Virogenomics: the virus-host interaction revisited

Abstract

Genomics tools allow us to assess gene expression 'genome wide' providing an unprecedented view on the host-side of the virus-host interaction. The success of the application of these tools crucially depends on our ability to reduce the total information load while increasing the information density of the data collected. In addition to the advanced data analysis algorithms, gene annotation-pathway databases, and theoretical models, specifically designed sets of complementary experiments are crucial in translating the collected genomics data into palatable knowledge. A better understanding of the molecular basis of virus-host interactions will support the rational design of improved and novel intervention strategies for viral infections.

Figure 1

Host responses to SARS-CoV infection in the lungs of adolescent cynomolgus macaques. A selection of genes, involved in the immune response, cell cycle, or lung repair processes, that showed an absolute fold change >5 and P < 0.0001 in at least two of the six animals was made (a). The detection of phosphorylated STAT1 in lung of SARS-CoV-infected macaques using immunohistochemistry shows abundant presence of phosphorylated STAT1 (brown) in lungs of SARS-CoV-infected macaques at day 1 postinfection, but not in SARS-CoV-infected cells (red) (b). Taken from: A de Lang et al. [32^••].

Figure 2

Schematic drawing of experimental design formats applied in transcriptional profiling studies of the virus–host interaction using different viruses and different cell types at different timepoints.