Exploring the Human-Nipah Virus Protein-Protein Interactome

Abstract

Nipah virus is an emerging, highly pathogenic, zoonotic virus of the family. Human transmission occurs by close contact with infected animals, the consumption of contaminated food, or, occasionally, via other infected individuals. Currently, we lack therapeutic or prophylactic treatments for Nipah virus. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. This aim led us to perform the present work, in which we identified 101 human-Nipah virus protein-protein interactions (PPIs), most of which (88) are novel. This data set provides a comprehensive view of the host complexes that are manipulated by viral proteins. Host targets include the PRP19 complex and the microRNA (miRNA) processing machinery. Furthermore, we explored the biologic consequences of the interaction with the PRP19 complex and found that the Nipah virus W protein is capable of altering p53 control and gene expression. We anticipate that these data will help in guiding the development of novel interventional strategies to counter this emerging viral threat. Nipah virus is a recently discovered virus that infects a wide range of mammals, including humans. Since its discovery there have been yearly outbreaks, and in some of them the mortality rate has reached 100% of the confirmed cases. However, the study of Nipah virus has been largely neglected, and currently we lack treatments for this infection. To develop these agents we must now improve our understanding of the host-virus interactions that underpin a productive infection. In the present work, we identified 101 human-Nipah virus protein-protein interactions using an affinity purification approach coupled with mass spectrometry. Additionally, we explored the cellular consequences of some of these interactions. Globally, this data set offers a comprehensive and detailed view of the host machinery's contribution to the Nipah virus's life cycle. Furthermore, our data present a large number of putative drug targets that could be exploited for the treatment of this infection.

Identifying potential entry inhibitors for emerging Nipah virus by molecular docking and chemical-protein interaction network

“…Initial drugtarget interactions data for identified drugs were extracted from Drugbank, while for extending these interactions to drug-target network, empirical data of host-protein interaction network was obtained from Human Protein Reference Database (HPRD, Release9) (Keshava Prasad et al, 2009). As a source of host-pathogen protein interaction network, interactions were obtained from an earlier study by Martinez-Gil, Vera-Velasco, and Mingarro (2017) (Martinez-Gil et al, 2017), which includes 126 protein-protein interactions between 91 human and 8 NiV proteins (N, P, V, W, C, M, G and F) determined by TAP-MS experiment. Dataset entries without any interacting partners were eliminated, and interactions that appeared more than once were simplified to single edges.…”

Comparison of expression profiling through microarray and RNA-seq analysis for Nipah virus

“…HUVEC between infected and unfected cells (Mathieu et al, 2012). In 2017 Martinez-Gil et al performed RNAseq experiment on NiV infected and uninfected HEK293T cell line (Martinez-Gil et al, 2017). The sample id of mock and experiment of the 2012 were GSM813064, GSM813066 and GSM813065, GSM813067 while that of 2017 were SRS2461913, SRS2461912, SRS2461909 and SRS2461911, SRS2461910, SRS2461908 respectively.…”

“…NiV is negative single stranded RNA (ssRNA) virus, with ~18kb genome size with six transcriptional units encoding nine proteins. The nine proteins are nucleocapsid (N), phosphoprotein (P), fusion protein (F), glycoprotein (G), polymerase (L), matrix protein (M), and interferon antagonists W, V and C (Martinez-Gil et al, 2017). The unique characteristics of the members of the genus Henipavirus from other paramyxovirus is the presence of long untranslated regions (UTR) at 3' end of viral mRNA transcripts excluding L gene (Harcourt et al, 2000).…”

“…In the present study we are utilizing the gene expression-based profiling to extract the differentially expressed genes (DEGs) from NiV two studies from year 2012 and 2017 (Mathieu et al, 2012;Martinez-Gil et al, 2017). As NiV is a BSL4 pathogen, therefore working on live virus is very limited.…”

“…As NiV is a BSL4 pathogen, therefore working on live virus is very limited. In literature the limited amount of computational analyses (intra-study) was performed to investigate the modified genes during infection (Mathieu et al, 2012;Martinez-Gil et al, 2017). However, the comprehensive cross comparison study between the two studies has not been done in the literature, so as to detect the common DEGs between the NiV infection.…”