Kaposi's sarcoma: a computational approach through protein-protein interaction and gene regulatory networks analysis

Abstract

Interactomic data for Kaposi's Sarcoma Associated Herpes virus (KSHV) - the causative agent of vascular origin tumor called Kaposi's sarcoma - is relatively modest to date. The objective of this study was to assign functions to the previously uncharacterized ORFs in the virus using computational approaches and subsequently fit them to the host interactome landscape on protein, gene, and cellular level. On the basis of expression data, predicted RNA interference data, reported experimental data, and sequence based functional annotation we also tried to hypothesize the ORFs role in lytic and latent cycle during viral infection. We studied 17 previously uncharacterized ORFs in KSHV and the host-virus interplay seems to work in three major functional pathways - cell division, transport, metabolic and enzymatic in general. Studying the host-virus crosstalk for lytic phase predicts ORF 10 and ORF 11 as a predicted virus hub whereas PCNA is predicted as a host hub. On the other hand, ORF31 has been predicted as a latent phase inducible protein. KSHV invests a lion's share of its coding potential to suppress host immune response; various inflammatory mediators such as IFN-γ, TNF, IL-6, and IL-8 are negatively regulated by the ORFs while Il-10 secretion is stimulated in contrast. Although, like any other computational prediction, the study requires further validation, keeping into account the reproducibility and vast sample size of the systems biology approach the study allows us to propose an integrated network for host-virus interaction with good confidence. We hope that the study, in the long run, would help us identify effective dug against potential molecular targets.