expression is more complex and diverse than previously recognized. These observations suggest new directions in understanding the regulation of filovirus gene expression.
In its largest outbreak, Ebola virus disease is spreading through Guinea, Liberia, Sierra Leone, and Nigeria. We sequenced
99 Ebola virus genomes from 78 patients in Sierra Leone to ~2000× coverage. We observed a rapid accumulation of interhost
and intrahost genetic variation, allowing us to characterize patterns of viral transmission over the initial weeks of the
epidemic. This West African variant likely diverged from central African lineages around 2004, crossed from Guinea to Sierra
Leone in May 2014, and has exhibited sustained human-to-human transmission subsequently, with no evidence of additional zoonotic
sources. Because many of the mutations alter protein sequences and other biologically meaningful targets, they should be monitored
for impact on diagnostics, vaccines, and therapies critical to outbreak response.
In March 2014, the World Health Organization was notified of an outbreak of a communicable disease characterized by fever, severe diarrhea, vomiting, and a high fatality rate in Guinea. Virologic investigation identified Zaire ebolavirus (EBOV) as the causative agent. Full-length genome sequencing and phylogenetic analysis showed that EBOV from Guinea forms a separate clade in relationship to the known EBOV strains from the Democratic Republic of Congo and Gabon. Epidemiologic investigation linked the laboratory-confirmed cases with the presumed first fatality of the outbreak in December 2013. This study demonstrates the emergence of a new EBOV strain in Guinea.
A-to-I RNA editing, the deamination of adenosine (A) to inosine (I) that occurs in regions of RNA with double-stranded character, is catalyzed by a family of Adenosine Deaminases Acting on RNA (ADARs). In mammals there are three ADAR genes. Two encode proteins that possess demonstrated deaminase activity: ADAR1, which is interferon-inducible, and ADAR2 which is constitutively expressed. ADAR3, by contrast, has not yet been shown to be an active enzyme. The specificity of the ADAR1 and ADAR2 deaminases ranges from highly site-selective to non-selective, dependent on the duplex structure of the substrate RNA. A-to-I editing is a form of nucleotide substitution editing, because I is decoded as guanosine (G) instead of A by ribosomes during translation and by polymerases during RNA-dependent RNA replication. Additionally, A-to-I editing can alter RNA structure stability as I:U mismatches are less stable than A:U base pairs. Both viral and cellular RNAs are edited by ADARs. A-to-I editing is of broad physiologic significance. Among the outcomes of A-to-I editing are biochemical changes that affect how viruses interact with their hosts, changes that can lead to either enhanced or reduced virus growth and persistence depending upon the specific virus.
We assessed the alterations of viral gene expression occurring during persistent infections by cloning full-length transcripts of measles virus (MV) genes from brain autopsies of two subacute sclerosing panencephalitis patients and one measles inclusion body encephalitis (MIBE) patient. the sequence of these MV genes revealed that, most likely, almost 2% of the nucleotides were mutated during persistence, and 35% of these differences resulted in amino acid changes. One of these nucleotide substitutions and one deletion resulted in alteration of the reading frames of two fusion genes, as confirmed by in vitro translation of synthetic mRNAs. One cluster of mutations was exceptional; in the matrix gene of the MIBE case, 50% of the U residues were changed to C, which might result from a highly biased copying event exclusively affecting this gene. We propose that the cluster of mutations in the MIBE case, and other combinations of mutations in other cases, favored propagation of MV infections in brain cells by conferring a selective advantage to the mutated genomes.
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