Literature DB >> 27357207

Development of a subgenomic clone system for Kyasanur Forest disease virus.

Bradley W M Cook1, Aidan M Nikiforuk1, Todd A Cutts2, Darwyn Kobasa3, Deborah A Court4, Steven S Theriault5.   

Abstract

Emerging tropical viruses pose an increasing threat to public health because social, economic and environmental factors such as global trade and deforestation allow for their migration into previously unexposed populations and ecological niches. Among such viruses, Kyasanur Forest disease virus (KFDV) deserves particular recognition because it causes hemorrhagic fever. This work describes the completion of an antiviral testing platform (subgenomic system) for KFDV that could be used to quickly and safely screen compounds capable of inhibiting KFDV replication without the requirement for high containment, as the structural genes have been replaced with a luciferase reporter gene precluding the generation of infectious particles. The coordination of KFDV kinetics with the replication characteristics of the subgenomic system has provided additional insight into the timing of flavivirus replication events, as the genetically engineered KFDV genome began replication as early as 2h post cellular entry. Possession of such antiviral testing platforms by public health agencies should accelerate the testing of antiviral drugs against emerging or recently emerged viruses mitigating the effects of their disease and transmission.
Copyright © 2016. Published by Elsevier GmbH.

Entities:  

Keywords:  Antiviral research; Flavivirus; Kyasanur Forest disease virus; Molecular genetics; Subgenomic clone system; Tick-borne flavivirus

Mesh:

Substances:

Year:  2016        PMID: 27357207     DOI: 10.1016/j.ttbdis.2016.06.002

Source DB:  PubMed          Journal:  Ticks Tick Borne Dis        ISSN: 1877-959X            Impact factor:   3.744


  2 in total

Review 1.  Tick-Borne Viruses.

Authors:  Junming Shi; Zhihong Hu; Fei Deng; Shu Shen
Journal:  Virol Sin       Date:  2018-03-13       Impact factor: 4.327

2.  Kyasanur Forest Disease Classification Framework Using Novel Extremal Optimization Tuned Neural Network in Fog Computing Environment.

Authors:  Abhishek Majumdar; Tapas Debnath; Sandeep K Sood; Krishna Lal Baishnab
Journal:  J Med Syst       Date:  2018-09-01       Impact factor: 4.460

  2 in total

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