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      Human Host Factors Required for Influenza Virus Replication

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          Abstract

          Influenza A virus is an RNA virus that encodes up to eleven proteins and this small coding capacity demands that the virus utilize the host cellular machinery for many aspects of its life cycle1. Knowledge of these host cell requirements not only informs us of the molecular pathways exploited by the virus but also provides additional targets that could be pursued for antiviral drug development. Here, we employ an integrative systems approach, based upon genome-wide RNAi screening, to identify 295 cellular cofactors required for early-stage influenza virus replication. Within this group those involved in kinase-regulated signaling, ubiquitination and phosphatase activity are the most highly enriched and 181 factors assemble into a highly significant host-pathogen interaction network. Moreover, 219 of the 295 factors were confirmed to be required for efficient wild-type influenza virus growth and further analysis of a subset of genes revealed 23 factors necessary for viral entry, including members of the vacuolar ATPase (vATPase) and COPI-protein families, fibroblast growth factor receptor (FGFR) proteins, and glycogen synthase kinase 3 (GSK3)-beta. Additionally, 10 proteins were confirmed to be involved in post-entry steps of influenza virus replication. These include nuclear import components, proteases, and the calcium/calmodulin-dependent protein kinase (CaM kinase) II beta (CAMK2B). Importantly, growth of swine-origin H1N1 influenza virus is also dependent on the identified host factors and we show that small molecule inhibitors of several factors, including vATPase and CAMK2B, antagonize influenza virus replication. Influenza viruses are a major cause of morbidity and mortality, and influenza A viruses in particular have the propensity to cause pandemic outbreaks such as occurred in 1918, 1957, 1968 and currently in 2009 with the swine-origin H1N1 influenza virus2. Two of the viral proteins, neuraminidase (NA) and the M2 ion channel protein are the targets for the FDA-approved influenza antiviral drugs; oseltamivir, zanamivir, amantadine and rimantadine 3. Unfortunately, there is now widespread resistance to both of these drug classes 4. Combined with the limited number of viral drug targets for influenza virus, this creates concern for the development of new influenza therapies. An alternative therapeutic strategy that may greatly reduce the emergence of viral resistance is the pharmacological targeting of host factors required for viral replication. Genome-wide RNAi screens have enabled the identification of host factors required by a number of RNA viruses 5–7 8 9, 10 11, including an insect cell-based RNAi screen which implicated 110 Drosophila genes in influenza virus replication 12. In an effort to more comprehensively characterize the host machinery utilized by influenza virus in mammalian cells, we have performed a genome-wide siRNA screen with human lung epithelial (A549) cells. To facilitate the readout for the high-throughput screen, the coding region for the influenza A/WSN/33 virus hemagglutinin (HA) protein was replaced with that of Renilla luciferase (Figure 1a)13. As no HA is produced, this recombinant virus cannot complete its replication cycle. Thus our RNAi screen focuses on the cellular requirements for viral entry, uncoating, nuclear import, and viral RNA transcription/translation, but is not expected to identify factors involved in virus assembly, budding or release. An arrayed siRNA library targeting over 19,000 human genes was employed to transfect human A549 cells (Figure 1b and Supplementary Information). These cells were infected with the modified influenza virus (WSN-Ren), and luciferase readings were taken after 12, 24, and 36h. Data from two independent screens were analyzed using an integrative data analysis approach, which included Redundant siRNA Activity (RSA), as well as interactome and ontology-based analyses, (see Supplementary Information)6, 14. Using these methodologies, we were able to confirm 295 cellular genes for which at least 2 siRNAs reduced viral infection by 35% or greater (~2 standard deviations from mean of negative controls), without a concomitant induction of significant cellular toxicity (Supplementary Figure S1 and Supplementary Table S1). While some of these factors were previously known to be involved in influenza virus replication (confirming the robustness of our RNAi approach), the majority of the factors identified through this analysis represent host genes that have not previously been implicated in mediating influenza virus replication. Analysis of over-represented biological annotations identified over 170 statistically enriched categories (Supplementary Table S2), which fell into 11 broadly related functional groups (Supplementary Figure S2, Supplementary Table S3). Signaling molecules, including those involved in the PI3K/AKT pathway, molecules that function to regulate cytoskeletal dynamics, and proteins involved in ubiquitination, phosphatase, and protease activities were overrepresented amongst the 295 factors, underscoring the importance of these cellular functions during influenza virus infection (Table 1, see also Supplementary Table S4 and S5). Consistent with these observations, we found that small molecule inhibition of two identified AKT pathway regulators, mTOR (FRAP1) and HSP90AA1, as well as microtubule assembly (TUBB), resulted in a dose-dependent inhibition of influenza virus replication (Supplementary Figure S3)15, 16. To understand the network of host-pathogen interactions that govern the early steps of influenza virus replication, we employed several protein interaction datasets to construct a host-pathogen interaction map depicting associations between the identified host factors, viral-encoded proteins, and other cellular proteins (Figure 1c, Supplementary Figures S4 and S5). The integration of RNAi and interactome datasets produced a network containing 181 confirmed host cellular factors that mediate 4,266 interactions between viral or cellular proteins, and act as central rate-limiting “hubs” in cellular pathways or processes required for influenza virus replication (Supplementary Figure S6, Supplementary Table S6). Although the coverage and quality of currently available protein interaction databases remains difficult to assess17, the influenza interaction map was found to be highly significant (p<0.001), indicating that this network topology is not randomly derived, and likely reflects a unique cellular sub-network. Of the 295 identified host factors required for influenza virus replication, 53 were previously identified in RNAi screens for different RNA viruses (Supplementary Figure S7, Supplementary Table S7), including 9 mammalian orthologues of host proteins required for influenza virus infection of Drosophila cells 12. It is currently not clear if this statistically significant (p=3.1 × 10−9), but modest, overlap reflects false-negative activities in the current or the aforementioned screen, or the differential host cell requirements between insect and mammalian cells for influenza virus replication. However, functional classification and protein interaction analysis of these shared factors revealed that, collectively, these viruses rely on common host cellular mechanisms to promote discrete stages of their life cycles (Figure 1d, Supplementary Figure S8; Supplementary Table S8). To verify that the genes identified through the use of the reporter virus reflect the requirements in the context of a wild-type (WT) virus infection, 219 of 295 identified genes were confirmed to inhibit multi-cycle replication of WT WSN virus with at least two siRNAs per gene. Furthermore, 76% of the remaining genes had one siRNA that inhibited WT influenza replication, indicating a high confirmation rate (Figure 2a, Supplementary Table S9). For a subset of these genes additional assays were undertaken to confirm that depletion of these genes resulted in reduced viral gene expression (Figure 2a, Supplementary Table S9), and also to ensure that inhibition of viral replication was not being triggered by a non-specific siRNA-mediated induction of an antiviral state (Supplementary Table S10). Next, to identify potential factors specifically involved in virus entry steps, 45 of the top-scoring genes in the WT WSN assay were selected to be tested in a pseudotyped particle (PP) entry assay, designed to identify host factors that impede low-pH-dependent entry mediated specifically by influenza virus HA (WSN) and vesicular stomatitis virus (VSV)-G protein, while not affecting pH-independent entry promoted by the murine leukemia virus (MMLV) envelope (Env) 18, 19. WSN-PP infection was reduced in the presence of siRNAs targeting 23 of these genes, including CD81, FGFR4, GSK3B, MAP2K3 and the v-ATPase subunit ATP6V0C (Figure 2a, 2b, Supplementary Table S11, Supplementary Figure S9). These genes were also required for efficient VSV-G-PP (but not MMLV-PP) infection, suggesting a role in low-pH-dependent virus entry. Importantly, small molecule inhibitors of FGFR4, GSK3B, and v-ATPase activities attenuated replication of WSN virus, further highlighting their importance in influenza virus infection (Supplementary Figures S3 and S10). The COPI coat complex is made up of seven subunits, four of which (ARCN1, COPA, COPB2, COPG) were among the confirmed factors in the protein interaction network (Figures 1c and 2c). COPI association with endosomes is pH-dependent and coatomer complex is required for the formation of intermediate transport vesicles between the early and late endosomes 20, 21. Consistent with this role, depletion of COPG and ARCN1 both blocked WSN-PP infection (Figure 2b). The requirement for ARCN1 during the influenza virus entry step was further demonstrated using a more direct virus-like particle (VLP) assay (Figure 2d)22, as well as immunolocalization studies (Figure 2e). To evaluate those factors that affect virus replication but not influenza virus entry, we monitored the localization of the influenza virus nucleoprotein (NP) in siRNA-depleted cells after infection with influenza A/WSN/33 virus (Figure 3a; Supplementary Figure S11, see Supplementary Information). In comparison to controls, cells depleted of CSE1L, PRSS35, F13A1, SF3A1, CAMK2B, KPNB1, and PPP1R14D show a significant decrease (p<0.01) of nuclear to cytoplasmic ratios of NP protein at 180 min. With the exception of F13A1, depleting these factors did not inhibit entry by WSN pseudotyped virus