Identification of Host Proteins Involved in Japanese ... - ACS Publications

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Identification of Host Proteins Involved in Japanese Encephalitis Virus Infection by Quantitative Proteomics Analysis Lei-Ke Zhang,†,‡,⊥ Fan Chai,†,§,⊥ Hao-Yu Li,†,‡ Gengfu Xiao,*,†,§ and Lin Guo*,†,‡ †

State Key Laboratory of Virology and ‡College of Life Sciences, Wuhan University, Wuhan, China § Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China S Supporting Information *

ABSTRACT: Japanese encephalitis virus (JEV) enters host cells via receptor-mediated endocytosis and replicates in the cytoplasm of infected cells. To study virus−host cell interactions, we performed a SILAC-based quantitative proteomics study of JEV-infected HeLa cells using a subcellular fractionation strategy. We identified 158 host proteins as differentially regulated by JEV (defined as exhibiting a greater than 1.5-fold change in protein abundance upon JEV infection). The mass spectrometry quantitation data for selected proteins were validated by Western blot and immunofluorescence confocal microscopy. Bioinformatics analyses were used to generate JEV-regulated host response networks consisting of regulated proteins, which included 35 proteins that were newly added based on the results of this study. The JEV infection-induced host response was found to be coordinated primarily through the immune response process, the ubiquitin-proteasome system (UPS), the intracellular membrane system, and lipid metabolism-related proteins. Protein functional studies of selected host proteins using RNA interference-based techniques were carried out in HeLa cells infected with an attenuated or a highly virulent strain of JEV. We demonstrated that the knockdown of interferon-induced transmembrane protein 3 (IFITM3), Ran-binding protein 2 (RANBP2), sterile alpha motif domain-containing protein 9 (SAMD9) and vesicle-associated membrane protein 8 (VAMP8) significantly increased JEV replication. The results presented here not only promote a better understanding of the host response to JEV infection but also highlight multiple potential targets for the development of antiviral agents. KEYWORDS: Japanese encephalitis virus, quantitative proteomics, STRING, siRNA, IFITM3, RANBP2, SAMD9, VAMP8

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INTRODUCTION Japanese encephalitis virus (JEV) is the leading cause of epidemic encephalitis worldwide, accounting for more than 16,000 reported cases and 5,000 deaths annually.1 Half of the survivors suffer neuropsychiatric sequelae.2 JEV is a zoonotic virus that is transmissible between pigs, ardeid wading birds and Culex mosquitoes.3 Humans are considered dead-end hosts because their low viremia levels are insufficient to infect feeding mosquitoes.4 With a plus-sense, single-stranded RNA genome of ∼11 kb in length, the JEV virion genome encodes 3 structural proteins, capsid protein (C), membrane protein (M), and envelope protein (E), and 7 nonstructural proteins (NS), NS, NS2A, NS2B, NS3, NS4A, NS4B, and NS5.5 JEV belongs to the “Flavivirus” genus of the family Flaviviridae.6 The Flaviviridae include several other important human pathogens, such as Hepatitis C virus (HCV), West Nile virus (WNV), yellow fever virus (YFV), and Dengue virus (DENV). Flaviviruses enter host cells via receptor-mediated endocytosis and replicate in the cytoplasm of infected cells. During infection, the viruses hijack various host cell systems to promote their own replication and survival under the constant attack of the host immune system. The host cells in turn © XXXX American Chemical Society

activate various antiviral responses. The balance of the host− virus interactions determines the outcome of viral infection and disease progression.7 A better understanding of these host− virus interactions may lead to the identification of potential drug targets and the development of novel antiviral agents.8 Due to the complex nature of virus−host interactions, many recent studies have turned from the traditional hypothesisdriven, one-pathway-at-a-time approaches in favor of systems biology or large-scale screening approaches; these methods allow the system-wide evaluation of virus−host interactions at many different levels, including transcriptomes, metabolomes, or proteomes.9 It is now well recognized that large-scale screening may be very effective for identifying host proteins of interest, many of which are unexpected and, after additional functional validation, may lead to new discoveries regarding host−virus interactions. One large-scale screening strategy that has been used in recent years is proteomics analysis. A key question addressed in various proteomics-based studies has been how viral infection Received: January 4, 2013

