Biosafety, biosecurity, logistical, political, and technical considerations can delay or prevent the wide dissemination of source material containing viable virus from the geographic origin of an outbreak to laboratories involved in developing medical countermeasures (MCMs). However, once virus genome sequence information is available from clinical samples, reverse-genetics systems can be used to generate virus stocks de novo to initiate MCM development. In this study, we developed a reverse-genetics system for natural isolates of Ebola virus (EBOV) variants Makona, Tumba, and Ituri, which have been challenging to obtain. These systems were generated starting solely with in silico genome sequence information and have been used successfully to produce recombinant stocks of each of the viruses for use in MCM testing. The antiviral activity of MCMs targeting viral entry varied depending on the recombinant virus isolate used. Collectively, selecting and synthetically engineering emerging EBOV variants and demonstrating their efficacy against available MCMs will be crucial for answering pressing public health and biosecurity concerns during Ebola disease (EBOD) outbreaks.
Predicting gene regulatory regions with a convolutional neural network for processing double-strand genome sequence information