Arch Virol (2015) 160:173–182 DOI 10.1007/s00705-014-2249-2

ORIGINAL ARTICLE

Prediction of signaling pathways involved in enterovirus 71 infection by algorithm analysis based on miRNA profiles and their target genes Liang Bian • Yan Wang • Qingqing Liu Jufeng Xia • Jian-Er Long

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Received: 25 May 2014 / Accepted: 29 September 2014 / Published online: 7 October 2014 Ó Springer-Verlag Wien 2014

Abstract Enterovirus 71 (EV71) causes major outbreaks of hand, foot, and mouth disease. Host factors and signaling pathways exhibit important functions in the EV71 life cycle. We conducted algorithm analysis based on miRNA profiles and their target genes to identify the miRNAs and downstream signaling pathways involved in EV71 infection. The miRNA profiles of human rhabdomyosarcoma cells treated with interferon (IFN-)-a or IFN-c were compared with those of cells infected with EV71. Genes targeted by differentially expressed miRNAs were identified and assigned to different signaling pathways according to public databases. The results showed that host miRNAs specifically responded to the viral infection and IFN treatment. Some miRNAs, including miR-124 and miR491-3p, were regulated in opposite manners by the IFNs and EV71. Some signaling pathways regulated by both EV71 infection and IFN treatment were also predicted. These pathways included axon guidance, Wingless/Int1 (Wnt) signaling cascade, platelet-derived growth factor receptor (PDGFR)/PDGF, phosphatidylinositol 3-kinase (PI3K), Jun N-terminal kinase (JNK)/mitogen-activated

Electronic supplementary material The online version of this article (doi:10.1007/s00705-014-2249-2) contains supplementary material, which is available to authorized users. L. Bian  Y. Wang  Q. Liu  J.-E. Long (&) Laboratory of Medical Microbiology, Department of Medical Microbiology and Parasitology, Shanghai Medical College of Fudan University, 138 Yixueyuan Road, Shanghai 200032, China e-mail: [email protected] J. Xia  J.-E. Long Key Laboratory of Medical Molecular Virology of Ministries of Education and Health, Shanghai Medical College of Fudan University, Shanghai 200032, China

protein kinase (MAPK), transforming growth factor-beta receptor (TGF-bR)/TGF-b, SMAD2/3, insulin/insulin-like growth factor (IGF), bone morphogenetic protein (BMP), CDC42, ERB1, hepatocyte growth factor receptor (c-Met), eukaryotic translation initiation factor 4E (eIF4E), protein kinase A (PKA), and IFN-c pathways. The identified miRNA and downstream signaling pathways would help to elucidate the interaction between the virus and the host. The genomics method using algorithm analysis also provided a new way to investigate the host factors and signaling pathways critical for viral replication.

Introduction Enterovirus 71 (EV71) causes major outbreaks of hand, foot, and mouth disease (HFMD), which usually affects young children [1]. This virus also causes various severe neurological complications that can lead to death [2, 3]. EV71 is a single, positive-strand RNA virus belonging to the species Enterovirus A, genus Enterovirus, family Picornaviridae. The increased prevalence of HFMD in China over the last several years has made the prevention and therapy of this disease a critical issue [4, 5]. Currently, no effective vaccine or specific antiviral agent is available to prevent or treat EV71 infection [6, 7]. This situation has prompted intense basic research on the interaction between EV71 and its host. EV71-infection-induced cytokine storm and apoptotic cell death are possibly correlated with neuropathogenesis [1, 2, 8]. However, little is known about the molecular mechanisms underlying the virus-induced illness. Several signaling pathways are reportedly crucial for viral replication, virus-induced cellular apoptosis, and pro-inflammatory

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cytokine production [9–17]. Identifying the crucial signal cascades in viral infection and the host immune response is challenging because numerous signaling pathways are involved in the virus-host interaction. Genomics methods combined with algorithm analysis may help in this identification. However, identifying the important signaling pathways by merely comparing the expression levels of genes and proteins after EV71 infection using cDNA microarrays or 2-D gel electrophoresis is difficult because of the interference of thousands of irrelevant genes [18–21]. Recent studies have demonstrated that miRNAs are important regulators of viral life cycles. miRNAs are 19- to 25-nt non-coding RNAs that post-transcriptionally regulate gene expression by binding to target mRNA in 30 untranslated regions. To date, more than 1000 miRNAs have been identified in humans, and over 60 % of all human protein-coding genes are targeted by miRNAs according to computational prediction [22, 23]. miRNAs are also involved in the replication of enteroviruses [24– 30]. There are considerably fewer human miRNAs than protein-encoding genes. A single miRNA can potentially target numerous different transcripts, and a transcript can be targeted by numerous miRNAs [22, 23]. The host response to viral infection is subjected to effective, efficient, and economical regulation. Thus, algorithm analysis of miRNAs and their target genes can be used to predict important signaling pathways involved in viral infection. Interferon (IFN)-a shows antiviral activity against EV71 [31–33], whereas EV71 inhibits host immune responses and induces cellular apoptosis [8–10, 34–36]. Hence, the miRNAs and downstream signaling pathways regulated by EV71 or IFNs are more likely to be involved in EV71 replication. In the present study, human rhabdomyosarcoma (RD) cells were treated with IFN-a and IFN-c to explore potential host factors and antiviral signaling pathways involved in EV71 infection. MiRNAs were detected by miRNA qPCR array, and the miRNA profiles of cells treated with IFN-a and IFN-c were compared with those of cells infected with EV71. Genes targeted by differentially expressed miRNAs were identified by algorithm analysis and assigned to different signaling pathways.

