We combined our 85 Guinean EBOV sequences (Extended Data Table 1) with 110 publicly available 2014 EBOV genome sequences sampled from Guinea, Mali and Sierra Leone, producing a total data set of 195 sequences. Phylogenetic analysis reveals greater genetic diversity than previously described, with the presence of three distinct lineages, in contrast to the relatively limited variation documented early in the Sierra Leone outbreak4 (Fig. 1). The first lineage (denoted GUI-1) represents a cluster of sequences only found in Guinea, although from all urban and rural regions sampled in this country, and that is most closely related to the earliest viruses sampled in March 2014 (ref. 2). This lineage co-circulated in the greater Conakry region with viruses of the remaining two lineages described below. Notably, GUI-1 is characterized by multiple non-synonymous mutations in the nucleoprotein (NP), VP35 and GP such that it may also be phenotypically distinct, although this will require future experimental verification (Fig. 2a).

Figure 1: Maximum clade credibility (MCC) phylogenetic tree of the 195 EBOV isolates from West Africa. Tip times are scaled to the date of sampling (with a timescale shown on the x axis), and colour-coded according to the geographic location of sampling (at the district level for Guinea, and country level for Sierra Leone and Mali). Full size image Download PowerPoint slide

Figure 2: Patterns of mutation accumulation during the 2014 epidemic. a, Mutations found in at least two separate sequences, showing one patient per row. Grey blocks indicate identity with the Kissidougou Guinean sequence (GenBank accession KJ660346). The top row shows the type of mutation (dark grey, intergenic; green, synonymous; red, non-synonymous), with the genomic location indicated above. Cluster assignment is shown at the left. b, The geographic distribution of EBOV variants, coloured by clusters. c, Number of Ebola virus disease patients sequenced per ten days, coloured by cluster. Full size image Download PowerPoint slide

These data also reveal that EBOV sequences from the two documented introductions into Mali (October and November 2014) belong to another larger cluster of Guinean viruses, denoted here as GUI-2. This phylogenetically distinct lineage is most closely related to the second cluster of Sierra Leone sequences (SLE-2), and could represent either a reintroduction from Sierra Leone or the continued diffusion in Guinea of strains related to those initially introduced to Sierra Leone. Finally, a third cluster of viruses (SLE-GUI-3) is found in Conakry, Forécariah, Dalaba and to a limited extent in Coyah (Fig. 2b), with multiple sequences falling within the third cluster4 of Sierra Leonean sequences. Such a phylogenetic structure suggests that there have been multiple migrations of EBOV into Guinea from Sierra Leone (although viral traffic from Guinea to Sierra Leone may also have occurred on occasion). An example of such cross-border virus traffic is a documented case that initiated a transmission chain in June 2014 in Conakry5, as well as transmission chains in Dalaba (260 km from Conakry), each of which is directly linked to different travellers from Sierra Leone. Although the numbers are small, the decreasing proportion of these sequences (matching the third cluster of Sierra Leone sequences) along the road from the Sierra Leonean border towards Conakry via Forécariah, and deeper inland in Coyah, might reflect the major transmission route of these viruses (Fig. 2b).

The area constituted by the urban setting of Conakry and the neighbouring prefectures harbours extensive EBOV genetic diversity, characterized by multiple co-circulating viral lineages. For example, all three lineages defined above (GUI-1 to SLE-GUI-3) co-circulated in Conakry during September and October 2014 (Figs 1 and 2c). Although early concerns associated with the presence of Ebola virus disease in high population density settings such as Conakry did not result in increased viral transmission, the capital city of Guinea nevertheless represents an important regional travel hub and highlights the challenge of controlling Ebola virus disease in and near large urban centres. In addition, although it is clear that a number of the EBOV strains circulating in Guinea are also present in neighbouring Sierra Leone (lineage SLE-GUI-3), reflecting the continued mobility of individuals between these localities during the peak of the epidemic and in the face of outbreak control measures, Guinea is also characterized by a number of independently evolving viral lineages, such that the epidemics in these countries have generated localized genetic diversity. Despite case reports reaching very low values in Conakry at several points during the summer of 2014, the recurrent transmission of the three distinct lineages in this locality is another indication of the challenges of controlling Ebola virus disease in large urban centres with highly mobile populations.