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dx.doi.org/10.1021/pr400011k | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

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Subcellular Fractionation

or the expression of a specific viral protein affects the protein expression profile of the host cell.10 For example, Boris et al. used two-dimensional fluorescence difference gel electrophoresis (2-D DIGE) to identify 127 host proteins that were differentially expressed in West Nile virus (WNV)-infected Vero cells.11 Choum et al. used a similar approach to identify 18 significantly differentially regulated host proteins in the midgut of Dengue virus (DENV-2)-infected Aedes aegypti, the yellow fever mosquito.12 However, proteins with low abundance and proteins that are very large or very small have proven difficult to resolve using 2D gels.10 An alternative to 2D gel-based techniques is provided by quantitative proteomics methods based on stable isotope labeling by amino acids in cell culture (SILAC). SILAC-based proteomics studies of virus infection have been used in studies of virus−host cell interactions of several important viruses, including influenza virus,13,14 human respiratory syncytial virus, and adenoviruses.15 However, to the best of our knowledge, no such analysis has been performed for any flavivirus. In this study, SILAC-based subcellular quantitative proteomics was employed to compare the protein profiles of JEVinfected HeLa cells and mock-infected HeLa cells. At 48 h after infection, 158 proteins, or approximately 9.9% of the 1,602 proteins quantified, were up- or down-regulated (cutoff set to 1.5-fold change) in either the nuclear or the cytoplasmic fractions. Western blot and confocal microscopy were performed to further investigate selected proteins and provide additional evidence validating the MS-based quantification results. Bioinformatic analysis revealed that the regulated proteins were enriched in several biological systems or processes, including the immune response process, the ubiquitin−proteasome system, the intracellular membrane system, and lipid metabolism. STRING analysis was used to create JEV-regulated host response networks consisting of regulated proteins. Protein functional studies identified IFITM3, RANBP2, SAMD9, and VAMP8 as potential antiviral factors with roles in JEV infection.

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The cell pellets were washed with PBS and resuspended in prechilled subcellular fractionation Buffer A (10 mM Tris-HCl, pH 7.4, 5 mM MgCl2, 10 mM NaCl, 1 mM DTT, proteinase inhibitor cocktail (Roche)) and incubated at 4 °C for 15 min. Then, subcellular fractionation Buffer B (10 mM Tris-HCl, pH 7.4, 5 mM MgCl2, 10 mM NaCl, 1 mM DTT, proteinase inhibitor cocktail, 10% NP-40) was added, and the mixture was vortexed and centrifuged at 500g for 5 min. The supernatant, containing predominantly cytoplasmic proteins, was collected. The pellet was resuspended in subcellular fractionation Buffer C (20 mM HEPES-OH, pH 7.9, 1.5 mM MgCl2, 0.5 M NaCl, 1 mM DTT, 0.2 mM EDTA, 20% (v/v) glycerol, proteinase inhibitor cocktail), incubated at 4 °C for 15 min, and centrifuged at 13,200g for 15 min, and the supernatant, containing predominantly nuclear proteins, was collected. In-Solution Digestion and Peptide Separation

Proteins from the cytoplasmic or nuclear fractions were precipitated by mixing with 50% acetone/50% methanol/ 0.1% acetic acid and centrifuging at 2,000g for 20 min. Pellets were resuspended in a buffer containing 8 M urea, 4 mM CaCl2, and 0.2 M Tris-HCl, pH 8.0, reduced with 10 mM DTT at 50 °C for 30 min and alkylated with 40 mM iodoacetamide in the dark for 30 min. The protein concentrations were measured using the Bradford assay, and then the proteins were digested with trypsin at a ratio of 1:50 (trypsin/protein w/w) overnight. The digested peptides were desalted using a SepPak C18 cartridge (Waters) and dried using a Speed Vac. Desalted peptides were fractionated using strong cation exchange chromatography (SCX). SCX separations were performed on a PolySULFOETHYL Aspartamide column (2.1 mm × 50 mm, 5 μm, PolyLC, Columbia, MD) at a flow rate of 0.2 mL/min. SCX Buffer A contained 5 mM KH2PO4 pH 2.7 in 20% acetonitrile/80% ddH2O. SCX Buffer B contained 5 mM KH2PO4 and 0.5 M KCl pH 2.7 in 20% acetonitrile/80% ddH2O. A 60 min gradient elution was performed, and the eluent was collected in 15 fractions. Each fraction was desalted using a ZiptipC18 micropipet tip (Millipore), dried using a SpeedVac, and stored at −80 °C before the LC−MS/MS analysis.

