RT Journal Article
SR Electronic
T1 Critical Nodes of Virus–Host Interaction Revealed Through an Integrated Network Analysis
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 548909
DO 10.1101/548909
A1 Korbinian Bösl
A1 Aleksandr Ianevski
A1 Thoa T. Than
A1 Petter I. Andersen
A1 Suvi Kuivanen
A1 Mona Teppor
A1 Eva Zusinaite
A1 Uga Dumpis
A1 Astra Vitkauskiene
A1 Rebecca J. Cox
A1 Hannimari Kallio-Kokko
A1 Anders Bergqvist
A1 Tanel Tenson
A1 Valentyn Oksenych
A1 Magnar Bjørås
A1 Marit W. Anthonsen
A1 David Shum
A1 Mari Kaarbø
A1 Olli Vapalahti
A1 Marc P. Windisch
A1 Giulio Superti-Furga
A1 Berend Snijder
A1 Denis Kainov
A1 Richard K. Kandasamy
YR 2019
UL http://biorxiv.org/content/early/2019/02/13/548909.abstract
AB Viruses are one of the major causes of various acute and chronic infectious diseases and thus a major contributor to the global burden of disease. Several studies have shown how viruses have evolved to hijack basic cellular pathways and evade innate immune response by modulating key host factors and signalling pathways. A collective view of these multiple studies could advance our understanding of viral evasion mechanisms and provide new therapeutic perspectives for the treatment of viral diseases. Here, we performed an integrative meta-analysis to elucidate the 17 different host-virus interactomes. Network and bioinformatics analyses showed how viruses with small genomes efficiently achieve the maximal effect by targeting multifunctional and highly connected host proteins with a high occurrence of disordered regions. We also identified the core cellular process subnetworks that are targeted by all the viruses. Integration with functional RNA interference (RNAi) datasets showed that a large proportion of the targets are required for viral replication. Furthermore, we performed an interactome-informed drug re-purposing screen and identified novel activities for broad-spectrum antiviral agents against hepatitis C virus and human metapneumovirus. Altogether, these orthogonal datasets could serve as a platform for hypothesis generation and follow-up studies to broaden our understanding of the viral evasion landscape.