Projects and Grants

Meta-analysis of defective viral genome sequences

Defective interfering particles (DIPs) are viral deletion mutants that hamper virus replication and are, thus, potent novel antiviral agents. To evaluate possible antiviral treatments we, first, need to get a deeper understanding of DIP characteristics. Thus, we perform meta-analyses of already published sequencing datasets of influenza viruses from in vivo and in vitro experiments. We characterize defective viral genomes (DVGs) with large deletions according to features, such as genome length, direct repeats, and nucleotide enrichment at the deletion site to reveal novel findings with potential implications for DVG biology and/or future DIP treatment design. For instance, we develop computational strategies to rank DVGs and pre-select top candidates for experimental validation. While we currently focus on influenza virus infections, our methodologies are transferable to other DIP-forming viruses, such as Zika-, dengue- and coronaviruses.

Exploring dynamics of defective viral genomes

In infected cell cultures that are cultured continuously over multiple weeks, the presence of DVGs causes periodic oscillations of the virus concentration. Since several thousands of DVGs are present simultaneously in infected cell cultures, it is not immediately evident which DVGs are the main drivers of those oscillations. However, to assess every DVG sequence individually in experiments would be resource- and time intensive. Hence, we leverage computational methods to mine longitudinal sequencing data to identify those DVGs that have an impact on the dynamics of the infectious virus concentration and, thus, could serve as potential candidates for antiviral therapy. 

In another project related to the impact of DVGs on virus dynamics we investigate the impact of DVGs on persistent and latent infections in real-world spreading and outbreak scenarios. For this, we collaborate with the Outbreak Preparedness and Response group of Dr. Sophie Duraffour (Bernhard Nocht Institute for Tropical Medicine, Hamburg) to elucidate the role of DVGs in hemorrhagic fever virus infections, e.g. as risk factor for resurging virus outbreaks, using tailored bioinformatics tools.