Materials and methods Viral infection and TCID50 assay The EV71 strain (GenBank accession no. HQ891927) used in this study was isolated from an HFMD patient as described in our previous report [37]. Written informed consent was obtained from the patient’s parents. This work was approved by the Ethics Committee of Fudan

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University, China. To determine the virus titer (TCID50), RD cells were seeded at 2 9 104/well in 96-well plates and incubated at 37 °C for 24 h in DMEM/F12 medium supplemented with 10 % fetal bovine serum (FBS). Then, 100 ll of serially diluted virus was added to infect the cells for 2 h. After removal of the virus, the medium was replaced with fresh medium, and the cells were incubated for another 72 h. The cells were stained with 10 ll of methylthiazolyldiphenyl-tetrazolium bromide (MTT) for 4 h and lysed with 200 ll of dimethylsulfoxide (DMSO) at 37 °C for 15 min. Absorbance was measured using an optical density (OD) reader at 570 nm. Instead of conventional observation under a microscope to detect a cytopathic effect (CPE), virus-induced CPE was expressed as (1 - ODvirus-infected/ODcell control) 9 100 %. The CPE induced by viruses correlated inversely with the OD value after MTT staining, because MTT can be reduced to purple formazan in living cells. Consequently, the OD value could indicate the course of viral infection and cellular pathogenesis. TCID50 was calculated according to the BehrensKa¨rber method: log TCID50 = L - d(S - 0.5), where L is the log value at the lowest dilution, d is the log value of the serial dilution factor, and S is the total value of accumulated CPE. Each sample was detected at least three times and expressed as mean ± SD. Determination of the effects of IFNs on EV71 infection To determine the efficacy of IFN in protecting RD cells against EV71, cells were seeded at 2 9 104/well in 96-well plates and then cultured for 24 h. Subsequently, the cells were treated with IFN-a (IFN-a-2a) or IFN-c (ProSpecTany TechnoGene Ltd., Israel) for another 6 h at the indicated concentrations. IFNs were serially diluted fivefold starting from 2 9 104 IU/ml because concentrations higher than 2 9 104 IU/ml would result in loss of cell viability (data not shown). The cells were infected with EV71 at a multiplicity of infection (MOI) of 100 TCID50 in a volume of 100 ll. After 48 h of incubation, MTT and DMSO were added sequentially as described above. The absorbance values of the cells were determined at 570 nm. Cells not treated with IFN but infected with EV71 were used as the virus control, and mock-treated cells were used as the cell control. Based on the results obtained using IFN-treated cells at different concentrations, RD cells were treated with IFN-a or IFN-c at 160 IU/ml for another 6 h after seeding at 2 9 106 in a 25-cm2 flask for 24 h and grown to 70 % to 80 % confluence. The RD cells were subsequently infected with EV71 at an MOI of 104 TCID50 in a volume of 500 ll for 2 h. After changing the medium, the time course of virus multiplication was analyzed by collecting the cell culture supernatant at different time points after infection.

