Research Project Database
| Code: | EMIDA26 |
| 1: | EMIDA26 |
| Title: | Epi-SEQ – Molecular epidemiology of epizootic diseases using next generation sequencing technology |
| 2: | Epi-SEQ – Molecular epidemiology of epizootic diseases using next generation sequencing technology |
| Country: | United Kingdom Italy Sweden Belgium Germany |
| 3: | United Kingdom Italy Sweden Belgium Germany |
| Funding Organisation: | Biotechnology and Biological Science Research Council (BBSRC) Department for the Environment, Food and Rural Affairs (Defra) The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning Veterinary and Agrochemical Research Centre (CODA-CERVA) Italian Ministry of Health Department for Veterinary Public Health, Nutrition and Food Safety Federal Ministry of Food Agriculture and Consumer Protection (BMELV) |
| 4: | Biotechnology and Biological Science Research Council (BBSRC) Department for the Environment, Food and Rural Affairs (Defra) The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning Veterinary and Agrochemical Research Centre (CODA-CERVA) Italian Ministry of Health Department for Veterinary Public Health, Nutrition and Food Safety Federal Ministry of Food Agriculture and Consumer Protection (BMELV) |
| Animal Group: | Chickens Pigs Cattle Sheep Turkeys Goats |
| 5: | Chickens Pigs Cattle Sheep Turkeys Goats |
| Pathogen: | Avian influenza viruses Foot-and-mouth disease virus (FMDV) Classical Swine Fever Virus (CSFV) Newcastle disease virus (NDV) |
| 6: | Avian influenza viruses Foot-and-mouth disease virus (FMDV) Classical Swine Fever Virus (CSFV) Newcastle disease virus (NDV) |
| Disease: | |
| 7: | |
| Category: | |
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| 9: | |
| Research Organisation: | Institute for Animal Health (IAH) University of Glasgow Veterinary and Agrochemical Research Centre (CODA-CERVA) Swedish University of Agricultural Sciences (SLU) FLI - Friedrich Loeffler Institute Istituto Zooprofilattico Sperimentale della Venezie |
| 10: | Institute for Animal Health (IAH) University of Glasgow Veterinary and Agrochemical Research Centre (CODA-CERVA) Swedish University of Agricultural Sciences (SLU) FLI - Friedrich Loeffler Institute Istituto Zooprofilattico Sperimentale della Venezie |
| Number of Research Staff (FTE): | |
| 11: | |
| Principal Investigator (PI): | Steven Van Borm, Coda-Cerva |
| 12: | Steven Van Borm, Coda-Cerva |
| Cost (Euros): | 2008639 |
| 13: | 2008639 |
| End Date (dd/mm/yyyy): | 31-03-2015 |
| 14: | 1427756400 |
| Duration (months): | 36 |
| 15: | 36 |
| Link: | |
| 16: | |
| Project objectives and deliverables with estimated delivery dates for each deliverable (if possible): | 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. |
| 17: | 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. |
| Files | No files are attached. |