EXPERIMENTAL SECTION

Cell Cultivation and Virus Infection

JEV strains SA 14-14-2 and AT 31 were used. HeLa and BHK21 cells were obtained from the ATCC. BHK-21 cells were cultured in Minimum Essential Medium (MEM). HeLa cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM). Both media were supplemented with 10% fetal bovine serum (FBS, GIBCO) and 1% penicillin/streptomycin (Invitrogen). Cells were maintained at 37 °C in a 5% CO2 atmosphere. DMEM for SILAC was obtained from Thermo Scientific. For the SILAC experiments, HeLa cells were cultured in DMEM containing either 13C- and 15N-labeled arginine and lysine (R10K6, “heavy medium”) or unlabeled arginine and lysine (“light medium”) and supplemented with 10% dialyzed FBS (Thermo) and 1% penicillin/streptomycin. After six population doublings, the HeLa cells in the heavy medium were infected with SA 14-14-2 at a multiplicity of infection (MOI) of 10 for 1 h, washed, and then supplemented with heavy medium; HeLa cells in light medium were mock infected. At 48 h postinfection (hpi), the JEV-infected cells and mock-infected cells were collected from flasks and mixed at a ratio of 1:1. Two biological replicates were performed.

Mass Spectrometry Analysis

All ESI-based LC−MS/MS experiments were performed on a QSTAR Elite instrument (AB Sciex) coupled with an Eksigent Tempo nano MDLC system. The dried peptides were resuspended in 0.2% formic acid/2% acetonitrile, loaded into a precolumn (0.5 mm × 2 mm, MICHROM Bioresources, Inc.) at a flow rate of 5 μL/min, and subsequently eluted from the precolumn over the analytic column (100 μm × 150 mm, 3 μm particle size, 200 Å pore size, MICHROM Bioresources, Inc.) at a flow rate of 300 nL/min in a 130 min gradient. The mobile phase consisted of two components: component A was 2% acetonitrile with 0.1% formic acid, and component B was 98% acetonitrile with 0.1% formic acid. The IDA (informationdependent acquisition) mode was used to acquire MS/MS. After a TOF-MS scan, five multiply charged (from 2 to 5) precursor ions were selected for MS/MS. The precursor ion range was set from m/z 400 to m/z 1800, and the product ion range was set from m/z 50 to m/z 1600. Tandem mass spectra were extracted by Analyst version 2.0. B



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The nuclei of the fixed cells were stained with DAPI. The coverslips were then sealed onto slides and imaged using a PerkinElmer fluorescence microscope.