miRNA and signaling pathways involved in EV71 infection

Cells not treated with IFNs but infected with EV71 were used as a control. miRNA qPCR array assay RD cells (1 9 107) were seeded in a 75-cm2 flask for 24 h. The cells were divided into four groups. Group 1 was treated with 160 IU of IFN-a per ml for 6 h. Group 2 was treated with 160 IU of IFN-c per ml for 6 h. Group 3 was infected with EV71 at an MOI of 105 TCID50 for 2 h. The medium was replaced with warm fresh medium, and cells were incubated for another 4 h. Group 4 was mocktreated and incubated for 6 h as a cell control. The four cell groups were lysed with 2 ml of Trizol Reagent (Invitrogen, USA). The experiments were repeated three times, and pooled cell lysates were collected for the miRNA qPCR array (full human miRNA Panel I, provided by Exiqon) and standard quantitative real-time PCR assay. MiRNA qPCR array analysis was performed by KangCheng Biotech. Co. Shanghai according to the manufacturer’s instructions. Briefly, RNA was extracted with TRIzol Reagent, and 25 ng of RNA was reverse transcribed at 42 °C for 60 min, followed by heat inactivation of the reverse transcriptase. The cDNA was diluted 80-fold, and PCR was performed in 4 ll of diluted solution using SYBRTM Green Master Mix (Exiqon). After incubation at 95 °C for 10 min, 40 amplification cycles were run at 95 °C for 10 s and 60 °C for 1 min. Fluorescence signals were detected, and Ct values were analyzed using the software supplied with the real-time PCR instrument. The DCt (average Ct - average Ct of housekeeping genes) for the target miRNA gene in each treatment group and the DDCt (DCtgroup 2 - DCtgroup 1) for each gene across two groups were calculated to determine the fold change. In this analysis, the fold change in each gene from groups 1 and 2 was calculated as 2-DDCt. Standard quantitative PCR assay The expression levels of several miRNAs (miR-491-3p, miR-124, miR-204, and miR-122) as determined by qPCR array assay were determined by standard qPCR with heminested primers as described previously [38]. In brief, 1.0 lg of denatured RNA was reverse transcribed using stem-loop RT primers (Table S1) in a total volume of 10 ll. After incubation at 42 °C for 45 min, the M-MLV reverse transcriptase was inactivated. The miRNAs were amplified with specific primers by running the following program: 95 °C for 10 min, followed by 40 cycles of 95 °C for 5 s, and 60 °C for 10 s. Fluorescence signals were acquired by the PCR machine (Applied Biosystems 9700, USA), and Ct values were calculated with the supplied software. 5S rRNA was detected simultaneously as a

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reference control in the standard qPCR assay. Each miRNA was quantified three times, and fold change (IFN-a vs. mock, IFN-c vs. mock, and EV71-infected vs. mock) was expressed as mean ± SD. MiRNA cluster analysis, target identification, and assignment of targets to signaling pathways The miRNA expression data were hierarchically clustered for visualization as a heat map using the Treeview program of Toppcluster (http://toppcluster.cchmc.org/) [39]. The miRNA targets were identified on the web using the software TargetScan Human v6.0 (http://www.targetscan.org/) according to the manufacturer’s instructions. All genes targeted either by EV71- or IFN-regulated miRNAs were included in the signaling pathway analysis program of Toppcluster. The correction methods of Bonferroni and false discovery rate (FDR) were selected (0.05 was the Pvalue cutoff and transformed with the value of -log P; P [ 1.3 is therefore used in the figures to indicate significant difference). The output data were graphed using Microsoft Excel 2007. Statistical analysis Student’s t-test was applied to the two groups of data sets. All statistical analysis was performed using SPSS 11.0 (SPSS, In., Chicago IL). Differences with P \ 0.05 were considered statistically significant.

Results Dose-dependent protection of cells against EV71 infection by IFNs RD cells were treated with various concentrations of IFN-a or IFN-c to evaluate their efficacy in protecting cells against EV71 infection and to identify the antiviral conditions. Treated cells were infected with EV71 and stained with MTT. The OD values of the cells treated with IFN-a or IFN-c from 2 9 104 IU/ml to 160 IU/ml were similar but significantly lower than those of mock-treated cells (Fig. 1A). However, the OD values was significantly higher than those of cells treated with IFN-a and IFN-c at low concentrations (1.28 IU/ml to 32 IU/ml), and much higher than those of the virus control. This finding indicated that IFN-a and IFN-c protected the cells against EV71 infection in a dose-dependent manner but could not completely block virus replication, even at high concentrations. Liu et al. [32] reported that IFN-a elicits significant protective effects against viral infection at low MOI.

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1.28 6.4 32 160 800 IFN-γ

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7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56

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Fig. 1 (A) IFN-a and IFN-c protect RD cells against EV71 infection in a dose-dependent manner. RD cells were seeded in 96-well plates for 24 h and then treated with IFN-a or IFN-c at the indicated concentrations for another 6 h. EV71 was loaded onto the cells and incubated for 48 h. Finally, MTT was added, and the cells were lysed using DMSO. The value of OD570 nm was measured and expressed as mean ± SD. Cells not treated with IFN but infected with the virus were used as a virus control, and mock-treated cells were used as a cell control. **P\0.01. The OD values of the cells treated with the

same IFN at different concentrations were compared. (B) Time course of viral replication in RD cells after IFN-a or IFN-c treatment. RD cells were seeded for 24 h and treated with IFN-a or IFN-c at 160 IU/ ml for another 6 h. The cells were infected with EV71 at a low MOI of 0.005 TCID50/cell. The time course of virus replication was analyzed by collecting the cell culture supernatant at different time points after infection. Cells not treated with IFN but infected with the virus were used as a control

