Differential Protein Analysis of IPEC-J2 Cells Infected with Porcine

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Differential protein analysis of IPEC-J2 cells infected with porcine epidemic diarrhea virus pandemic and classical strains elucidate the pathogenesis of infection Huixing Lin, Lei Chen, Zhe Ma, and Hongjie Fan J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 15 May 2017 Downloaded from http://pubs.acs.org on May 17, 2017

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Journal of Proteome Research

Differential protein analysis of IPEC-J2 cells infected with porcine epidemic diarrhea virus pandemic and classical strains elucidate the pathogenesis of infection Huixing Lin1, Lei Chen1, Zhe Ma1, Hongjie Fan1,2, * 1 College

of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China

2 Jiangsu

Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases

and Zoonoses, Yangzhou, China * Corresponding author. Tel.: +86 25 84396219. Fax: +86 25 84396219. E-mail address: [email protected] (Hongjie Fan).

ABSTRACT: Porcine epidemic diarrhea (PED) has re-emerged in China in late 2010 and is now become widespread. Accumulated evidence indicates that this large-scale outbreak of diarrhea was caused by variants of the highly virulent porcine epidemic diarrhea virus (PEDV). A pandemic PEDV YC2014 strain (YC2014) was isolated from clinical samples. An iTRAQ-based comparative quantitative proteomic study of IPEC-J2 cells infected with YC2014 and a classical CV777 strain (CV777) was performed to determine the differences between pandemic and classical PEDV strains infection. Totals of 353 and 299 differentially expressed proteins were identified upon YC2014 and CV777 infection, respectively. The canonical pathways and functional networks involved in both PEDV infections were analyzed. The results indicated that the PEDV suppressed protein synthesis of IPEC-J2 cells through down-regulation of the PI3K-AKT/mTOR signaling pathways. Infection with YC2014 could activate the JAK-STAT signaling pathway and the NF-κB pathway more intensively than CV777. YC2014 could activate NF-κB pathway more intensively than CV777. Based on differentially expressed proteins, we propose that PEDV might disrupt apoptosis, and may elicit stronger inflammatory cascades as well. This study might contribute to an understanding of the pathogenesis of PEDV infection, and aid in the development of effective preventive and control vaccines. 1 ACS Paragon Plus Environment


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KEYWORDS: Differential protein expression; Comparative proteomics; Porcine epidemic diarrhea virus; Virulence

INTRODUCTION Porcine epidemic diarrhea virus (PEDV) is the main causative agent of porcine epidemic diarrhea (PED), a devastating enteric disease resulting in tremendous economic losses to the swine industry.(1, 2)

Since December 2010, a large-scale outbreak of severe diarrhea, characterized by watery stool,

dehydration, and vomiting, with 80 to 100% morbidity and 50 to 90% mortality in suckling piglets, has been observed on swine farms in China.(3, 4) Accumulated evidence indicates that this large-scale outbreak of diarrhea may be caused by variants of the highly virulent PEDV.(5, 6) New PED outbreaks have also been reported in the United States, Canada, Vietnam, and Korea.(7-10) Many relevant studies have been conducted and have focused on the viral isolation and molecular epidemiology surveys. The pathogenic mechanism and immune regulation between PEDV and host, as well as the difference between pandemic and classical strains of PEDV infection remain largely unknown. Proteomics techniques are effective tools for characterizing the dynamic interaction between host and pathogen.(11-13) Among the current proteomics methods, isobaric tags for relative and absolute quantitation (iTRAQ) combined with LC–MS/MS analysis is a rapidly emerging quantitative proteomic method with great sensitivity, accuracy, and high throughput for protein identification and quantification.(14-16) In this study, a quantitative proteomics approach based on an iTRAQ combined with LC–MS/MS was used to identify proteins differentially expressed between the PEDV pandemic and classical strains infecting the porcine small intestinal epithelial cell line (IPEC-J2).