Protein Identification and Quantification

All MS/MS samples were submitted to Mascot Distiller (version 2.3, Matrix Science) to perform peak picking and extracted ion current-based quantitation. The files generated by Mascot Distiller were searched with Mascot (version 2.2, Matrix Science) against the SwissProt_2011_08 database (selected for Homo sapiens, 20245 entries), assuming trypsin as the enzyme used for digestion. The other parameters were as follows: fragment ion mass tolerance of 0.40 Da; parent ion tolerance of 100 ppm; an iodoacetamide derivative of cysteine as a fixed modification; and the oxidation of methionine and phosphorylation of serine, threonine, and tyrosine as variable modifications. The false discovery rates (FDRs) of peptidespectra matches determined by a decoy database search were 0.7% for the cytoplasmic fraction and 0.2% for the nuclear fraction. Proteins with at least one corrected assigned peptide (with Mascot scores at or above the homology score) were considered to be identified successfully (Supplemental Table 1). For single peptide-identified proteins, the spectrum of the peptide was examined manually (Supplemental Table 2). In each independent biological replicate, the relative quantification of the protein was performed as described in a previous study.16 Briefly, the quantitation processes were as follows: (1) For the 15 LC−MS/MS analyses in each sample group, 15 individual rov files were processed. (2) The 15 quantitation reports were combined (as Microsoft Excel files), and only peptides passing stringent tests (threshold values for fraction, correlation, and standard error set to >0.5, >0.7, and 0.400) were kept for further analysis. The proteins and their interactions were then uploaded to Cytoscape (version 2.6.3) for data visualization. The GO analysis of the regulated proteins based on the biological process was performed using Scaffold (version Scaffold_3.2.0, Proteome Software Inc.). Scaffold uses the GO terms that appear in the NCBI database as part of a protein’s description. To assess the statistical over- or underrepresentation of categories for the regulated proteins relative to all quantified proteins, Fisher’s exact test was used to measure the annotation enrichment of the regulated proteins. The entire set of proteins with quantitative data was set as the background. P-values were corrected for multiple testing using a Bonferroni procedure. Microscopy Image Capture and Cell Counting

The cell images were acquired with a NIKON Digital Sight DSU1 on an OLYMPUS TH4-200. Cells in 24-well plates were digested with trypsin and then counted with a BIO-RAD TC10 automated cell counter. Small Interfering RNAs and Cell Transfection

Predesigned small interfering RNAs (siRNAs) were obtained from GenePharma. RD or HeLa cells were transfected with a target protein-specific siRNA or with a negative control siRNA (Supplemental Table 5). The siRNA was introduced into cells using Lipofectamine RNAiMAX (Invitrogen) in Opti-MEM medium (Invitrogen). The siRNA efficiency was detected by Western blot or quantitative real-time PCR (qRT-PCR) analysis.

Western Blot Analysis

Equal amounts of proteins from each sample were separated on 10% SDS-PAGE gels and transferred to polyvinylidene difluoride (PVDF) membranes (Millipore) by electroblotting. Membranes were blocked with Tris-buffered saline Tween-20 (TBST) buffer containing 5% BSA or 5% nonfat milk and then stained with rabbit anti-IFITM3 polyclonal antibody (Proteintech Group), mouse anti-ACTA2 polyclonal antibody, rabbit anti-GAPDH antibody, rabbit anti-LMNA polyclonal antibody (Santa Cruz Biotechnology), rabbit anti-SUMO2 polyclonal antibody (NewEastBio), rabbit RIG-I (DDX58) polyclonal antibody, or mouse anti-IFIT1 antiserum. The membranes were then washed by TBST and incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies at room temperature for 1 h; the HRP was then detected by enhanced chemiluminescence. The film was visualized, and the band intensities were measured.

PCR and Real-Time PCR Analysis

Total RNA was purified using TRIzol reagent (Invitrogen) according to the manufacturer’s protocol. A 1 μg aliquot of total RNA was subjected to reverse transcription with MMLVRT (Invitrogen). PCR was performed with the Mastercycler pro PCR System (Eppendorf). The PCR products were verified by agarose gel electrophoresis. qRT-PCR was performed on a StepOne Real-Time PCR System (Applied Biosystems) with SYBR qPCR Mix (TOYOBO). All qRT-PCR products were verified by melting curve analyses and agarose gel electrophoresis. All RNA measurements were collected within a reliable range (the Ct values of GAPDH ranged from 15 to 20, while that of JEV ranged from 18 to 26). Plaque Assay

BHK-21 cells were seeded in 12-well plates to form a confluent monolayer overnight at 37 °C in a 5% CO2 incubator. The cell monolayer was inoculated with an appropriate dilution of viral culture supernatant to ensure that the final plaque counts were reliable (always approximately 10−100) and then incubated for 90 min at 37 °C with occasional shaking. After adsorption, the unbound virus was removed, and the cells were washed with PBS. The cells were overlaid with 1 mL solid culture medium

Fluorescence Microscopy Analysis

Cells were plated on glass coverslips, fixed with 4% formaldehyde, permeabilized in 0.3% Triton X-100, and then incubated with the appropriate primary antibody diluted in PBS/5% FBS. After incubation for 4 h at room temperature, the fixed cells were washed with PBS and incubated with Cy3conjugated secondary antibody at room temperature for 1 h. C