Therefore, in the present study, cells treated with 160 IU of IFN-a or IFN-c per ml were infected with EV71 at a low MOI of 0.005 TCID50/cell. The culture medium was collected at different time points after infection, and virus titers were determined. The results showed that the virus titers reached 105 TCID50/ml after approximately 16, 20, and 24 h in mock-treated, IFN-c-treated, and IFN-a-treated cells, respectively. At 14 hpi, the virus titers (expressed as log TCID50/ml) reached 3.6, 4.3, and 4.9 in IFN-a-treated, IFN-c-treated, and mock-treated cells, respectively (Fig. 1B). At later time points ([30 hpi), the EV71 titers were similar regardless of IFN treatment. These results indicated that IFN-a and IFN-c inhibited EV71 replication. IFN-a showed a slightly higher efficacy than IFN-c in reducing the virus titer at early time points (\24 hpi).

The array data were confirmed using a standard quantitative real-time RT-PCR assay using four representative miRNAs (miR-491-3p, miR-124, miR-204, and miR-122). The fold change in each gene across two groups (IFN-a vs. mock, IFN-c vs. mock, and EV71-infected vs. mock) was calculated. The results of the standard qPCR and miRNA qPCR array showed that miR-491-3p was downregulated by 4.68- and 6.18-fold, respectively, after IFN-a treatment, downregulated by 9.86- and 12.91-fold, respectively, after IFN-c treatment, and upregulated by 4.28- and 5.60-fold, respectively, after EV71 infection, (Fig. 2D). The other three miRNAs also showed similar upregulation or downregulation by the two methods. This finding indicated the consistency between the results obtained using the miRNA qPCR array and standard qPCR for measuring miRNA expression.

Identification of miRNAs involved in the responses to IFN-a treatment, IFN-c treatment, or EV71 infection MiRNAs play important roles in the protection of cells by IFN against viral infection [40]. To identify the specific miRNAs involved in the antiviral activity of IFNs against EV71, the cells were treated with IFN-a or IFN-c. The miRNA expression was analyzed using an miRNA qPCR array. The miRNA profiles of the IFN-a- or IFN-c-treated cells were compared with that of the EV71-infected cells. The results showed that 18 and 22 miRNAs were upregulated and downregulated, respectively, by IFN-a, 16 and 25 miRNAs were upregulated and downregulated, respectively, by IFN-c, and 25 and 22 miRNAs were upregulated and downregulated, respectively, by EV71 (Figs. 2A–C and Tables S2–S4).

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Comparison of cellular miRNA profiles after IFN-a treatment, IFN-c treatment, or EV71 infection The miRNA expression levels of IFN-a-treated, IFN-ctreated, or EV71-infected cells were compared (Tables S5– S7). Some miRNAs (miR-216a, miR-491-3p, miR-129-3p, and miR-124) were downregulated by IFN-a but upregulated by EV71 infection, whereas miR-526b was downregulated by EV71 infection but upregulated by IFN-a (Fig. 2A and Tables S2–S3). Five miRNAs (miR-204, miR-122, miR-491-3p, miR-124, and miR-510) were also regulated by IFN-c treatment and EV71 infection in opposite manners (Fig. 2B, Tables S2, and S4). Two miRNAs (miR-124 and miR-491-3p) were downregulated by IFN-a and IFN-c but upregulated by EV71 infection

miRNA and signaling pathways involved in EV71 infection

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hsa-miR-432,374a, Similarly regulated: 142-3p,144,34c-5p, hsa-miR-205, 204,147b,219-5p,141, 190,193a-3p,122,765, 608,885-5p hsa-miR-518f, 576-3p,142-5p, 525-5p 516b,375,150 hsa-miR-193a-5p, 223,520c-3p,98, 373,371-3p,620,184, 302a, 510,509-3-5p, 623,422a,519d, 548b-3p,202,890

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hsa-miR-195,627, 584,524-3p,617,146a, 346, 371-5p,296-5p, 298,602

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hsa-miR-432,374a, 142-3p,144,34c-5p, 147b, 219-5p,141, 190, 216a,193a-3p, 765, 576-3p,142-5p, 129-3p, 516b,375, 150,608 hsa-miR-193a-5p, 223,520c-3p,526b, 198,373,371-3p,620, 184,302a,509-3-5p, 623,422a,519d,202, 890

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hsa-miR-488,187, 886-3p,499-5p,891a, 129-5p,518a-3p,583, 200c,622,146b-5p

Reversely regulated: hsa-miR-204,122, 491-3p,124 hsa-miR-510

hsa-miR-524-5p, 628-3p,584,617,602, 497,147,346,146a, 298,888,760,371-5p, 524-3p

miR-491-3p miR-122

hsa-miR-195, 627, 216a, 129-3p, 296-5p

Similarly regulated: hsa-miR-205, 886-3p,499-5p, 622,885-5p hsa-miR-518f,584, 524-3p,617,124, 491-3p,146a,525-5p, 346,371-5p, 298, 602 Reversely regulated: No found

