Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

<p>Abstract</p> <p>Background</p> <p>The genus <it>Flavivirus </it>encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4). Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle.</p> <p>Results</p> <p>We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation.</p> <p>Conclusions</p> <p>We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.</p

IRGM Is a Common Target of RNA Viruses that Subvert the Autophagy Network

Autophagy is a conserved degradative pathway used as a host defense mechanism against intracellular pathogens. However, several viruses can evade or subvert autophagy to insure their own replication. Nevertheless, the molecular details of viral interaction with autophagy remain largely unknown. We have determined the ability of 83 proteins of several families of RNA viruses (Paramyxoviridae, Flaviviridae, Orthomyxoviridae, Retroviridae and Togaviridae), to interact with 44 human autophagy-associated proteins using yeast two-hybrid and bioinformatic analysis. We found that the autophagy network is highly targeted by RNA viruses. Although central to autophagy, targeted proteins have also a high number of connections with proteins of other cellular functions. Interestingly, immunity-associated GTPase family M (IRGM), the most targeted protein, was found to interact with the autophagy-associated proteins ATG5, ATG10, MAP1CL3C and SH3GLB1. Strikingly, reduction of IRGM expression using small interfering RNA impairs both Measles virus (MeV), Hepatitis C virus (HCV) and human immunodeficiency virus-1 (HIV-1)-induced autophagy and viral particle production. Moreover we found that the expression of IRGM-interacting MeV-C, HCV-NS3 or HIV-NEF proteins per se is sufficient to induce autophagy, through an IRGM dependent pathway. Our work reveals an unexpected role of IRGM in virus-induced autophagy and suggests that several different families of RNA viruses may use common strategies to manipulate autophagy to improve viral infectivity

Virus-host interactomics: new insights and opportunities for antiviral drug discovery

International audienceThe current therapeutic arsenal against viral infections remains limited, with often poor efficacy and incomplete coverage, and appears inadequate to face the emergence of drug resistance. Our understanding of viral biology and pathophysiology and our ability to develop a more effective antiviral arsenal would greatly benefit from a more comprehensive picture of the events that lead to viral replication and associated symptoms. Towards this goal, the construction of virus-host interactomes is instrumental, mainly relying on the assumption that a viral infection at the cellular level can be viewed as a number of perturbations introduced into the host protein network when viral proteins make new connections and disrupt existing ones. Here, we review advances in interactomic approaches for viral infections, focusing on high-throughput screening (HTS) technologies and on the generation of high-quality datasets. We show how these are already beginning to offer intriguing perspectives in terms of virus-host cell biology and the control of cellular functions, and we conclude by offering a summary of the current situation regarding the potential development of host-oriented antiviral therapeutics

Extracting signature motifs from promoter sets of differentially expressed genes.

International audienceThere is a critical need for new and efficient computational methods aimed at discovering putative transcription factor binding sites (TFBSs) in promoter sequences. Among the existing methods, two families can be distinguished: statistical or stochastic approaches, and combinatorial approaches. Here we focus on a complete approach incorporating a combinatorial exhaustive motif extraction, together with a statistical Twilight Zone Indicator (TZI), in two datasets: a positive set and a negative one, which represents the result of a classical differential expression experiment. Our approach relies on the existence of prior biological information in the form of two sets of promoters of differentially expressed genes. We describe the complete procedure used for extracting either exact or degenerated motifs, ranking these motifs, and finding their known related TFBSs. We exemplify this approach using two different sets of promoters. The first set consists in promoters of genes either repressed or not by the transforming form of the v-erbA oncogene. The second set consists in genes the expression of which varies between self-renewing and differentiating progenitors. The biological meaning of the found TFBSs is discussed and, for one TF, its biological involvement is demonstrated. This study therefore illustrates the power of using relevant biological information, in the form of a set of differentially expressed genes that is a classical outcome in most of transcriptomics studies. This allows to severely reduce the search space and to design an adapted statistical indicator. Taken together, this allows the biologist to concentrate on a small number of putatively interesting TFs

Hepatitis C virus/human interactome identifies SMURF2 and the viral protease as critical elements for the control of TGF-β signaling

International audienceTGF-signaling induces epithelial to mesenchymal transition (EMT) and plays an important role in hepatocellular carcinoma (HCC) development. Clinical observations indicate that hepatitis C virus (HCV) chronic infection, which is a major cause of HCC, induces TGF-signaling perturbations. Here, we investigate the mechanisms by which HCV nonstruc-tural proteins interfere with TGF-signaling, in human hepatoma cell lines expressing HCV subgenomic repli-con. A transcriptomic study showed that TGF-stimulation of these cells resulted in a protumoral gene expression profile and in up-regulation of EMT-related genes compared to control interferon-treated cells not expressing HCV proteins. We found that the viral protease NS3-4A interacted with SMURF2, a negative regulator of TGF-signaling. In cells expressing HCV subgenomic replicon or NS3-4A, TGF-stimulation induced an increased expression of SMAD-dependent genes compared to control cells. This enhanced signal-ing was suppressed by SMURF2 overexpression and mimicked by SMURF2 silencing. In addition, NS3-4A expression resulted in an increased and prolonged TGF-induced phosphorylation of SMAD2/3 that was abrogated by SMURF2 overexpression. Neither NS3-4A protease activity nor SMURF2 ubiquitin-ligase activity was required to affect TGF-signaling. Therefore, by targeting SMURF2, NS3-4A appears to block the negative regulation of TGF-signaling, increasing the responsiveness of cells to TGF-. Verga-Gérard, A., Porcherot, M., Meyniel-Schicklin, L., André, P., Lotteau, V., and Perrin-Cocon, L. Hepatitis C virus/human interactome identifies SMURF2 and the viral protease as critical elements for the control of TGF-signaling. FASEB J. 27, 4027-4040 (2013). www.fasebj.or