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Figure 1. Virus infection. (A) PCR validation of JEV infection in HeLa cells at 48 hpi. HeLa cells were infected with JEV strain SA 14-14-2 at a MOI of 10 or mock infected. HeLa cells were harvested 48 h later, and the intracellular SA14-14-2 mRNA was detected by PCR. (B) qRT-PCR analysis of JEV levels in HeLa cells. HeLa cells were infected with JEV strain SA 14-14-2 at a MOI of 10. The intracellular JEV RNA was extracted and measured by qRT-PCR at different time points. (C) Western blot analysis of cytoplasmic and nuclear fractions from JEV- and mock-infected HeLa cells. Equal amounts of proteins from the cytoplasmic and nuclear fractions were separated by SDS-PAGE and transferred to PVDF membranes. The membranes were then probed with antibody, and the identified bands were visualized. GAPDH and LMNA were used as markers of cytoplasmic and nuclear proteins, respectively.

with mock-infected (control) cells cultured in light media at a 1:1 ratio. The mixed cells were then separated into cytoplasmic and nuclear fractions. The efficiency of the subcellular fractionation was confirmed by Western blot (Figure 1C). The proteins from each fraction were then subjected to trypsin digestion. The resulting peptides were further separated into 15 fractions by SCX and analyzed by RPLC−MS/MS. Two independent biological replicates were performed. Overall, 1,328 and 1,440 host proteins were identified in the nuclear and cytoplasmic fractions, respectively, for a total of 2,185 nonredundant proteins (Supplemental Table 1). In previously reported SILAC-based quantitative protein abundance measurements, ratios between 1.3-fold to 2.0-fold have been used as cut-offs for biological significance.24 Here, we set the cutoff threshold to a 50% change in ratios; that is, JEVto-mock control ratios of >1.5 or 0.400) are presented. (A) Network of regulated proteins from the cytoplasmic fraction. The network includes 48 nodes (proteins) and 81 edges (interactions). (B) Network of regulated proteins from the nuclear fraction. The network includes 29 nodes and 46 edges. ISGs: proteins shown to be regulated by IFN in other studies.

the cytoplasmic fraction (Figure 5A) is clearly much more extensive than the protein network obtained from the nuclear fraction (Figure 5B). This may be because the interactive protein network was largely based on previous studies with proteins of cytoplasmic origin. Interestingly, we found that nearly all highly correlated and network-forming proteins from the cytoplasmic fraction were up-regulated (Figure 5A, in red). Many of these proteins are ISGs (indicated as triangles), which implies a strong immune response. Through the STRING analysis, in addition to previously known viral responsive proteins, we found 35 new regulated proteins in the JEV response network (Figure 5; proteins added to the networks based on our study are shown as squares). Among these 35 proteins, 9 have 4 or more potential connections (edges) with other proteins in the network: EGFR, USB10, ERP29, RPL28, RPS29, RPL4, RPL27, UBE2I, and HSP90B1. Although the roles of these newly added, differentially regulated proteins in host cell response remain to be examined further, the new G



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Figure 6. Influence of the knockdown of selected proteins on JEV infection. (A) HeLa cells were transfected with the indicated siRNAs for 48 h, and cells were then infected with JEV strain SA14-14-2 at a MOI of 10. The intracellular SA14-14-2 mRNA level was analyzed by qRT-PCR at 48 hpi. (B) HeLa cells were transfected with the indicated siRNAs for 48 h, and the cells were then infected with JEV strain SA14-14-2 at a MOI of 10. The supernatants were collected at 72 hpi, and virus titers were measured by plaque assays (The titer for negative control used to normalize other values was 940,000 PFU/mL). (C) HeLa cells were transfected with the indicated siRNAs for 48 h and then infected with JEV strain AT31 at a MOI of 1. The intracellular AT31 mRNA levels were analyzed by qRT-PCR at 46 hpi. C: Mock transfected; NC: negative control siRNA transfected. The relative fold change is normalized to NC. Bars represent the mean ± SD (n = 3). *P < 0.05.