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Fig. 2 Host miRNAs specifically responded to IFN-a treatment, IFNc treatment, or EV71 infection. (A) miRNAs that were upregulated or downregulated by EV71 infection and IFN-a treatment. (B) miRNAs that were upregulated or downregulated by EV71 infection and IFN-c treatment. (C) miRNAs that were regulated by both or each IFN. Upregulated and downregulated miRNAs are represented by upward (:) and downward (;) arrows, respectively. Two arrows lined up with the directions represent the regulated directions on the left and right. (D) The miRNA qPCR array data were confirmed by standard qPCR

assay. Four representative miRNAs were quantified after the cells were treated with IFN-a, IFN-c, or EV71. Each miRNA was quantified three times, and fold change was expressed as mean ± SD. ‘‘Standard’’ and ‘‘Array’’ indicated the standard qPCR assay and the miRNA qPCR array assay, respectively. (E) Hierarchical cluster analysis of miRNA profiles regulated by IFN-a treatment, IFN-c treatment, or EV71 infection. The clusters were visualized as a heat map using the Treeview program of Toppcluster

(Figs. 2A and B). Meanwhile, both IFN treatments upregulated miR-205 and miR-886-3p but downregulated miR518f and miR-584 (Fig. 2C and Table S3–S4). Cluster analysis showed that the miRNA profile of IFN-a/mock was closer to that of IFN-c/mock, with a coefficient of 0.62, but farther than that of IFN-a/IFN-c, with a coefficient of 0.23. The miRNA profile of EV71/IFN-a was closer to that of EV71/IFN-c, with a coefficient of 0.52, but farther than that of EV71/mock, with a coefficient of 0.32. The miRNA profiles were significantly classified by the IFN treatments and viral infection, and therefore clustered into two branches (Fig. 2E).

Target gene ontology and signaling pathways involved in the responses to EV71 infection, IFN-a treatment, and IFN-c treatment MiRNAs participate in signaling pathways by regulating the expression of target genes. All miRNAs regulated by IFN-a, IFN-c and EV71 were included to identify their targets using TargetScan (Table S8). All target genes were then grouped and analyzed using Toppcluster. Ontology analysis showed that most miRNA target genes were grouped into protein-binding, DNA-binding, or transcription-related activities in the molecular function category,

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A

GO : Molecular Function

B

GO : Cellular Component

GO:0043169 cation binding

GO:0010843 promoter binding

GO:0008092 cytoskeletal protein binding GO:0046872 metal ion binding GO:0060589 nucleoside-triphosphatase regulator activity GO:0019904 protein domain specific binding GO:0004674 protein serine/threonine kinase activity GO:0003677 DNA binding

GO:0008013 beta-catenin binding GO:0003682 chromatin binding GO:0000988 protein binding transcription factor activity GO:0003702 RNA polymerase II transcription factor activity GO:0005509 calcium ion binding GO:0016564 transcription repressor activity

GO:0008134 transcription factor binding GO:0046983 protein dimerization activity GO:0019899 enzyme binding GO:0003700 sequence-specific DNA binding transcription factor activity

GO:0030528 transcription regulator activity GO:0016563 transcription activator activity GO:0001071 nucleic acid binding transcription factor activity GO:0003712 transcription cofactor activity

GO:0000975 regulatory region DNA binding GO:0016773 phosphotransferase activity, alcohol group as acceptor

GO:0019901 protein kinase binding GO:0019900 kinase binding

GO:0044212 transcription regulatory region DNA binding GO:0001067 regulatory region nucleic acid binding GO:0043565 sequence-specific DNA binding GO:0000989 transcription factor binding transcription factor activity GO:0030695 GTPase regulator activity

GO:0004672 protein kinase activity GO:0005083 small GTPase regulator activity GO:0043167 ion binding GO:0016301 kinase activity

GO:0016023 cytoplasmic membrane-bounded vesicle GO:0045202 synapse GO:0031982 vesicle GO:0005624 membrane fraction GO:0031988 membrane-bounded vesicle GO:0005626 insoluble fraction GO:0019717 synaptosome GO:0012505 endomembrane system GO:0005886 plasma membrane GO:0071944 cell periphery GO:0044431 Golgi apparatus part GO:0030425 dendrite GO:0031981 nuclear lumen GO:0005654 nucleoplasm GO:0031410 cytoplasmic vesicle GO:0031252 cell leading edge GO:0044456 synapse part GO:0043232 intracellular non-membrane-bounded organelle GO:0044459 plasma membrane part GO:0000267 cell fraction GO:0005829 cytosol

