Long-term interactions between viruses and their hosts often develop into genetic arms races, which result in fast-evolving proteins (i.e. proteins evolving under positive natural selection), especially in immune proteins. A bioinformatic screen of proteins in a component of the primate innate immune response, the interferon system, demonstrated that proteins farther downstream of interferon induction are more likely to be evolving under positive natural selection compared to proteins in interferon induction pathways. One of the proteins under positive selection in this screen, STING, is a known target of proteases from a group of viruses called flaviviruses. The human haplotypes of STING (three of which are studied in this work) demonstrate a range of phenotypes of antagonism and interferon induction that may help explain the evolutionary history of this crucial immune protein.
The cleavage of STING demonstrates that the dengue virus protease targets host proteins for cleavage as well as viral proteins. In an attempt to identify novel targets of the dengue virus protease, a machine learning screen was used to predict possible motifs based on known motifs. This resulted in the identification of DGAT2, a newly described target of flavivirus proteases. The ability to cleave DGAT2, a host protein involved in maintaining lipid homeostasis, improves dengue virus replication, and is a conserved property of all flavivirus proteases tested. DGAT2 is not evolving under positive selection, making it a host-virus antagonistic interaction that has not resulted in an evolutionary arms race. However, identifying and describing this host-virus interaction helps us understand how dengue virus and other flaviviruses alter the host lipid environment during replication.</p