nuclear fraction but was unchanged in the cytoplasmic fraction. SLC38A2 decreased in the cytoplasmic fraction but increased in the nuclear fraction. These proteins might have been identified as unchanged in whole-cell protein analysis. In addition, Western blot and confocal microscopy were used to validate the MS data, and the siRNA knockdown technique was used to characterize the functional effects of the regulated proteins on virus infection. In all, we obtained relative quantitation information for 1,009 proteins in the cytoplasmic fraction and 978 proteins in the nuclear fraction. Among these, 99 and 63 proteins in the cytoplasmic and nuclear fractions, respectively, were identified as being differentially regulated in response to JEV infection. A Q-TOF instrument was used in our study, and we believe that a higher performance instrument (such as a Orbitrap) would have been able to quantify a larger number of proteins, especially for the proteins identified from the cytoplasmic fraction. Through the cross-examination of similar proteomics studies, we found 33 regulated ISGs and 22 regulated proteins (ISGs not included) that were also found as “changed” in other virus-infected cells (Table 1). However, a large fraction of the regulated proteins that we identified in this study were not reported as differentially regulated in other virus-infected cells. Through a cross-examination of previous transcription analysis

viral infection by regulating the virus-triggered induction of type I interferon and cellular antiviral responses.43,44 Our preliminary data show that JEV infection could lead to an increase of IFN-β production (data not shown). Although the knockdown of IFITM3, RANBP2, SAMD9, and VAMP8 was able to reduce JEV production, these did not significantly alter IFN-β production in Sendai virus (SeV)-infected 293 cells (data not shown), indicating that the antiviral functions of these proteins were not mediated by changes in IFN-β production.

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DISCUSSION Proteomics methods have been widely accepted as a systems biology tool that may be used to study virus−host cell interactions.10,45,46 In combination with high-resolution tandem mass spectrometry analysis, SILAC-based quantitative techniques are especially useful for detecting system-wide protein changes in host cells upon virus infection.13,14,35,36,47 In this study, we analyzed JEV-infected HeLa cells using quantitative proteomics. Subcellular fractionation prior to proteomic analysis has proven to be a very useful technique, as this approach not only can significantly reduce sample complexity and therefore increase protein coverage but also allows the monitoring of proteins with multiple cellular locations. For example, the expression level of SUMO2 increased in the H



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Figure 7. Global view of protein regulation in HeLa cells in response to JEV infection. The regulated proteins (Table 1) were grouped into different categories based on their functions or cellular components as annotated by UniProt or the NCBI database. Red and green nodes represent up- and down-regulated proteins, respectively.

infection are consistent with known elements of the flavivirus life cycle.

studies of JEV infection,48,49 we were surprised to find that a very limited set of “changed” proteins was shared between our proteomics data and the mRNA microarray results. Among the 158 proteins that we identified as regulated by JEV infection (Table 1), only 5 (IFITM3, STAT1, OAS3, IFIT1, and Mx1) were observed to be changed in the JEV-infected cells or tissues at the mRNA level, as detected by mRNA microarray. Different host cells or virus strains used may contribute to this discrepancy, but the mRNA and protein-level inconsistencies are well documented as well.50,51 Through Gene Ontology analysis, we discovered that two biological processes were considered over-represented in the up-regulated proteins from the cytoplasmic fraction: the “immune system process” and the “multi-organism process”. Through protein network analysis, we added 35 regulated proteins to the JEV response protein networks, many of which have multiple potential connections within the network (Figure 5). Using siRNA functional analysis, we discovered that RANBP2, SAMD9, and VAMP8 knockdown can cause increases in the level of JEV in HeLa cells. We understand that by no means have we fully extracted all of the biological implications from the current proteomics data, and there are many unanswered questions regarding its mechanism of action. However, our proteomics data have deepened our understanding of the cellular processes involved in JEV infection and provided valuable new protein targets for future studies. To summarize our data and to illustrate the contributions of our data to the understanding of host response to JEV infection, we created a cellular response map (Figure 7). When proteins are sorted and aligned according to their biological functions, we find that many biological processes and protein complexes that are apparently regulated as a result of JEV