MATERIALS AND METHODS Cells and viruses A porcine small intestinal epithelial cell line IPEC-J2 was grown in antibiotic free Dulbecco's modified Eagle's medium (DMEM)/F12 (Gibco), supplemented with 5% foetal bovine serum (Gibco), insulin (5 μg/mL, Gibco), transferrin (5 μg/mL, Gibco), selenium (5 ng/mL, Gibco), and epidermal growth factor (5 ng/mL, Sigma-Aldrich). Cells were maintained in 100 mL flasks at 37 °C in an atmosphere of 5% CO2. The medium was replaced every second day. Upon reaching 90% confluency, cells were routinely passaged 1:2. The PEDV pandemic strain YC2014 (GenBank 2 ACS Paragon Plus Environment

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accession no. KU252649) was isolated from a suckling piglet with acute diarrhea from East China in May 2014. The PEDV classic strain CV777 (GenBank: KT323979.1) was kindly provided by the Jiangsu Academy of Agricultural Sciences. A phylogenetic analysis of these two PEDV strains was constructed based on the complete genomic DNA.

Immunofluorescence analysis (IFA) for the detection of PEDV antigen in IPEC-J2 cells IPEC-J2 cells grown on a 12-well plate were infected with YC2014 or CV777, respectively, at 0.1 multiplicity of infection (MOI). At 24 hours post infection (hpi), the PEDV antigen in IPEC-J2 cells was detected by IFA as previously described.(17)

Kinetics of PEDV multiplication in IPEC-J2 cells IPEC-J2 cells were cultured in 60 mm dishes for approximately 12 h to 90% confluence and washed twice with D-Hanks. After being incubated for 2h with 2.5μg/ml trypsin in serum-free DMEM/F12 medium, the cell monolayers were infected with YC2014 and CV777, respectively, at 0.01 multiplicity of infection (MOI). At 8, 16, 24, 32, 40, and 48 hours post infection (hpi), the virus were released by freezing and thawing of the cell suspension three times. The virus titer for each time point was determined by 50% tissue culture infective dose (TCID50). Each experiment was independently repeated three times and the standard deviation (SD) was calculated.

Protein isolation, labeling with iTRAQ reagents, and LC-MS/MS analysis Confluent monolayers of IPEC-J2 cells were washed twice with D-Hanks. Then, the cells were infected with YC2014 and CV777, respectively, at 0.1 MOI and incubated with serum-free DMEM/F12 containing 2.5 μg/mL trypsin. The YC2014, CV777 or mock (PBS) infected cells were collected at 24 hpi. Each group was processed with three independent biological replicates. The PEDV and mock infected cell samples were collected with a cell scraper, centrifuged at 400 × g for 8 min, and washed twice with ice-cold PBS containing 1 mM sodium fluoride and 1 mM pervanadate. The collected cells were lysed in 400 μL of RIPA lysis buffer containing 1 mM PMSF, and the soluble protein fraction was harvested by centrifugation at 10,000 × g for 15 min at 4 °C. The protein concentration was determined using the BCA Protein Quantitation Kit (Thermo Scientific). After reduction and cysteine-blocking as described in the iTRAQ protocol (AB Sciex, Concord, ON), 3 ACS Paragon Plus Environment


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solutions containing 100 μg protein were digested with sequence grade modified trypsin (Promega, V5111) overnight at 37 °C and then labeled with different iTRAQ tags as follows: iTRAQ 113 (IT113) and iTRAQ 114 (IT114) for the mock-infected samples; iTRAQ 117 (IT117) and iTRAQ 118 (IT118) for CV777 infected samples; and iTRAQ 119 (IT119) and iTRAQ 121 (IT121) for YC2014 infected samples. The labeled samples were then mixed and dried with a rotary vacuum concentrator. The LC-MS/MS analysis was done with the following program. Briefly, the fractionated peptides were analyzed by a Q-Exactive mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) fitted with Thermo Scientific EASY-nLC 1000 System (Thermo Fisher Scientific, Waltham, MA, USA). Source ionization parameters were as follows: spray voltage, 2.1 kV; capillary temperature, 250 °C; and declustering potential, 100 V. The mass spectrometer was operated in a Top 20 data-dependent mode with automatic switching between MS and MS/MS. Full-scan MS mode (350−1800 m/z) was operated at a resolution of 70 000 with automatic gain control (AGC) target of 1 × 106 ions and a maximum ion transfer (IT) of 60 ms. The precursor ions are fragmented by high-energy collisional dissociation (HCD) and subjected to MS/MS scans with the following parameters: resolution, 17 500; AGC, 5 × 106 ions; maximum IT, 70 ms; intensity threshold, 5000; and normalized collision energy, 29%.

Bioinformatics analysis of the IPEC-J2 cell proteome The differentially expressed proteins were assigned into different cellular localizations, molecular functions, and biological processes by searching the Gene Ontology (GO) and Uniprot databases. GO annotation comparison was performed to elucidate the characteristics of all differentially expressed proteins in IPEC-J2 cells induced by YC2014 or CV777 infection, which may be associated with virulence and pathogenicity.

