Detalle de: HAVEN: The interplay between host aging and virus evolution: an evolutionary integrative systems biology approach

There is a common observation that elderly individuals are more susceptible to a variety of viral infections, resulting in higher morbidity and mortality than juveniles.  In addition, elderly show stronger inflammatory and autoimmune responses, take longer to recover from infections and are less responsive to vaccination.  These are consequences of the phenomenon of immunosenescence, the gradual deterioration of the innate and adaptive branches of the immune system.  Once a virus infects a host, the immune system represents the strongest selective force operating upon it and determines the evolution of more or less virulent strategies of host exploitation.  Therefore, it is logical that age differences among hosts must translate in highly heterogeneous selective pressure on viruses.  This heterogeneity is particularly relevant if transmission is assortative among age classes (e.g., transmission in kindergartens/elementary schools vs in nursing homes).  HAVEN aims to explore the consequences of such segregation of subviral populations in the evolution of viral fitness and disease-related traits, including the severity of infections.  To do so, it will be crucial to apply an integrative systems biology approach.  We will use two well-studied and easy to use experimental systems Arabidopsis thaliana and Caenorhabditis elegans, and their natural viruses, to test the same hypotheses related with host aging, immunosenescence and the evolution of RNA viruses.  First, we will phenotype the response to infection and use RNA-seq and sRNA-seq data to characterize the transcriptomic and regulatory differences among ages in response to viral infections.  Second, we will perform virus evolution experiments in four different configurations of hosts populations (i.e., all juvenile, all young sexually mature, all elderly, or age-heterogenous) and characterize both the genetic changes in viral genomes and differences in transcriptomic and regulatory responses between ancestral and evolved viruses, disentangling age-dependent targets of viral adaptation.  Finally, we will develop computational and mathematical multi-layer models of virus evolution in age-structured populations.  To close the loop of systems biology, the predictions from the models will inspire new experiments.  HAVEN will pave the way to a better understanding of the interplay between age and viral infection.  Furthermore, by comparing two widely different pathosystems, we will be able to tease apart universal principles from host-specific ones.