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Bioinformatics Algorithms and Predictive Models: The Grand Challenge in Computational Virology
(2021)
Never in the past has the relevance of bioinformatic and predictive tools been more central
in the field of virology as today. SARS-CoV-2 has brought along a huge health burden, but also
a deeper awareness that scientific progress can no longer be effective without extensive systems
for data storage, sharing and analysis, as well as computational tools dedicated to molecular
epidemiology, NGS data analysis, prediction of drug targets, multi-OMIC data integration, and
many other applications.
Next Generation Sequencing (NGS)-technologies developed very fast in recent years and is used widely in current research areas. The aim of this study was to use NGS (i) for the identification of pathogens in outbreaks and (ii) for the identification of virulence-relevant sequencepolymorphisms when comparing whole genome sequences. Therefore, a previous developed workflow was used to identify a new virus of the family Bornaviridae. The generation of whole genome sequences elucidated the molecular epidemiological connection of infection of variegated squirrels (Sciurus variegatoides) and three human cases of fatal encephalitis. By generating the whole genome sequence of a Porcine Epidemic Diarrhea Virus (PEDV) in Germany it was possible to find difference compared to circulating high virulent strains in the USA. This led to potential virulence marker to distinguish strain in the USA and Germany. Connections between sequence variation and virulence were further investigated for the bovine viral diarrhea virus 2c (BVDV-2c), cowpox viruses (CPXV) and classical swine fever virus (CSFV). Here, for a highly virulent BVDV-2c strain a mixture of different genome structure variants could be found. The majority of these genomes harbors a duplication within the p7/NS2 coding region and might cause a high virulence. For CPXV virus isolated of different hosts were analyzed and a correlation between genome sequence and the A-type inclusion body phenotype could be found. Furthermore, several deletion/insertion events were detected which might influence the virulence of these strains. Finally, the virus population of CSFV strains in pigs was characterized. However, the population of the inoculum as well as of acute-lethal and chronically infected animals gave no indication that the virus itself causes the different types of disease outcome. In conclusion, this thesis shows the great potential of NGS for virus identification and characterization. Furthermore, it makes the identification of potential virulence marker possible which subsequently can be analyzed by reverse genetics.