Data analysis Protein identification and quantification steps were performed with the ProteinPilot™ Software (Version: 4.5; Applied Biosystems) using the Paragon™ algorithm as the searching engine. MS/MS data were searched against the Sus scrofa Uniprot database (http://www.uniprot.org, Version: UniProt_Sus scrofa_201508.fasta). The cysteine alkylation by methyl methanethiosulfonate and biological modifications in the algorithm were programmed into the search parameters. The protein 4 ACS Paragon Plus Environment

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confidence threshold cutoff was set to 1.30 (not include) to assume at least two peptides with 95% confidence interval, and all identified proteins were above 95% confidence. In addition, false discovery rate (FDR) analysis was applied for the identification of proteins by searching against a concatenated reversed database. The parameters for database searching were as following: trypsin was selected as the enzyme; two missed cleavages were allowed at maximum; precursor mass tolerance was set to 15 ppm; fragment mass tolerance was set to 20 mmu; carbamidomethylation of cysteine was set as fixed modification; methionine oxidation and iTRAQ labels at the N-termini and at lysine side chains were allowed as dynamic modification. Strict maximum parsimony principle was applied and only peptide spectrum matches (PSMs) with high or medium confidence and with delta Cn better than 0.15 were considered for protein grouping. Ion peaks were integrated based on the most confident centroid with 20 ppm tolerance. The peptide for quantification was automatically selected by Paragon™ algorithm to calculate the reporter peak area, error factor (EF) and P value. Proteins with fold change > 1.30 or < 0.77 and a P value < 0.05 were considered to have significant differential expressions. Auto bias-corrections were executed to decrease the artificial error.

Validation of protein quantification by western blot The PEDV- and mock-infected cells were collected at 24 hpi. Equivalent amounts of cell lysates from each sample were collected. The protein quantification was validated by western blot with the primary antibodies for ferritin (sc14420), Hsp beta-1 (sc9012), phospho-p70S6K (sc7984), STAT1 (sc346), PKC delta (sc937) and β-actin (sc47778) purchased from Santa Cruz Biotechnology, Inc. as previously described.(18)

RESULTS AND DISCUSSION Phylogenetic analysis and kinetics of PEDV multiplication in IPEC-J2 cells Phylogenetic analysis of the YC2014 and CV777 was constructed based on the complete genomic DNA and was depicted in Fig. 1A. The YC2014 was clustered with the PEDV epidemic strains (G2 cluster), with >99 % nucleotide identity to these strains, whereas the CV777 was clustered with the PEDV classic strains (G1 cluster). To determine the kinetics of the PEDV propagation in the IPEC-J2 cells, CPEs and viral titers were monitored after infection (Fig. 1B and 1C). At 24 hpi, the CPEs caused by YC2014 or CV777 showed vacuolation, formation of syncytia, and fusion of cells (Fig. 5 ACS Paragon Plus Environment


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1B). The result of IFA indicated that most of the IPEC-J2 cells were infected with PEDV at 24 hpi. According to the PEDV growth curve in IPEC-J2 cells, both of these two strains peaked at 32 hpi, and then gradually declined (Fig. 1C).

Protein profile by iTRAQ combined with the LC–MS/MS analysis In total, 2384 and 2379 proteins were identified and quantified by the iTRAQ coupled with the LC–MS/MS analysis in the IPEC-J2 cells infected with YC2014 and CV777, respectively. In all, 218 proteins were significantly up-regulated and 135 proteins were markedly down-regulated in cells infected with YC2014 compared with the PBS-treated cells. Meanwhile, 197 up-regulated and 102 down-regulated proteins were identified in cells infected with CV777 compared with the PBS-treated cells.