or β-lactamase (Bla)-M1 VLPs (Figure 3a), confirming their role in post-entry steps of influenza virus infection. Depletion of CSE1L, PRSS35, and F13A1 also led to a statistically significant (p<0.02) reduction of nuclear to cytoplasmic NP ratios at 90 minutes post-infection, suggesting that they may play specific roles in early post-entry steps, such as viral uncoating or nuclear import of viral ribonucleoproteins (vRNPs; see also Supplementary Figure S12). Consistent with a role in nuclear trafficking, imaging at higher resolution confirmed that RNAi-mediated inhibition of CSE1L, but not CAMK2B or KPNB1, results in a decrease in nuclear vRNPs typically seen 90 min after infection with influenza virus (Figure 3b)23. Furthermore, CSE1L specifically inhibited influenza virus gene expression in a mini-genome replicon assay, suggesting that CSE1L activity is required for the nuclear import of vRNPs as well as newly synthesized viral proteins (Figure 3c, Supplementary Table S12). Calcium/calmodulin-dependent protein kinase (CaM kinase) II beta (CAMK2B) is a ubiquitously expressed calcium sensor that regulates diverse cellular functions, including actin cytoskeletal regulation and CREB-dependent transcription 24. Our data implicate this kinase in the regulation of viral RNA transcription as RNAi-knockdown of the kinase had a moderate effect on expression of an influenza mini-genome (Figure 3c), but did not delay nuclear accumulation of vRNPs at 90 min post-infection (Figure 3b). We also show that a specific inhibitor of CAMK2B, KN-93, inhibits influenza virus growth (Figure 3d, Supplementary Figure S13), suggesting that pharmacological targeting of this kinase may be an effective strategy for the development of host factor-directed antivirals25. Finally, we assessed the requirements for twelve identified host cellular factors in the replication of a swine-origin influenza virus (SOIV) isolate from the 2009 pandemic (A/Netherlands/602/2009 (H1N1)) in comparison with influenza A/WSN/33 virus and VSV. Viral growth in siRNA-treated A549 cells revealed that these proteins are all required for both SOIV and WSN replication but none of these factors, with the exception of the vATPase and COPI factors, inhibited VSV replication (Figure 3e, Supplementary Table S13, Supplementary Figure S14). These results indicate that factors identified here are likely important for the replication of multiple influenza virus strains. This genome-wide analysis of influenza virus host factor requirements described here has revealed a large number of cellular proteins and biological pathways previously unknown to be involved in the influenza virus life-cycle. These include the identification of COPI complex, FGFR, GSK3B, CAMK2B, PRSS35, and others. Since this study focused on host factors that regulate the early steps of influenza virus replication, additional analyses will likely help to elucidate the full complement of cellular proteins required during the complete replication cycle. Further understanding of the roles for these proteins in influenza virus infection will provide new insight into the host-pathogen interactions that orchestrate the viral replication cycle and novel opportunities for the development of host factor-directed antiviral therapies. Methods Renilla luciferase influenza virus The coding region for the viral hemagglutinin (HA) protein was replaced with that of Renilla luciferase and the packaging signals for the HA segment were incorporated, as previously described 13. The recombinant WSN-Ren virus was generated by reverse genetics in the presence of complementing HA and amplified in HA-expressing MDCK cells 13. Genome-wide RNAi screen Genome-wide libraries comprising 98,737 synthetic siRNAs targeting 19,628 unique human genes were arrayed in 384-well plates (7ng/siRNA) such that each well contained either two (47,560 wells) or one (3617 wells) unique and identifiable siRNA per gene. Although use of low screening concentrations of RNAi may help to minimize off-target activities, this may also contribute to false-negative activities. The library matrix was introduced into A549 cells through a high throughput transfection process 26, 27 and after 48h the cells were infected with WSN-Ren virus at a multiplicity of infection (MOI) of 0.5. EnduRen Live Cell substrate (Promega) was added after 5 hours and relative luminescence for each well was analyzed on a plate reader (Viewlux) at 12h, 24h and 36h after infection. For the toxicity screen Cell-titer-glo (Promega) reagent was added 72h after siRNA transfection. The screens were run minimally in duplicate and analyzed using a scaling methodology that sets the positive control siRNA at an arbitrary value of 0.1, and the negative control siRNAs at 1. siRNAs targeting host factors were assigned a score based on the distribution of these values. For more details see Supplementary Information. Inhibition of virus growth siRNA-transfected A549 cells were infected with either influenza A/WSN/33 virus or VSV (MOI of 0.01) or swine origin influenza A/Netherlands/602/2009 virus (SOIV) (MOI of 1) at 48h post siRNA transfection. At 36h post infection supernatants were harvested and virus titers were determined by plaque assay on MDCK cells (for A/WSN/33 and A/Netherlands/602/2009) or on Vero cells for VSV. Supplementary Material 1 2 3 4

