Epi-SEQ - Molecular epidemiology of epizootic diseases using next generation sequencing technology

Next-generation sequencing (NGS) techniques offer an unprecedented step-change increase in the amount of sequence data that can be generated from a sample. NGS technologies can determine complete viral genomes with a resolution allowing the quantification of RNA quasispecies variation within samples and can economize the sequencing of large numbers of samples or larger DNA virus genomes. Focusing on important epizootic viral diseases that threaten livestock industries in Europe, the aim of this project is to exploit NGS to generate improved tools that can be used in real-time during epidemics. This work will be undertaken by a multidisciplinary team of scientists from Belgium, Germany, Italy, Sweden, and the United Kingdom with expertise in molecular virology, bioinformatics, mathematical modeling, and evolutionary biology. RNA viruses evolve rapidly and quickly adapt to different environmental pressures escaping host immune defenses, altering their pathogenicity and host range, and evading diagnostic tests. Current methodologies limit the resolution at which we can study the evolutionary dynamics of the complex genomic mixtures (quasispecies) that are typical for these viruses. Archived sample collections representing epizootic outbreaks of pathogens such as foot-and-mouth disease virus (FMDV), avian influenza virus (AIV), Newcastle Disease Virus (NDV) and classical swine fever virus (CSFV) will be used to monitor the evolution during field outbreaks of disease. Spatiotemporal data collected in the field will be integrated with this genetic data to produce robust models that can be used to reconstruct transmission trees during viral epidemics. Furthermore, in vitro experiments will be performed using FMDV (ss+RNA genome) and AIV (ss segmented-RNA genome) under strong selection pressures. Modeling of the resulting NGS data will provide a framework to describe the wider scale evolutionary patterns that are measured during these field outbreaks. Linking genetic data to viral phenotype will be undertaken by studying DNA viruses with large genomes (ASFV and poxviruses). Although the viruses have relatively stable genomes, their large size poses challenges for sequencing using traditional Sanger approaches. Specific work packages will focus on the improvement and dissemination of technical protocols and on data analysis and dissemination of bioinformatics and modeling tools. Insights from this project will result in: a) Novel information on viral evolution and (sub)populations; b) comparative evolutionary data between viruses with different genome organisation (+ vs. - sense RNA, segmented RNA, c) Improved diagnostic assays, based on an improved recognition of suitable sequence motifs; d) Powerful tools for molecular epidemiology; e) Enhanced capacity to optimize the strain composition of vaccines, and match to emerging virus variants; f) More effective tools to control epidemic and endemic infectious diseases.

Next-generation sequencing (NGS) techniques offer an unprecedented step-change increase in the amount of sequence data that can be generated from a sample. NGS technologies can determine complete viral genomes with a resolution allowing the quantification of RNA quasispecies variation within samples and can economize the sequencing of large numbers of samples or larger DNA virus genomes. Focusing on important epizootic viral diseases that threaten livestock industries in Europe, the aim of this project is to exploit NGS to generate improved tools that can be used in real-time during epidemics. This work will be undertaken by a multidisciplinary team of scientists from Belgium, Germany, Italy, Sweden, and the United Kingdom with expertise in molecular virology, bioinformatics, mathematical modeling, and evolutionary biology. RNA viruses evolve rapidly and quickly adapt to different environmental pressures escaping host immune defenses, altering their pathogenicity and host range, and evading diagnostic tests. Current methodologies limit the resolution at which we can study the evolutionary dynamics of so-called 'quasispecies' that are typical for these viruses. Archived sample collections representing epizootic outbreaks of viral pathogens will be used to monitor the evolution during field outbreaks of disease. Spatiotemporal data collected in the field will be integrated with these genetic data to produce robust models that can be used to reconstruct transmission trees during viral epidemics. Specific work packages will focus on the improvement and dissemination of technical protocols and on data analysis and dissemination of bioinformatics and modeling tools. Insights from this project will result in: a) Novel information on viral evolution and (sub)populations, more powerful tools for molecular epidemiology, and more effective tools to control epidemic and endemic infectious diseases.

Epi-SEQ brings together a multidisciplinary team of scientists with expertise in molecular virology, bioinformatics, mathematical modeling, and evolutionary biology. The power of the consortium lies in the complementary expertise ranging over virology, next generation sequencing, bioinformatics, mathematical modeling and data analysis, and in the synergy that will be generated as a result of complementarity between methodological and analytic expertise and the unparalleled access to sample collections available in partner labs from past epidemics and experiments. Focusing on important epizootic viral diseases that threaten livestock industries in Europe, the project will generate improved tools that can be used in real-time during epidemics. Archived sample collections representing epizootic outbreaks of pathogens such as foot-and-mouth disease virus (FMDV), avian influenza virus (AIV), Newcastle Disease Virus (NDV) and classical swine fever virus (CSFV) will be used to monitor the evolution during field outbreaks of disease. Spatiotemporal data collected in the field will be integrated with these genetic data to produce robust models that can be used to reconstruct transmission trees during viral epidemics.

The University of Glasgow component of the project will focus specifically on FMDV. FMDV is highly contagious and disease outbreaks are difficult to control. The exact mode of transmission between farms remains poorly understood and during the UK outbreak in 2001 the viral origin for many infected premises was attributed simply to "local spread". Working in close partnership with IAH-Pirbright, and in collaboration with other members of this consortium we will address the important problem of how to use viral sequence data to infer the movement of virus between farms. Full-length viral genomes from all farms from which virus was recovered during the UK 2001 outbreak will be generated and methods developed to infer the epidemiological transmission trees that relate how precisely the infection spread between farms. FMDV in the UK is an ideal system for this since the outbreak is likely to have been sampled close to exhaustively at the level of the 'premise'. Such a data set would become an absolute classic of its type, and hugely useful for testing ideas about the microevolution and transmission of RNA viruses generally. In order to maximize the robustness and confidence that can be placed in these inferences it is necessary to develop a more refined understanding of how the genetic signal in the data is generated, and transmitted between individuals from different herds. At the end of this project we will have developed new and improved viral tracing tools that can be used in real-time to support the FMD control and eradication programmes. Methods and results generated through this project will increase our confidence in the use of this type of sequence data to support epidemiological investigations realising the potential of full-genome sequencing for analysis of future epidemics of FMD.

Our ability to generate sequence data is undergoing sequential step-changes, leaving methods for analyzing these data trailing behind. However, the incredible uplift in the affordability of sequencing can potentially transform our understanding of how infectious diseases are transmitted between hosts (or closely related groups of hosts) - a process for which the fine-scale detail has to-date remained largely concealed from us. The capacity to reconstruct such a high resolution estimate of the transmission process would have a huge impact on our ability to focus efforts of control infectious disease, maximizing their effectiveness and efficiency.