Bioinformatics analysis of the IPEC-J2 cell proteome For cellular localizations annotation, proteins in both viruses-infected cells were mainly involved in the cytoplasmic part, organelle and cytoplasm. A comparison of the molecular function indicated that RNA binding accounted for large proportions in both YC2014 and CV777 infection. For biological process annotation, proteins in both groups were mainly involved in cellular response to type I interferon, cytokine stimulus, interferon-gamma, and innate immune response (Fig. 2). Because the porcine genome database was poorly annotated and many proteins were unassigned or uncharacterized as compared to the human genome, gene identifications of the differentially expressed proteins were converted to human protein gi numbers, followed by uploading into the MetaCore tool. To investigate the underlying biologically functional differences that may be related to viral infection, three strongly represented networks were depicted by the MetaCore tool. For YC2014 infection, the three networks were (1) Development; Angiotensin signaling via STATs (Fig. 3A); (2) Immune response; Antiviral actions of Interferons (Fig. 3B); (3) Immune response; IFN α-β signaling pathway (Fig. 3C). Another three representative networks existed in IPEC-J2 cells infected with CV777 were (1) Apoptosis and survival; Granzyme A signaling (Fig. 3D); (2) Immune response; Antiviral actions of Interferons (Fig. 3E); (3) Immune response; IFN α-β signaling pathway (Fig. 3F). Among the proteins present in the analysis of these networks, the up-regulated proteins are shown in shades of red and the down-regulated ones are in blue. 6 ACS Paragon Plus Environment

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PEDV infection induces the disruption of signaling pathways networks Protein clusters with functions such as cellular growth and proliferation, immune regulation, apoptosis, inflammation and cancer-related signaling were constructed by MetaCore (6.24.67895, Thomson Reuters, New York, USA) (Fig. 4), including the PI3K/AKT/mTOR signaling pathway, JAK/STAT signaling pathway, P53 signaling pathway, and NF-κB signaling pathway.

Validation of protein quantification by western blot assay To confirm the differential expression of cellular proteomes following PEDV infection, four proteins (ferritin, Hsp beta-1, STAT1, and PKC delta) based on different ratios were selected to be analyzed by western blot (Fig. 5). The western blot results of the verified proteins were in accordance with the proteomic results.

PEDV infection induces the disruption of cellular protein synthesis and apoptosis Some viruses suppressed the host protein synthesis machinery to contribute to cell apoptosis and facilitate its propagation

(19, 20)

. To assess the alteration of mTOR signaling during PEDV

multiplication, the total expression and phosphorylation profiles of mTOR, and p70S6K were analyzed by western blot. As shown in Fig. 6, the phosphorylation level of mTOR was decreased, followed by the reduced expression of phosphorylated p70S6K, which is mediated by YC2014 infection but not by CV777. Furthermore, this result was in agreement with the proteomic data acquired using iTRAQ labeled LC–MS/MS approach. The phosphorylation P53-dependent apoptosis was up-regulated of the classical CV777 infected cells. BAD is a proapoptotic gene in Bcl-2 family, which is Bcl-xl/Bcl-2 associated apoptosis promoter.(21) Apoptosis is regulated by competitive interactions between proapoptotic and antiapoptotic proteins of the Bcl-2 family in many researchs.(22,

23)

In this study, the PEDV

suppressed protein synthesis of IPEC-J2 cells through down-regulating the PI3K-AKT/mTOR signaling pathways (Fig. 4). The BAD associates with the HGF receptor of the pandemic YC2014 infected cells was down-regulated (Fig. 4 and Fig. 6), which implied that an apoptosis inhibition mechanism might exist at pandemic YC2014 infection to achieve a higher virus titer. As shown in Fig. 6 and Fig. 3D, the P53-dependent apoptosis was up-regulated of the classical CV777 infected 7 ACS Paragon Plus Environment


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cells.

PEDV infection induces the disruption of inflammatory and immune regulation responses Many inflammation and immune regulation-related pathways, such as the NF-κB signaling pathway, JAK/STAT signaling pathway, and the IL-6 and IL-8 pathways, were constructed by MetaCore analysis. STAT1 is a key molecule in Th1-type immune response development, which mainly involves in JAK/STAT pathway.(24) In this study, JAK-STAT, and IRF immune regulatory pathways were constructed based on the differentially expressed proteins of the PEDV pandemic and classical strains infected cells (Fig. 3), including the type I IFN signaling pathways. This proteomic data showed that the pandemic YC2014 could activate JAK-STAT signaling pathways more intensively than classical CV777. The cytokine expressions of PEDV- or mock-infected IPEC-J2 cells were examined using quantitative real-time RT-PCR. Briefly, total RNA was extracted from the PEDV-infected IPEC-J2 cells and supernatants using RNAiso plus (Takara). After the RNA was reverse-transcribed to cDNA using oligo dT (Takara) as the primer, quantitative real-time PCR assay was performed as previously described with 10μM of each forward and reverse primer (supplementary table S1).(25) The results showed that the cytokines were increased more significantly after YC2014 infection than after CV777 infection (Fig. 7A). The phosphorylation of p65, the synthesis of DDX60 and ERAP2, and the degradation of IκBα, which was associated with inflammatory responses were detected by immunoblotting analysis. The results showed that the phosphorylation of p65 was significantly enhanced, and the synthesis of DDX60 and ERAP2 were significantly increased. Meanwhile, the abundance of IκBα was decreased during YC2014 infection (Fig. 7B). No such obvious findings were presented upon CV777 infection. The results were coincided with the outcomes generated from proteomic analysis. NF-κB pathway plays an important role in regulation of the immune regulation responses and cell survival. Immunoblotting analysis indicated that the NF-κB pathway was more significantly activated after YC2014 infection through the phosphorylation of p65, the synthesis of DDX60 and ERAP2, and the degradation of IκBα, while moderately activated after CV777 infection. The more dramatically activation of NF-κB signaling in pandemic PEDV strain infected cells might be due to the characteristics of pathogenicity (as shown in Fig. 1C), as well as stronger replication capability of 8 ACS Paragon Plus Environment