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          Most cited references24

          • Record: found
          • Abstract: found
          • Article: not found

          An empirical framework for binary interactome mapping

          Several attempts have been made at systematically mapping protein-protein interaction, or “interactome” networks. However, it remains difficult to assess the quality and coverage of existing datasets. We describe a framework that uses an empirically-based approach to rigorously dissect quality parameters of currently available human interactome maps. Our results indicate that high-throughput yeast two-hybrid (HT-Y2H) interactions for human are superior in precision to literature-curated interactions supported by only a single publication, suggesting that HT-Y2H is suitable to map a significant portion of the human interactome. We estimate that the human interactome contains ~130,000 binary interactions, most of which remain to be mapped. Similar to estimates of DNA sequence data quality and genome size early in the human genome project, estimates of protein interaction data quality and interactome size are critical to establish the magnitude of the task of comprehensive human interactome mapping and to illuminate a path towards this goal.
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            • Record: found
            • Abstract: found
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            RNA interference screen for human genes associated with West Nile virus infection.

            West Nile virus (WNV), and related flaviviruses such as tick-borne encephalitis, Japanese encephalitis, yellow fever and dengue viruses, constitute a significant global human health problem. However, our understanding of the molecular interaction of such flaviviruses with mammalian host cells is limited. WNV encodes only 10 proteins, implying that it may use many cellular proteins for infection. WNV enters the cytoplasm through pH-dependent endocytosis, undergoes cycles of translation and replication, assembles progeny virions in association with endoplasmic reticulum, and exits along the secretory pathway. RNA interference (RNAi) presents a powerful forward genetics approach to dissect virus-host cell interactions. Here we report the identification of 305 host proteins that affect WNV infection, using a human-genome-wide RNAi screen. Functional clustering of the genes revealed a complex dependence of this virus on host cell physiology, requiring a wide variety of molecules and cellular pathways for successful infection. We further demonstrate a requirement for the ubiquitin ligase CBLL1 in WNV internalization, a post-entry role for the endoplasmic-reticulum-associated degradation pathway in viral infection, and the monocarboxylic acid transporter MCT4 as a viral replication resistance factor. By extending this study to dengue virus, we show that flaviviruses have both overlapping and unique interaction strategies with host cells. This study provides a comprehensive molecular portrait of WNV-human cell interactions that forms a model for understanding single plus-stranded RNA virus infection, and reveals potential antiviral targets.
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              • Record: found
              • Abstract: found
              • Article: not found