Immune Response Process

The recognition of viral components through patternrecognition receptors (PRRs),52 such as the detection of viral components by RIG-I (increased ∼5.8-fold in cytoplasm fraction here), is important for the host immune response to activate the intracellular signaling cascades and to secrete interferon (IFN) during infection. Type I IFN binds to a common IFN-α/β receptor (IFNAR), which initiates a signaling cascade that results in the phosphorylation and nuclear translocation of STAT1 and STAT2 and the induction of the expression of hundreds of interferon-stimulated genes (ISG).42 ISGs are key components of the host innate immune response and serve as the first line of defense against viral infection.53 In our study, 33 ISGs were identified as upregulated (Table 1). Among the ISGs found to be up-regulated here, ISG15, GTPase Mx1, PKR, and OAS3 have been well documented as important antiviral proteins in cells and knockout mice.53 ADAR1 and IFIT1 have been proven to be able to influence the infection of certain viruses in host cells.54,55 ZAP (zinc-finger antiviral protein) specifically inhibited the replication of Moloney murine leukemia virus (MMLV) and Sindbis virus (SIN) by preventing the accumulation of viral RNA in the cytoplasm.56,57 BST2 is a transmembrane and GPI-anchored protein that restricts the release of a number of enveloped viruses, including all retroviruses tested as well as members of the Arenavirus and Filovirus families.58 However, little is known about the antiviral potentials, target specificities, and mechanisms of action of most ISGs.33 Here, using siRNA analysis, we demonstrated that one of the upregulated ISGs, IFITM3 (interferon-induced transmembrane I



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participates in the docking and/or fusion of transport vesicles to the cognate membrane.74 Here, we found that the depletion of VAMP8 can increase JEV infection (Figure 6). Further analysis of VAMP8 will be required to determine how the absence of this protein affects JEV replication. Another member of the synaptobrevin family, VAMP5, was implicated as a factor influencing HCV infection.33

protein 3), can influence JEV production in HeLa cells. IFITM3 belongs to the IFITM family. Although its effect on JEV had not been demonstrated previously, IFITM3 was shown to be a host factor that can inhibit the infectivity of HIV,59 HCV,60 WNV, and influenza A H1N1 virus.60 It was suggested that IFITM3 acted by preventing viral entry to the host cell cytoplasm, and the antiviral activity of IFITM3 was posttranslationally regulated by S-palmitoylation.61 Other related IFTIM family proteins, such as IFITM1 and IFITM2, have also been shown to inhibit HIV-1 virus infection.59 Using siRNA analysis, we also demonstrated that the knockdown of another up-regulated ISG, SAMD9 (sterile alpha motif domain-containing protein 9), could lead to increased JEV infection (Figure 6). SAMD9 was previously shown to be up-regulated in U251MG cells treated with inactivated Sendai virus particles.62 A recent study suggested that SAMD9 might serve as a host innate antiviral factor against poxviruses.38

Lipid Metabolism

A large number of the regulated proteins are involved in metabolism, as indicated by GO analysis (Figure 4). Some of these proteins are related to fatty acid/cholesterol metabolism (Figure 7). A previous study linked the removal or addition of cholesterol with flaviviral entry, RNA uncoating, and replication.75 It has also been reported that WNV modulates host cell cholesterol homeostasis by upregulating cholesterol biosynthesis and redistributing cholesterol to viral replication membranes.76 In this study, we found that four cytoplasmic proteins involved in cholesterol synthesis, namely, DHCR7 (7dehydrocholesterol reductase), ERG25 (methylsterol monooxygenase 1), FDFT (squalene synthase), and HMCS1 (hydroxymethylglutaryl-CoA synthase), were down-regulated. The pharmacological inhibition or RNAi-mediated depletion of DHCR7 can reduce steady-state HCV protein expression and viral genomic RNA expression.77 The downregulation of ERG25 or the inhibition of Erg25p activity with an inhibitor (6-amino-2-n-pentylthiobenzothiazole; APB) leads to a 3- to 5fold reduction in TBSV replication in yeast.78 The inhibition of these two proteins prevented virus infection through the downregulation of cholesterol synthesis. We speculate that the downregulation of proteins involved in cholesterol synthesis here may result in the down-regulation of cholesterol synthesis in host cells and thus inhibit the infection of JEV.

