The current Ebola 2014 virus is mutating at a similar rate to seasonal flu (Influenza A). This means the current Ebola outbreak has a very high intrinsic rate of viral mutation. The bottom line is that the Ebola virus is changing rapidly, and in the intermediate to long term (3 months to 24 months), Ebola has the potential to evolve.
We cannot predict exactly what the Ebola virus will look like in 24 months. There is an inherent stochastic randomness to viral evolution which makes predictions on future viral strains difficult, if not impossible. One basic tenet we can rely on is this: Viruses tend to maximize their infectivity (basic reproduction number) within their biological constraints (Nowak, 2006).
These evolutionary constraints can be extremely complex, and can include trade-offs between virulence and infectivity, conditions of superinfection, host population dynamics, and even outbreak control measures.
One of the few statements we can make with confidence that the Ebola genome is changing at a specific rate, which is explained below.
Ebola Mutation Rate:
Analysis of the available research suggests that the Ebola 2014 virus is currently mutating at a rate 200% to 300% higher than historically observed (Gire, 2014).
Furthermore, the Ebola-2014 virus’s mutation rate of 2.0 x 10−³ subs/site/year is nearly identical to Influenza A’s mutation rate of 1.8 x 10−³ subs/site/year (Jenkins, 2002). This means Ebola 2014 is mutating as fast as seasonal flu.
Disclaimer: This paper contains no evidence (for or against) alternate modes of transmission for Ebola, nor is this paper postulating that genetic changes have impacted EVD clinical presentation (although evidence for this has started to emerge). This paper is simply demonstrating what appears to be a rapid rate of evolution in the Ebola 2014 Virus. Many recent Ebola viral mutations have been synonymous mutations, some have been in intergenic regions, while others are non-synonymous substitutions in protein-coding regions. All have unknown impact at the present time. Such questions should be the subject of future scientific research. This article simply points out that Ebola in 2014 is undergoing rapid mutation and adaptation. The future implications of Ebola’s rapid evolution are unclear.
We chose to compare Ebola-2014 to Influenza A (Seasonal Flu) because Influenza is one of the fastest-mutating viruses (Jenkins, 2002). Unlike chickenpox (VZV), which people usually only contract once per lifetime, Influenza can infect a single individual many times repeatedly over the years. One of the reasons Influenza is able to re-infect humans each year is because the Influenza’s high mutation rate allows the virus to generate ‘escape mutants’. Escape mutants are Influenza viruses which are no longer recognized by human immune systems. Each winter presents us with a new mutated strain of the Influenza virus. Rapid mutation is beneficial to Influenza genetic fitness (in regards to antigenic regions), because it allows a ‘new’ Influenza virus to circulate year after year.
The benefit of a high mutation rate in Ebola 2014 is different — the genetic changes in Ebola-2014 allow for rapid exploration of the entire fitness landscape in a brand new host — humans. We need to be aware that the Ebola-2014 virus is undergoing rapid adaptation.
Ebola in Zoonotic Reservoir: Viral Genome adapted to Fruit Bats. (Green)
Ebola in Human Hosts: Viral Genome adapted to Humans. (Red)
Ebola Genotype will move Green -> Red during serial passage through Humans.
Until the Ebola outbreak is brought under control, the Ebola-2014 virus will continue to seed and adapt in its growing pool of West African human hosts. We need to consider that as the weeks and months go on, the rapidly-changing Ebola-2014 virus will undergo repeated export from the West African region to countries around the world.
As new Ebola cases grow in West Africa and elsewhere, we are effectively conducting ‘serial passage’ experiments of Ebola-2014 through human hosts. The repeated passage of Ebola-2014 through humans is exerting selection pressure on the Ebola-2014 virus to adapt to our species (instead of fruit bats). The introduction of Ebola-2014 into a large pool of West African human hosts (coupled with the complex dynamics of evolutionary selection pressure) may allow the Ebola-2014 virus to become more transmissible as the months go on, particularly in the absence of effective control interventions.
The high mutation rate we see in Ebola-2014 reflects its ability to rapidly explore the fitness landscape. The ability of Ebola to undergo rapid genome substitutions and SNPs, coupled with genetic recombination, will allow ‘survival of the fittest’ in Ebola-2014 genetic variants (on both the intra-host and inter-host levels). New Ebola sub-clades are created with each passing month (there are already four sub-clades as of August 2014). New Ebola genetic variants are created with each new infection, though most are selected against. Rapid adaptation emerges from the high intrinsic Ebola-2014 mutation rate, coupled with the virus’s ability to undergo RNA recombination during superinfection.
Molecular dating of the Ebola-2014 outbreak (Gire, 2014).
Probability distributions for both 2014 divergence events are overlaid above.
This phylogenetic tree is based on 99 Ebola viral genomes deep-sequenced from 78 distinct patients in Sierra Leone (Gire, 2014). We can see in the figure above that there are at least four Ebola genetic clusters (or sub-clades) based on phylogenetic analysis: These Ebola clusters are called GN, SL1, SL2, and SL3 by Gire et al. The key takeaway is that even prior to July 2014, the current Ebola outbreak had already accumulated significant genetic diversity. Furthermore, the dominant circulating Ebola variants have changed over time. Up to four different Ebola-2014 viral sub-clades (groups of genetically related Ebola isolates) have circulated between humans since the onset of the 2014 Ebola outbreak.
