Oluwagbemi, O.; Awe, O.

A comparative computational genomics of Ebola Virus Disease strains: in-silico insight for Ebola control

Article

Oluwagbemi, O. and Awe, O. 2018. A comparative computational genomics of Ebola Virus Disease strains: in-silico insight for Ebola control. Informatics in Medicine Unlocked . 12, pp. 106 - 119. https://doi.org/10.1016/j.imu.2018.07.004

ISSN
Type	Article
Title	A comparative computational genomics of Ebola Virus Disease strains: in-silico insight for Ebola control
Authors	Oluwagbemi, O. and Awe, O.
Abstract	Ebola Virus Disease (EVD), is a national epidemic in Countries affected. It is also a potential global public health pandemic. The menace of the disease outbreak among West and Central African nations, in recent years, has resulted in the death of many unsuspecting victims. The present study was conducted to present a systematic review of the literature, focusing on the control of Ebola Virus Disease (EVD), among human subjects. It also centered on a bioinformatics analysis of five different strains of Ebola virus. Research articles published between 2008 and 2018, on EVD control studies, were systematically reviewed. Four online databases were searched for the purpose of this review. These include: Science Direct, Google Scholar, SpringerLink and PubMed. Study outcomes were extracted. The outcomes were summarized and categorized. Five different strains of Ebola virus were obtained from the NCBI database, specifically the Entrez Genome database. Bioinformatics analysis was performed using Muscle software, RawXL, Treview, iTOL and Clustal X. Bioinformatics analysis was performed on five selected strains of Ebola virus (Reston, Bundingbugyo, Zaire, Sudan and Tai forest). Evaluation of the phylogenetic tree was performed by using MEGA X and PHYLIP software. 237,498 publications were identified, out of which 104 research articles, from different regions of the world, fulfilled our inclusion criteria. Insight was gained for the control of EVD from these studies. Of the studies reviewed, 23 articles focused on vaccines/vaccination-related Ebola control research, 12 studies on modeling and simulation-related Ebola control research, 41 on drugs and therapeutics-related Ebola control research, and 28 focused on other experimental studies (such as biological experiments, bioinformatics experiments, travel border control measures, educational campaign measures, hand and environmental sanitization, amongst others). Very few modeling and simulation studies have been conducted on the control of EVD in the last 10 years. Thus, there is the need for more modeling and simulation-related ebola control research. Comparative computational genomics of the five Ebola virus strains produced phylogenetic trees in different shapes. An evaluation of the phylogenetic tree was performed. Results showed that Taiforest Ebola virus and Bundibugyo Ebola virus are closely related. The results also revealed that Sudan and Reston Ebola virus are closely related. Zaire Ebola virus stood out from all the others. It may be possible to adopt similar Ebola control measures against Ebola virus strains that are closely related. Insight from these results, can facilitate the development and production of multi-protective, multi-treatment drugs, multi-protective vaccines and antivirals, against these ebola virus disease strains. The results of the evaluations of the phylogenetic tree can be assistive in providing insight into the origin, evolution, and possible structural and genetic mutations of the Ebola virus. It can also provide insight for inferring the structural and functional properties of each Ebola virus. The knowledge of such inference can be useful for EVD control. This can bring about a radical transformation in control efforts for disease.
Keywords	Comparative genomics; Ebola virus disease; In-silico; Insight; Ebola control
Sustainable Development Goals	3 Good health and well-being
Middlesex University Theme	Health & Wellbeing
Publisher	Elsevier
Journal	Informatics in Medicine Unlocked
Electronic	2352-9148
Publication dates
Online	23 Jul 2018
Print	27 Jul 2018
Publication process dates
Accepted	17 Jul 2018
Submitted	03 Jan 2018
Deposited	15 Apr 2024
Output status	Published
Publisher's version	1-s2.0-S2352914818300029-main.pdf License CC BY-NC-ND 4.0 File Access Level Open
Copyright Statement	Copyright © 2018 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/)
Digital Object Identifier (DOI)	https://doi.org/10.1016/j.imu.2018.07.004
Language	English

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