VIROINF does not only fill the gaps of tools to be developed but generates a new era of tools for virus-host interactions across all main virus and host species.
During productive infection, viral proteins and RNAs interact with cellular pathways to reprogram their hosts’ cells for efficient virus replication and immune evasion. ESR 13 will develop tools to identify the genes that are involved in virus-host interaction at the example of crAssphage. For many viral genes, their functions remain unknown. However, for crAssphage functional proxies for proteins are linked to hosts by assessing functional descriptions. ESR 13 will specifically address proteins of unknown function by developing Deep Learning algorithms to predict protein functions and validate the predicted functions of unknown Coronavirus accessory proteins.
VIROINF will study virus-host interactions in a specific context to be used afterwards generically: ESR 6 will study the modulation of hosts cells upon cytomegalovirus infection using an integrative analysis of a broad range of high-throughput data sets. She or he will focus on the identification of novel genetic elements of the human and mouse cytomegalovirus, analyse their conservation in the human system and the mouse model and investigate conserved reprogramming mechanisms. New computational tools will be developed for the integrative analysis of the big heterogeneous data sets alongside with a computational model of CMV induced reprogramming of the regulatory network. ESR 15 will analyse changes in host gene expression of cytomegalovirus and how these are affected by RNA modification. ESR 15 will further examine whether this level of gene regulation helps the virus to modulate the host response.
Viral infections are characterised by complex interactions between viruses and their hosts. Viruses exploit and manipulate cellular pathways for efficient replication, whereas the host raises antiviral responses to combat the infection. These interactions shape the evolution of both virus and host. The aim of ESR 9 is to understand the effect of host antiviral responses on viral population dynamics. Life history theory predicts that there may be trade-offs that prevent simultaneous improvement in fitness traits, such as resistance to pathogens and virulence. To test this hypothesis, well-established model viruses (Drosophila C virus, Nora virus) will be serially passaged over Drosophila mutants in which individual immune pathways (e.g. RNAi, Jak-Stat, Heat-shock response) are inactivated or over-expressed. At multiple passages, RNA will be recovered from the infected animals and subjected to RNA-Seq analyses. In parallel, ESR 9 will isolate virus populations to deduce phenotypes such as viral loads, host survival, and specific readouts of virus-induced pathology. RNA-Seq will be used to accurately describe viral population dynamics as developed by ESR 3. Moreover, RNA seq data will be analysed to see whether the virus populations evolved under different immune pressures induce differential antiviral responses.
- ESR 6: Conservation of regulatory elements and effector mechanisms in lytic and latent cytomegalovirus infection
- ESR 9: Impact of host immune pathways on virus evolution
- ESR 13: Functional inferences from colinear crAssphage genomes
- ESR 15: Elucidating the role of RNA modification during cytomegalovirus infection
- ESR 3: Development of new computational methods for characterisation and analyses of intra-host viral populations
- ESR 4: Experimental evolution of Deformed wing virus in bees
- ESR 8: Genotype-Phenotype mapping and inference of epistatic interactions driving adaptation in viral hosts
- ESR 10: Computational prediction of virus-host interactions in the microbiome
Quantitative measures of within-host viral genetic diversity Journal Article
In: Curr Opin Virol, 49 , pp. 157-163, 2021.
In: Viruses, 13 (5), pp. 766, 2021.