As the number of people affected by the 2014 Ebola outbreak has grown, so has the number of Ebola unique viral mutations and unique viral genetic lineages. We can expect Ebola 2014 viral lineages to grow as some function f(i) proportional to the number of people infected with Ebola.
Ebola-2014: Acquisition of genetic variation over time (Gire, 2014).
Fifty mutational events (short dashes) and 29 new viral
lineages (long dashes) were observed.
The diagram above suggests that as the Ebola-infected host pool grows, so does the number of unique Ebola viral lineages (Gire, 2014). This implies that Ebola acquires genetic diversity as it infects more people, particularly if the virus undergoes recombination during superinfection (Niman, 2007). The growing number of new Ebola viral lineages will undergo natural selection for some ‘optimum’ balance of virulence, infectivity, tissue tropism, immune suppression, and other parameters which maximize the reproductive fitness of the Ebola virus in humans. What that final virus might eventually look like 2 years from now is anyone’s guess. But the explosion of genetic variation suggests that the Ebola virus will become more difficult to contain as time goes on, which is why early action is important.
The idea that the Ebola-2014 Virus jumped species, but is now somehow ‘static’ or ‘frozen in time’ is a mistake. The Ebola-2014 virus is undergoing a period of rapid adaptation in human hosts, as evidenced by the Ebola RNA sequences deposited in Genbank, and the studies referenced with this article. Hopefully, interventions (like contact tracing) will be able to stop Ebola-2014 before the virus optimizes its genotype.
RNA Virus Mutation RatesRNA Virus Mutation Rates – image not available
These are two scenarios to outline what may happen in the future. The critical variable determining the global outcome of Ebola is the response in West Africa, not the response in the United States.
Best Case Scenario:
WHO immediately deploys contact-tracing teams on the ground in West Africa. The US Military is deployed as well, and constructs hospitals sufficient to care for the sick. The hospitals are staffed by qualified (read: well trained) caregivers. Teams on the ground track down and care for Ebola-infected patients across West Africa, distributing self-treatment kits, food, medicine, and expertise. An effort is made to involve local authorities and community leaders. These efforts cause measurable reductions in the basic reproduction number of the virus by the end of 2014.
Within 3 months to 9 months, the outbreak in West Africa peaks, levels-off, and begins to fade. The Ebola virus never has the opportunity to acquire any significant mutations, due to its limited host pool. Ebola is fully under control by early 2015. Sporadic cases in other countries are dealt with by treatment and contact tracing. By Q4 2015, multiple Ebola vaccines and drugs are in the pipeline limiting the overall threat Ebola poses.
Worst Case Scenario:
The international response is perpetually behind the curve. Every response action is 8 to 12 weeks too late. Statistics from the WHO become volatile and are unreliable as the lack of deployed personnel make hard numbers impossible to pin down. By 2015 the number of infections is in the hundreds of thousands in West Africa. The West African region exports ‘asymptomatic infectives’ which go undetected by basic screening. These individuals ‘seed’ outbreaks in other countries.
As more people become infected, a significant mutation arises that allows for a longer asymptomatic but infectious period, increasing the R-0. Globally, cases continue to double every 16 days, contact tracing infrastructure outside the West becomes saturated, and hospitals are overrun. By early-to-mid 2015, the global pool of Ebola-infected patients are in the millions, mainly centered in West Africa and Southeast Asia with multiple strains of varying virulence. A sudden change in the outbreak epidemiology caused by a recombinant Ebola strain causes confusion about how to respond. Efforts at developing treatments/vaccines become logistically complex and ineffective.
The implication of the Ebola 2014 mutation rate is this: A single Ebola mutation doesn’t necessarily mean the virus will become ‘airborne’, or that the virus has altered tissue tropism, or that the virus spreads more easily. But a high intrinsic rate of Ebola mutation means that such changes may become possible in the future. If the number of people infected grows into the hundreds of thousands, or even low millions, then the probability of a significant ‘constellation’ of accumulated Ebola mutations with phenotypic impact becomes more likely. The problem is that accumulated Ebola mutations will scale with the size of the population infected. Conversely, in a small population, such Ebola mutations are not likely to have a significant impact. It’s a bit like the virus is buying lottery tickets… The more lottery tickets the Ebola virus ‘buys’, the more chances it has to ‘win’.
The general consensus in the scientific and epidemiological community is immediate intervention in West Africa is necessary in order to avoid taking the risky outcomes possible in a ‘worst case’ scenario. A suitable response would need to include airlifting self-treatment kits with thermometers, the distribution of life-saving drugs, the construction of Ebola treatment centers, hospital staffing, contact tracing teams, and so forth. A robust international response must happen soon in order to ensure that the current situation with the Ebola outbreak remains a ‘best case’ outcome.
 Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. (Gire et al, 2014).
 Rates of Molecular Evolution in RNA Viruses: A Quantitative Phylogenetic Analysis. (Jenkins et al, 2002).
 Isolates of Zaire ebolavirus from wild apes reveal genetic lineage and recombinants. (Wittman et al, 2007).
 Ebola Recombination: Recombinomics Commentary. (Niman, 2007).
 Evolutionary Dynamics: Exploring the Equations of Life. (Nowak, 2006).