Virus Genetics and Evolution in Ebola

Ebola is a virus that has been present for years, but scientists have recently been able to learn more about its genetic makeup and evolutionary tendencies. Ebola is a deadly virus that can cause severe symptoms and even death in people. Using genomic sequencing, researchers have detected the particular genetic traits of this virus and the various mutations it has undergone. This has given us insight into its ability to spread, the various forms of disease it causes, and how it may evolve in the future. Knowing Ebola’s genetic and evolutionary origins can aid in developing more effective treatments and vaccines.

Ebola is highly contagious and spreads swiftly when contaminated body fluids come into touch. The virus was discovered in Congo in the year 1976, and it has subsequently caused outbreaks across many African countries. The virus fits the Filoviridae family and comprises five species (Holmes et al. 2016). Each species comprises multiple genetic lineages that can be identified based on their genetic makeup. The virus’s genetic makeup can vary as it spreads from one individual to another and from animal to human.

The effect of the virus on human and animal health is a crucial piece of information that needs to be added to the topic of virus genetics and evolution in Ebola. Understanding the virus’s genetic and evolutionary dynamics will help researchers understand how it evolves and affects human populations. This knowledge is essential to creating strategies for virus prevention, detection, and treatment and understanding the virus’s long-term effects on human health.

Both articles focused on the 2013-2016 Ebola outbreak. The first article,” Rapid Outbreak Sequencing of Ebola Virus in Sierra Leone,” attempted to solve the question below. How did the Sierra Leone Ebola epidemic evolve? In Sierra Leone, how can Ebola transmission networks be identified? Could occasional Ebola cases be connected to transmission chains? The researchers presented how the Ebola virus evolved during the 2013-2016 pandemic in the second article, “The Evolution of Ebola Virus: Insights from the 2013-2016 Epidemic”. To solve this question, the researchers used a molecular epidemiological analysis of the Ebola virus samples from Sierra Leone city, Guinea, and Liberia (Tong et al., 2015). The research examined the virus’s hereditary alterations and geographical distribution during the pandemic.

The researchers used a range of study methods to answer these questions. The researchers used next-generation sequencing (NGS) to generate the Ebola viral genotypes in both articles. NGS is a strong method for rapidly sequencing vast volumes of genetic material. This allowed the researchers to generate many sequences fast, essential for the rapid epidemic sequencing described in the first article. The researchers gathered samples from 78 patients with confirmed or probable Ebola infection and analyzed them using the NGS method (Torrens & Castellano,2016). The researchers employed NGS and bioinformatics tools to evaluate the information provided by the sequencing. These methods enabled them to identify transmission chains, compare different Ebola virus sequences, and assess its evolution.

The first article aimed to employ NGS to detect Ebola virus transmission networks in Sierra Leone during the 2013-2016 outbreak. The researchers collected blood samples from Sierra Leone patients, sequenced them using NGS, and then analyzed them using bioinformatics tools. This allowed them to identify the Ebola virus transmission networks in the region, which could assist in improving public health initiatives for better infection management. The second article aimed to employ NGS and bioinformatics methods to study the evolution of the Ebola virus during the 2013-2016 pandemic (Lawrence et al., 2019). To accomplish this, the researchers collected samples from patients in several nations and analyzed them using NGS. They then analyzed the data and used bioinformatics to compare different Ebola virus frequencies. This enabled them to pinpoint the evolutionary changes during the pandemic, which could aid in preventing future outbreaks.

The first research discovered that the NGS technique could identify Ebola virus transmission chains in Sierra Leone. The investigation demonstrated that the virus spread from isolated cases to larger clusters and that certain clusters were linked. Furthermore, the investigation revealed that the virus’s spread was not limited to a specific location but throughout Sierra Leone. The second research found that the Ebola virus had been mutating since the 2013-2016 pandemic. The investigation revealed that the virus had undergone genomic diversification, with numerous unique lineages emerging and circulating simultaneously. The investigation found that the virus had been able to adjust to its new habitat, making it easier for it to spread.

The article “The Evolution of Ebola Virus: Insights from the 2013-2016 Epidemic” discovered that Ebola virus disease (EVD) was initially identified in 1976 in Zaire (now the Democratic Republic of the Congo) when it caused an outbreak of 318 cases with an 88% fatality rate. In Central Africa, 12 minor epidemics were documented between 1977 and 2014, with cases ranging from 32 to 315 and death rates ranging from 47% to 89%. The EVD pandemic in West Africa from 2013 to 2016 was the first to have case exportations and nosocomial transmissions recorded outside of Africa. While the 2013-2016 EVD pandemic was enormous in scope, its features and transmission profiles appear to be similar to earlier EVD outbreaks, with the death rate estimated to be about 70% and the basic reproduction rate (R0) estimated to be around 50%.

Table 1

Around thirty per cent (30%) of Sierra Leone’s population lives in urban and rural areas in the west. Yet, these regions accounted for 41% of all recorded Ebola cases. The remaining cases were dispersed among Sierra Leone’s three provinces, 12 districts, and 149 chiefdoms. While 26% of chiefdoms had no recorded cases, the remaining 74% were distributed unevenly, with 14 chiefdoms accounting for 60% of all cases.

Both articles reach conclusions concerning the evolution of the Ebola virus between 2013 and 2016. Researchers concluded that the virus in West Africa evolved in terms of transmission, mortality, and pathogenicity during the epidemic, with outbreaks in urban areas being more severe and death being higher in some places (Arias et al. 2016). They also claimed that rapid outbreak analysis could detect transmission chains connected to sporadic cases, allowing outbreaks to be identified and contained more swiftly. These findings imply that knowing the development of the Ebola virus is critical to controlling its spread and lowering mortality.

Finally, understanding the emergence of Ebola requires understanding virus genetics and evolution. Scientists can develop more precise predictions about how the virus will evolve and spread by researching its genetic variations. This knowledge can be applied to developing more effective medicines and vaccinations. The study of virus genetics and evolution can shed light on how the virus spreads and how it can be avoided. Scientists can better plan for future epidemics and protect society from the threat of Ebola by researching virus genetics and evolution.

REFERENCE

Arias, A., Watson, S. J., Asogun, D., Tobin, E. A., Lu, J., Phan, M. V., … & Cotten, M. (2016). Rapid outbreak sequencing of the Ebola virus in Sierra Leone identifies transmission chains linked to sporadic cases: virus evolution, 2(1).

Holmes, E. C., Dudas, G., Rambaut, A., & Andersen, K. G. (2016). The evolution of Ebola virus: Insights from the 2013–2016 epidemic. Nature, 538(7624), 193-200.

Lawrence, P., Danet, N., Reynard, O., Volchkova, V., & Volchkov, V. (2017). Human transmission of Ebola virus. Current opinion in virology, 22, 51-58.

Tong, Y. G., Shi, W. F., Liu, D., Qian, J., Liang, L., Bo, X. C., … & Cao, W. C. (2015). Genetic diversity and evolutionary dynamics of Ebola virus in Sierra Leone. Nature, 524(7563), 93-96.

Torrens, F., & Castellano, G. (2016). Ebola virus disease: Questions, ideas, hypotheses, and models. Pharmaceuticals, 9, 14-6.