A total of 207 single nucleotide polymorphisms (SNPs) (51 non-synonymous, including 24 novel, 88 synonymous and 68 intergenic), have been fixed in individual patients within the sample of viruses analysed here. In contrast to the situation early in Sierra Leone, the viruses sampled from Guinea harbour numerous non-synonymous mutations which define lineages (Fig. 2a). Notably in GP, in which mutations could affect the efficacy of vaccines or antibody treatments, a C7025T (Pro→Ser) substitution in part defines GUI-1, and belongs to the heavily glycosylated mucin-like domain. Although O-glycosylation does involve the attachment of N-acetylglucosamine (GlcNac) to a serine (and/or threonine) residue, the sialylation pattern of this disordered domain appears to vary with the cellular environment. Two mutations (A6357G (Asn→Asp), in GP1 domain II and G7476A (Gly→Asp) in GP1 carboxy terminus) co-occur in a later branch of this cluster, whereas C7256T (His→Tyr), again in the mucin-like domain, is observed in another branch. We also observed one change in a glycosylation site (A6726G (Thr→Ala)) in a sub-cluster of sequences in SLE-GUI-3. Surprisingly, a mutation in the highly conserved interferon inhibitory domain of VP35 (C4116T) introduces a phenylalanine, characteristic of Sudan EBOV, but never previously observed in EBOV-Zaire. Another mutation in VP35, G3151A (Arg→Lys), lies in the sequence targeted by AVI-7539, a phosphorodiamidate morpholino oligomer (PMO)-based therapeutic candidate6. Studies of the phenotypic consequences of such mutations on viral components directly interacting with the host immune response could provide key insights into their epidemic potential, and also inform the therapeutic options currently considered for deployment7,8.

There has been some debate over the rate at which EBOV has evolved during the West African outbreak of EBOV, and what this may mean for the adaptive capacity of the virus, including changes in virulence9. Our estimates of the rate of nucleotide substitution for the combined Guinea and Mali and Sierra Leone data set under both strict and relaxed molecular clocks and using a variety of demographic and substitution models fall within the range of those obtained previously for EBOV4,9,10,11, with mean rates of between 0.87 × 10−3 to 0.91 × 10−3 nucleotide substitutions per site per year (range of credible intervals of 0.68 × 10−3 to 1.1 × 10−3 substitutions per site per year) (Extended Data Fig. 2). Essentially identical rates were observed when studying the Guinean viruses in isolation. However, these rates are lower than those observed during the early spread of the virus in Sierra Leone4. It is therefore possible that the rate estimate provided by ref. 4 represents a random fluctuation due to limited genetic variation within sequences from Sierra Leone sampled over a relatively short time-period, and/or has been elevated by the presence of transient deleterious mutations that have yet to be removed by purifying selection, as suggested by those authors4. Indeed, evolutionary rates in RNA viruses are known to have a strongly time-dependent quality, such that they are expected to be higher in the short-term than the long-term12. In addition, it is possible that differences in rate estimates in part reflect minor differences in substitution model parameters, the duration of intra-host virus evolution, as well as local epidemiological variation. More generally, it is difficult to translate relatively small differences in estimates of substitution rate, such as those obtained for EBOV in West Africa, into predictions on the future evolution of such key phenotypic traits as virulence, as the latter are more dependent on the nature of the selection pressures acting on the virus as well as the complex relationship between virulence and transmissibility. The data presented here indicates EBOV is able to generate and fix nucleotide and amino acid variation within co-circulating viral lineages on the time-scale of individual outbreaks, including the presence of country-specific lineages, and which may ultimately produce variants with important fitness differences.

Continued genomic surveillance is a strong complement to sometimes difficult local epidemiological investigations. We believe that the deployment of additional next-generation sequencing facilities in the West African surveillance network, thereby avoiding the logistical and regulatory13 hurdles associated with long-distance sample transportation, will positively contribute to the control of the current epidemic and help limit future outbreaks.