GO:0043025 neuronal cell body GO:0005794 Golgi apparatus GO:0014069 postsynaptic density GO:0043233 organelle lumen GO:0044463 cell projection part GO:0030424 axon GO:0030054 cell junction GO:0005856 cytoskeleton GO:0043234 protein complex GO:0043228 non-membrane-bounded organelle GO:0044451 nucleoplasm part GO:0000139 Golgi membrane GO:0043005 neuron projection GO:0031974 membrane-enclosed lumen GO:0030136 clathrin-coated vesicle GO:0042995 cell projection GO:0030135 coated vesicle GO:0005667 transcription factor complex GO:0044428 nuclear part GO:0070013 intracellular organelle lumen

Fig. 3 Gene ontology terms in the molecular function (A) and cellular component (B) categories of predicted targets by EV71regulated miRNAs in RD cells. The miRNA targets were identified

using the software TargetScan Human v6.0. All target genes were then grouped and analyzed by Toppcluster Ontology analysis (logP = 10)

and into cytoplasmic membrane, synapse, and vesiclerelated structures in the cellular component category regulated by IFN-a treatment, IFN-c treatment, and EV71 infection (Fig. 3 and Figs. S1–S2). The target genes were also assigned to signaling pathways, based on the public signaling pathway databases, by Toppcluster. Some signaling pathways, such as the Wnt, adherens junction, and c-Met signaling pathways, were affected by EV71 infection (Fig. 4); the cadherin, Wnt, and colorectal cancer signaling pathways were regulated by IFN-a (Fig. S3); and the SMAD2/3, axon guidance, and insulin receptor signaling pathways were regulated by IFNc (Fig. S4). Some signaling pathways were affected by EV71 infection, IFN-a treatment and IFN-c treatment. These pathways included the axon guidance, nerve growth factor (NGF), tyrosine kinase (TRK) receptor A, Wnt, TGF-b/BMP, insulin/IGF-1/FGF, PDGF/PDGFR, CDC42, ERB1, c-Met (mediated by hepatocyte growth factor receptor), PI3K, and JNK/MAPK signaling pathways. The PKA (protein kinase A) and IFN-c signaling pathways

were also regulated by EV71 infection and IFN treatments. Some signaling pathways involved in cancer were also observed in the regulated pathways (Fig. 4 and Figs. S3–S4).

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Discussion IFN-a inhibits EV71 replication in vitro and in vivo [31– 33]. In the current study, both IFN-a and IFN-c were found to inhibit EV71 replication in a dose-dependent manner (Fig. 1). Cellular miRNAs are also critical host factors for viral replication. Numerous miRNAs that are significantly regulated by viral infection reportedly regulate the virus life cycle [24, 25, 41–43]. Thus, miRNAs regulated by IFNs or EV71 were more likely to participate in the virus life cycle by targeting the downstream genes and signaling pathways. To identify the potential miRNAs and downstream signaling pathways involved in EV71 replication, an miRNA qPCR array assay was performed after the cells

miRNA and signaling pathways involved in EV71 infection

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Wnt signaling pathway Adherens junction Signaling events mediated by Hepatocyte Growth Factor Receptor (c-Met) Genes involved in Signaling by BMP IFN-gamma pathway Genes involved in Signalling by NGF Genes involved in Axon guidance Signaling events mediated by VEGFR1 and VEGFR2 Integrins in angiogenesis Pathways in cancer(hsa05200) PDGF signaling pathway Genes involved in G alpha (12/13) signalling events Role of Calcineurin-dependent NFAT signaling in lymphocytes TGF-beta signaling pathway Neurotrophic factor-mediated Trk receptor signaling EPHB forward signaling Colorectal cancer N-cadherin signaling events PDGFR-alpha signaling pathway Regulation of actin cytoskeleton Insulin signaling pathway Nectin adhesion pathway Genes involved in TRKA signalling from the plasma membrane Genes involved in Membrane Trafficking Focal adhesion CDC42 signaling events Genes involved in Clathrin derived vesicle budding E-cadherin signaling in the nascent adherens junction Angiogenesis Regulation of eIF4e and p70 S6 Kinase Long-term potentiation Genes involved in Semaphorin interactions Genes involved in Golgi Associated Vesicle Biogenesis Signaling events mediated by Stem cell factor receptor (c-Kit) JNK MAPK Pathway Genes involved in Rho GTPase cycle Glioma Protein kinase A (PKA) signaling Melanogenesis S1P1 pathway EGF receptor (ErbB1) signaling pathway S1P3 pathway Ras Pathway Regulation of nuclear SMAD2/3 signaling Phospholipids as signalling intermediaries Genes involved in Nuclear Receptor transcription pathway Signaling events regulated by Ret tyrosine kinase PI3 kinase pathway Differentiation Pathway in PC12 Cells; this is a specific case of PAC1 Receptor Pathway Scatter factor/hepatocyte growth factor signaling Reelin signaling pathway MAPKinase Signaling Pathway

