Developing models to guide selection of genetic sequences with anti-viral properties

This project is part of a larger project called “Arming food production animals with a novel anti-viral defence”. The primary objective of the larger project is to strengthen the immune system of livestock and aquaculture species against viral threats.

Head and shoulders of a woman wearing glasses. — Dr Emiliana Weiss,

Outbreaks of viral diseases in our livestock and aquaculture animals can be a huge economic burden on society as well as impact Australia’s freedom to trade.

Recently, scientists have developed a new understanding of an existing technology, which expands its use to include a diagnostic capability. The technology can be used to detect pathogenic microorganisms in genomes. It can also be used to find bacteria that defends the host animal against invasive viruses.

Using advanced machine learning and utilisation of extensive datasets I will develop a model that will optimise the use of this new technology to identify the parts of a genome that can effectively combat infectious pathogens.

I will also be modelling the evolution of influenza viruses to be able to predict natural mutations that occur.
These methodologies will be validated using diverse viral datasets and experimental results obtained from sub-projects A, Arming food production animals with a novel antiviral defence, and B, Studying genetic sequences for anti-viral biocontrol in food production animals.

Project lead: Dr Emiliana Weiss.