Ubiquitin−Proteasome System

The post-translational attachment of ubiquitin or ubiquitin-like modifiers (such as SUMO) to proteins regulates many cellular processes, including the generation of innate and adaptive immune responses to pathogens.63 Unsurprisingly, many different pathogens have evolved to exploit the cellular UPS system due to its functional flexibility and far-reaching functional downstream consequences.64 A yeast-two-hybridbased “functional yeast array” study of DENV reported that DENV envelope proteins can interact with UPS proteins.65 The regulation of proteins in the ubiquitin−proteasome system after DENV infection was observed using microarray, highthroughput quantitative PCR66 and 2D gel-based proteomics methods.67 In our study, 10 UPS proteins, including SUMO1 (increased ∼1.3-fold), SUMO2, UBC9, RANBP2, UB2 V1, PSME1, PSA7L, PSB3, PRS6A, and USP10, were differentially regulated after JEV infection, indicating a relatively intense influence of JEV on UPS. UBC9 (SUMO-conjugating enzyme UBC9) can interact with DENV,68 and the overexpression of UBC9 reduced DENV plaque formation in mammalian cells.65 RanBP2 is one of the few known SUMO E3 ligases, and it stably interacts with UBC9 throughout the cell cycle.69 In our functional studies, we found that RanBP2 may participate in the host defense system to prevent JEV propagation (Figure 6), suggesting that an anti-UPS strategy may be helpful in preventing JEV propagation.

Other Proteins

We also found that proteins associated with several protein complexes were differentially regulated in response to JEV infection, including proteins belonging to the MHC I complex, ribosomes, and histones (Figure 7).

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CONCLUSIONS

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ASSOCIATED CONTENT

In conclusion, our subcellular quantitative proteomics study provided a global view of host cell protein response during JEV infection. Based on the quantitative protein level regulation data, we selected 8 regulated proteins for functional analysis using siRNA and identified IFITM3, RANBP2, SAMD9, and VAMP8 as potential antiviral factors against JEV infection. This indicated that the combination of quantitative proteomics data and siRNA analysis is a particularly effective approach for identifying functional proteins. Through network analysis, we added 35 new regulated proteins to the viral response network. Further studies of the functions of these proteins in virus−host cell interactions may lead to new strategies for treating encephalitis.

Intracellular Membrane System

Flaviviruses depend on intracellular membrane structures for virus replication.70 Thus, it is not surprising to find that a large number of proteins associated with the intracellular membrane structure were regulated in our study (Figure 7). For example, we identified vesicle-associated membrane protein-associated protein A (VAPA) as increased by ∼1.5-fold in the cytoplasmic fraction of HeLa cells after JEV infection. VAPA is a multifunctional protein that is involved in intracellular transport, including in the regulation of COPI-mediated transport.71 VAPA was previously identified as a factor mediating the formation of the HCV replication complex.72 A recent study suggested that viperin, one of the interaction partners of VAPA, may destabilize HCV RNA replication and further inhibit the infection of HCV.73 In our siRNA experiments, we investigated the effects of SSR4 and VAMP8, two up-regulated membrane proteins, on JEV infection. VAMP8 is a synaptobrevin family protein and

S Supporting Information *

Supplemental figures and tables. This material is available free of charge via the Internet at http://pubs.acs.org. J



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AUTHOR INFORMATION

Corresponding Author

*(L.G.) Tel: +86-27-68753800. Fax: +86-27-68753797. E-mail: [email protected]. (G.X.) Tel: +86-27-87198685. Fax: +86-2787198685. E-mail: [email protected]. Author Contributions ⊥

These authors contributed equally to this work.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Yong Zhao for technical help with mass spectrometry analysis. This work was supported by grants from the Ministry of Science and Technology of China (nos. 2013CB911102, 2010CB530100), the National Science Foundation of China (no. 31221061), and the 111 Project of China (B06018). The mass spectrometry analysis was supported by a shared instrument fund from Wuhan University.

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