Bonfer. FDR

Sprouty regulation of tyrosine kinase signals N-cadherin signaling events Genes involved in TRKA signalling from the plasma membrane Insulin/IGF pathway-protein kinase B signaling cascade Insulin/IGF pathway-mitogen activated protein kinase kinase/MAP kinase cascade Skeletal muscle hypertrophy is regulated via AKT/mTOR pathway Vitamin C in the Brain Non-small cell lung cancer Genes involved in G alpha (12/13) signalling events Melanoma Neurotrophic factor-mediated Trk receptor signaling Transforming growth factor-beta Smad dependent signaling Genes involved in G1 Phase Genes involved in NCAM1 interactions Genes involved in Transmission across Chemical Synapses Adherens junction ErbB1 downstream signaling Genes involved in Neuroransmitter Receptor Binding And Downstream Transmission In The Postsynaptic Cell CDC42 signaling events Signaling events mediated by Hepatocyte Growth Factor Receptor (c-Met) Prostate cancer Direct p53 effectors Scatter factor/hepatocyte growth factor signaling Regulation of nuclear SMAD2/3 signaling Genes involved in Signaling by PDGF Colorectal cancer Chronic myeloid leukemia FGF signaling pathway Glioma Wnt signaling pathway Genes involved in Signalling by NGF TGF-beta receptor signaling Pathways in cancer(hsa05200) Genes involved in Axon guidance

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P value Fig. 4 Signaling pathways possibly involved in EV71 infection according to EV71-regulated miRNAs and their target genes. All of the target genes regulated by differentially expressed miRNA were identified using TargetScan, and the data were entered and analyzed using the signaling pathway component of Toppcluster (0.05 as cutoff value and transformed with -log P, i.e., expressed as P value [1.3 to

indicate significant difference, and the correction methods of Bonferroni and false discovery rate [FDR] were used). The upper part indicates the downstream signaling pathways of EV71-upregulated miRNAs, and the lower part indicates of the EV71-downregulated miRNAs. A star indicates the common downstream signaling pathways of both EV71-upregulated and downregulated miRNAs

were infected with EV71 or treated with IFN-a and IFN-c. Five miRNAs (miR-216a, miR-491-3p, miR-129-3p, miR124, and miR-526b) were regulated by IFN-a and EV71 in opposite manners (Fig. 2A and Table S5). In addition to miR-124 and miR-491-3p, three other miRNAs (miR-204, miR-122, and miR-510) were also oppositely regulated by IFN-c and EV71 (Fig. 2B and Table S6). These results indicated that these miRNAs had potentially important functions in viral infection. In particular, miR-124 is the most abundant miRNA in the central nervous system, regulating neural development and differentiation [44–46]. miR-124 was upregulated by EV71 infection but downregulated by IFN treatment. This suggests that miR-124 might be involved in EV71-induced neuropathogenesis.

However, the functions of miRNA in viral infection need further investigation. Some miRNAs that have been reported to be involved in EV71 infection, such as miR-141 and miR-548 [24, 29], were also found in this study, whereas some miRNAs, including miR-146a [25], were not found to be regulated significantly. This is not surprising, because the miRNAs were expressed not only in a timedependent manner, but also in a tissue-specific pattern [47– 49]. In two other similar searches using miRNA array assay [50] and deep sequencing analysis [51], miR-146a was not found to be upregulated by EV71. In contrast, miR-146a was downregulated in a neural cell line [50]. Cluster analysis indicated that the cellular miRNA profile after the IFN-a treatment was similar to that after

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IFN-c treatment and different from that associated with viral infection (Fig. 2E). The miRNA profiles were significantly classified by EV71 infection and IFN treatments, indicating that host miRNAs were specifically modified to adapt to viral replication after viral infection or to an antiviral state after IFN treatment. The cellular miRNA profiles after IFN-a and IFN-c treatment were similar but with considerable differences, indicating that the antiviral activities of IFN-a and IFN-c involved different signaling pathways but shared some key components. This result was consistent with earlier findings reviewed by Bonjardim et al. [52]. MiRNAs were deduced to regulate viral infection by targeting genes that are important for viral replication. Accordingly, the target genes regulated by differentially expressed miRNAs were identified (Table S8). Previous reports indicated that EV71 infection changes the expression of some of these genes. Specifically, EV71 infection reportedly downregulates CDK6, eIF4A2, and TGF-a in RD cells [18–20] and upregulates caspase-7, IL-8, and TRAF4 in SF268 cells [21]. An algorithm for assignment of signaling pathways showed that some signaling pathways involved in cell development, apoptosis, and life cycle were significantly modified by viral infection or IFN treatment. These include the Wnt signaling cascade, SMAD2/3, PDGF/PDGFR, IGF/BMP, CDC42, PI3K, JNK/ MAPK, TGF-b, ERB1, c-Met, and eIF4E signaling pathways. The antiviral PKA and IFN-c pathways were also regulated by viral infection and IFN treatment. Generally, when viruses infect host cells, pathogenassociated molecular patterns (PAMPs) are sensed by host pattern recognition receptors (PRRs), resulting in the expression of type I IFNs by activating Toll-like receptor (TLR)-IFN regulatory factor (IRF) 3/7 signaling [53–55]. However, EV71 does not effectively stimulate infected hosts to produce type I IFNs because some important molecules for this signaling are targeted by EV71 protease 2A (2Apro), 3Cpro, and virus-induced host factors [25, 34– 36]. Some molecules related to IFN-producing signaling were also found to be targeted by some miRNAs identified by this study, such as IRAK-1 (targeted by has-miR142-3p), TLR-7 (has-miR-525-5p), IRF1 (has-miR-205), TBK1-binding protein (has-miR-202), and NF-jB repressing factor (has-miR-124) (Table S8). It is possible that the virus inhibited the host IFN-producing signaling and further inhibited the antiviral responses by targeting some pathways such as PKA and IFN-c (Fig. 4). In addition, it might be important for viral replication to control of the cell cycle and biosynthesis at the early stage, since many signaling pathways involved in cell cycle, growth, and apoptosis were found to be significantly regulated by the virus, such as Wnt, PDGF/PDGFR, TGF-b, BMP, IGF, PI3K, SMAD2/3, and eIF4E pathways (Fig. 4).