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pandemic strain than that by the classical strain.

CONCLUSIONS This study explored proteome wide profiles of IPEC-J2 cells individually infected by the pandemic and classical strains of PEDV using iTRAQ coupled with the LC–MS/MS approach. This proteomic analysis based on these differentially expressed proteins might lay the foundation for in-depth studies to elucidate the different pathogenesis and host responses to pandemic and classical PEDV infections.

SUPPORTING INFORMATION: The following files are available free of charge at ACS website http://pubs.acs.org: Table S1. The primers for the quantitative real-time PCR assay of cytokines expressed by PEDVor mock-infected IPEC-J2 cells. Data S1. Information for each significantly altered host proteins identified in PEDV strains YC2014 andCV777 infection.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]. Phone: 86-25-84396219. Fax: 86-25-84396219. Notes The authors declare no competing financial interest.

ACKNOWLEDGMENTS This study was supported by the National Transgenic Major Program (2014ZX0800946B), Special Fund for Agro-scientific Research in the Public Interest (201403054), the Jiangsu Agriculture Science and Technology Innovation Fund (CX(15)1056) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).

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Captions to illustrations Figure 1. Phylogenetic analysis and virus infection. (A) Phylogenetic trees of PEDV based on the complete genomic DNA. (B) PEDV replication in IPEC-J2 cells. (C) One-step growth curve of PEDV strains YC2014 and CV777 in IPEC-J2 cells. Figure 2. The Gene Ontology (GO) categories of the differentially expressed proteins. Figure 3. Ingenuity Pathway Analysis of proteins significantly altered in IPEC-J2 cells. (A, B, C) Upon PEDV pandemic strain YC2014 infection. (D, E, F) Upon PEDV classical strain CV777 infection. Red, up-regulated proteins; blue, down-regulated proteins. The shapes are indicative of the molecular class.

Figure 4. Specific network analysis of proteins significantly altered in PEDV

infected IPEC-J2 cells. (A, B, C) With pandemic strain YC2014. (D, E, F) With classical strain CV777. Red, up-regulated proteins; blue, down-regulated proteins. The shapes are indicative of the molecular class. Figure 5. Validation of protein quantification by western blot assay. β-actin was used as a control. The iTRAQ ratio (YC2014/mock; CV777/mock) obtained by MS analysis are shown on the right. Figure 6. Confirmation of apoptosis disruption in IPEC-J2 cells upon PEDV infection by western blot assay. β-actin was used as a control. Figure 7. Confirmation of inflammatory and immune dysregulation in IPEC-J2 cells upon PEDV infection with real-time RT-PCR or immunoblotting analysis. (A) Real-time RT-PCR analysis of 11 ACS Paragon Plus Environment


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cytokine expressions in IPEC-J2 cells infected or mock-infected with PEDV at 0.1 MOI. The cells were collected at 24 hpi for real-time RT-PCR to analyze the relative expression of the specified cytokines mRNA. (B) PEDV infection induced the phosphorylation of p65, the synthesis of DDX60 and ERAP2, and the degradation of IκBα. IPEC-J2 cells were infected with PEDV strain YC2014 or CV777 at 0.1 MOI and harvested at 24 h pi for immunoblotting. β-actin was used as a control.

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ACS Paragon Plus Environment


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Differential Protein Analysis of IPEC-J2 Cells Infected with Porcine

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