Three species viral zoonotic infections - a systems virology analysis

Recent high profile events highlight the transmission of bat viruses to humans, usually involving an intermediate farmed/companion animal host. These include Hendra (bats - horses - humans), Nipah (bats - pigs - humans), SARS-CoV (bats - palm civet - humans) and MERS-CoV (bats - camels - humans). Thus, there is an established paradigm of new viruses passing from wild animals to farmed/companion animals and/or humans. There is every possibility that this kind of jump from bats to humans via another animal - which is known as a zoonosis - could keep happening in the future. Bats make up almost 20% of all living mammals and they are found almost everywhere on the planet, which means that new viruses spreading from bats to animals and humans could happen anywhere. Bats are widespread and carry a range of viruses similar to MERS-CoV/SARS-CoV and in the UK, bats come into contact with a range of wild and farmed animals. Thus, a new outbreak is as likely to happen here as anywhere else. In addition to the threat to human health, this kind of three-stage zoonosis poses two potential food security issues; one is that the novel virus impacts animal health directly (e.g. effects ranging from a failure to gain weight to mortality). The second is an indirect impact on food security resulting from the threat to human health, e.g. Nipah virus outbreaks have resulted in the wholesale slaughter of farmed pigs.
A key barrier to understanding how serious a disease might become, or which animals might be affected in zoonotic events, is that we have little information on how the emerging virus interacts with the regulation of transcriptional and translational systems in different animals. This means we do not understand how the virus might interact with a new host species, which will influence whether the virus successfully replicates and whether the infection will cause disease or fatalities.
In human virus research, techniques such as high-throughput proteomics/transcriptomics/interactomics have been successfully used to reveal how viruses modulate and interact with thousands of human genes and proteins. This new "systems virology" approach even suggests ways of combating or managing the disease. Studying a zoonotic virus with a potential to impact food security, in the same level of detail, could help us understand the pronounced differences in pathogenicity of these viruses in different animal and vector species. Crucially, this will reveal how viruses adapt and jump into other animals, or if certain species jumps are more likely than others. In turn, this will help inform policy by allowing predictions of which animals may readily act as new hosts, or are likely to suffer severe pathogenic responses, and thus can be controlled accordingly.
The ability to do this type of research in non-human species (i.e. the animal reservoirs and intermediate hosts of zoonotic infections) has a number of serious bottlenecks. This is because the "systems virology" approach requires high-throughput methods of detecting and identifying gene transcripts and proteins, which is still a major challenge in non-human species. Even if there is a genome sequence available, it will not have been annotated with regard to i) the identification of orthologous genes, ii) the full complement of gene transcripts, for example, differentially spliced transcripts, and iii) the proteins encoded by these transcripts. We have developed a world-leading technique (called PIT analysis) that allows us to use high-throughput techniques to study virus-host interactions in any animal with the same precision as we can currently apply to human diseases. In this project we will examine how a zoonotic virus interacts with three different animals (including humans), identifying the different cellular pathways that are affected and help us understand how viruses jump from one animal to another and suggesting ways of combating them in the future.

Over the last few decades we have seen repeated zoonotic events of varying severity but with common hallmarks which is that the original host does not appear to suffer significant pathogenicity whilst spill over hosts do. Application of deep sequencing and high throughput quantitative proteomics have provided significant insights into virus-host interactions but the application of this to animals other than humans and mice is severely curtailed by the quality of bioinformatic annotation in other species. At Bristol we have pioneered a novel combined transcriptomic and proteomic technique that allows us to study the interactions of any virus with any eukaryotic species on a very high throughput scale typically following changes in around 8000 transcripts and 5000 proteins simultaneously even if the genome of the target host organism is not known. Moreover, we can use this analysis to build an interactome between any virus protein and the host proteins it interacts with in any eukaryotic species. As a model system we will study MERS-CoV which has recently emerged from bats, spread to camels and from there to humans and so it represents a classical three species zoonotic event. We wil examine how MERS-CoV affects gene and protein expression in human, camel and bat cells and to study the interaction of key MERS-CoV proteins in these species. We anticipate this analysis will shine a powerful spotlight on how one virus interacts with genes and proteins of three species, what similarities and differences are there between the cellular response of these species and do these correlate with pathogenicity, also does a deeper understanding of the virus-host cell interaction in three species help us understand how one virus can spread to different species.

This proposal is aimed at understanding the interplay between a zoonotic virus and three mammalian species - bats, camels and humans. It is expected that at the conclusion of the 3 year study a number of key protein-protein interactions and key pathways will have been identified.
Critically, the refinement of our analysis pipeline will enable us to rapidly examine newly emerging infectious diseases in any host, irrespective of the quality of the bioinformatics datasets available for any given species. The solutions derived from this project can be applied to any viral pathogen that crosses multiple species, including ones that involve insect vectors or avian hosts. Therefore the project is ideally placed within the BBSRCs strategic aims of developing the areas of both "big data" and "one health".
The pathways we identify could be further investigated as targets for anti-viral strategies by the scientific community. Outside of academic beneficiaries, the major immediate beneficiaries of the results produced in the investigation will be those in the commercial private sector. There is a clear unmet need to develop antiviral strategies against viruses and this project will be a significant boost to this area. In particular, by analysing the same virus in three hosts with different pathogenic outcomes our comparative analysis should help to identify those cellular pathways that need in depth investigation as they may be critical to host survival or to host morbidity/mortality. This is a unique approach to understanding those cellular responses to a viral infection that are helpful and those that are harmful.
Allied to this is the concept of determining, side by side, how different species respond to the same virus infection. We believe, very strongly, that this will have long term impact on the selection and development of new animal models in non-traditional species that are more appropriate models of human conditions.
Finally, this project will represent a major investment in the newly emerging field of "systems virology" which offers the prospect of a deeper understanding of virus-host cell interactions, new avenues for antiviral research and the identification of common pathways in viral pathogenesis, which may lead to broader spectrum antiviral treatments or the identification of drugs already in use that may be applied to the treatment of zoonotic viruses that may emerge in the future.
The project involves the use of cutting edge transcriptomics, proteomics and broad bioinformatics analysis skills. Thus, as the project progresses, the PDRA and technician will acquire advanced training in this field. As academics at the UoB, the PI and Co-Is are increasingly transferring these skills to undergraduate and postgraduate students, both in the form of lectures, practicals and research projects. They are currently developing a 20 lecture unit in a new MSc programme that focuses on high-throughput technologies and the associated bioinformatic analysis. Overall this fits well with the BBSRC strategy to increase training and capacity in bioinformatics in the UK.
This project will generate large amounts of raw data, processed data and will further promote the use of bioinformatics analysis that will be of significant value to the research community. We are committed to abiding by the BBSRC's data sharing policy, and will ensure that all data from the project is freely available for at least ten years from the date of publication. This includes our project partners who are also committed to sharing the data generated.