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The PubMed database (http://www.ncbi.nlm.nih.gov/ pubmed?db=PubMed) was searched to validate the results of algorithm analysis. Pathways that potentially participate in EV71 replication were also partially confirmed by some publications. For example, cyclooxygenase-2 (COX-2) and its metabolite, prostaglandin E2 (PGE2), which are considered the major neurotoxic mediators, are upregulated by EV71 infection via the c-Src/PDGFR/PI3K/Akt/p42/p44 MAPK/AP1 and NF-jB pathways in rat brain astrocytes [12, 13]. EV71-induced COX-2 expression and PGE2 production also stimulate viral replication via the activated c-Src/EGFR/p42/p44 MAPK/CREB signaling pathway in human neuroblastoma SK-N-SH cells [11]. EV71 infection induces an early activation of the PI3K/Akt and MAPK/ ERK signaling pathways, thereby inactivating GSK3b (a downstream target of these pathways) and delaying cellular apoptosis [16]. In the EV71 replication cycle, MEK1, but not MEK2, is crucial in the ERK signaling cascade and is also required to promote viral replication [15]. EV71 has been presumed to disseminate throughout the body of the host through the blood and induce inflammation in vascular smooth muscle cells; this result can be attributed to the capacity of the virus to upregulate VCAM-1 [56]. This process is mediated through the NF-jB transactivation initiated by the activation of the p38, JNK, and PDGFR/ PI3K/Akt pathways after EV71 infection [14]. The signaling pathways predicted by algorithm analysis in this research were also partially confirmed in earlier studies. Thus, the algorithm analysis based on the regulated miRNAs was feasible and provided comprehensive information to elucidate the signaling pathway network in viral replication. However, the algorithm analysis cannot determine which signaling pathway is most important for viral infection. Furthermore, determining the function of these signaling pathways is complicated because EV71 and host IFN systems are interactive. IFNs can inhibit viral infection, and EV71 infection modifies IFN production and its downstream signaling. For example, the IFN-c signaling pathway was activated by EV71 infection in the present study. However, EV71 3C protein reportedly inhibits RIG1-mediated IRF-3 activation and type I IFN response [35]. The protein 2A protease encoded by EV71 can function as an antagonist of IFNs. EV71 also blocks the IFN-mediated phosphorylation of STAT1, STAT2, Jak1, and Tyk2 by reducing IFNAR1 levels [34]. These findings indicate that the signaling pathways are synergistically or antagonistically mediated by IFNs or virus by regulating some important target genes, thereby rendering the cells antiviral or permissive to viral replication. In conclusion, in this study, we conducted algorithm analysis based on miRNA profiles and their target genes to identify the miRNAs and downstream signaling pathways involved in EV71 replication. Both IFN-a and IFN-c

miRNA and signaling pathways involved in EV71 infection

elicited antiviral activity against EV71. Some miRNAs and downstream signaling pathways were regulated by the virus and IFNs, which probably function significantly in EV71 replication. The miRNAs and downstream signaling pathways identified by this algorithm analysis could help elucidate the virus-host interaction. However, their roles in viral infection should be further investigated. Acknowledgments The authors thank Prof. Shuping Tong for numerous revisions and critical comments on the manuscript. This work was supported by the National Science and Technology Major Project on Infectious Diseases (Grant No. 2012ZX10004503-003) and the Shanghai Science and Technology Fund (Grant No. 09411964500). Conflict of interest The authors declare no conflict of interest with respect to this study.

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