              Drosophila RNAi screen identifies host genes important for influenza virus replication.

              All viruses rely on host cell proteins and their associated mechanisms to complete the viral life cycle. Identifying the host molecules that participate in each step of virus replication could provide valuable new targets for antiviral therapy, but this goal may take several decades to achieve with conventional forward genetic screening methods and mammalian cell cultures. Here we describe a novel genome-wide RNA interference (RNAi) screen in Drosophila that can be used to identify host genes important for influenza virus replication. After modifying influenza virus to allow infection of Drosophila cells and detection of influenza virus gene expression, we tested an RNAi library against 13,071 genes (90% of the Drosophila genome), identifying over 100 for which suppression in Drosophila cells significantly inhibited or stimulated reporter gene (Renilla luciferase) expression from an influenza-virus-derived vector. The relevance of these findings to influenza virus infection of mammalian cells is illustrated for a subset of the Drosophila genes identified; that is, for three implicated Drosophila genes, the corresponding human homologues ATP6V0D1, COX6A1 and NXF1 are shown to have key functions in the replication of H5N1 and H1N1 influenza A viruses, but not vesicular stomatitis virus or vaccinia virus, in human HEK 293 cells. Thus, we have demonstrated the feasibility of using genome-wide RNAi screens in Drosophila to identify previously unrecognized host proteins that are required for influenza virus replication. This could accelerate the development of new classes of antiviral drugs for chemoprophylaxis and treatment, which are urgently needed given the obstacles to rapid development of an effective vaccine against pandemic influenza and the probable emergence of strains resistant to available drugs.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                0028-0836
                1476-4687
                20 March 2010
                11 February 2010
                11 August 2010
                : 463
                : 7282
                : 813-817
                Affiliations
                [1 ]Infectious and Inflammatory Disease Center, Burnham Institute for Medical Research, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA
                [2 ]Department of Microbiology, Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029, USA
                [3 ]Genomics Institute of the Novartis Research Foundation, 10675 John J Hopkins Dr., San Diego, CA 92121, USA
                [4 ]Nomis Center for Immunobiology and Microbial Pathogenesis The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037
                [5 ]Departments of Medicine and Bioengineering, University of California, San Diego, Pharmaceutical Sciences Bldg, 9500 Gilman Drive, La Jolla, CA 92093, USA
                [6 ]Gene Expression Laboratory, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA 92037
                [7 ]Department of Medicine, Division of Infectious Diseases, Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029, USA
                [8 ]Global Health and Emerging Pathogens Institute, Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029, USA
                Author notes
                [* ]to whom correspondences should be addressed ( megan.shaw@ 123456mssm.edu & schanda@ 123456burnham.org )
                [9]

                equal contributions

                [10]

                equal senior author contributions

                Article
                nihpa165660
                10.1038/nature08699
                2862546
                20027183
                aa3baaf1-798f-4156-942a-7a6830bd3aaa

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                Funding
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: U54 AI057158-065713 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
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                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: U01 AI074539-02 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
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                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-10 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
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                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
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                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
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                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-06 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-05 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-04 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-03 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-02 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: T32 AI007647-01 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: P01 AI058113-050004 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: P01 AI058113-040004 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: P01 AI058113-030004 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: P01 AI058113-020004 ||AI
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
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