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. 2019 Mar 4;10:160. doi: 10.3389/fimmu.2019.00160

The Megalocytivirus RBIV Induces Apoptosis and MHC Class I Presentation in Rock Bream (Oplegnathus fasciatus) Red Blood Cells

Myung-Hwa Jung 1, Verónica Chico 2, Sergio Ciordia 3, Maria Carmen Mena 3, Sung-Ju Jung 1, Maria Del Mar Ortega-Villaizan 2,*
PMCID: PMC6410659  PMID: 30886611

Abstract

Rock bream iridovirus (RBIV) causes severe mass mortality in Korean rock bream (Oplegnathus fasciatus) populations. To date, immune defense mechanisms of rock bream against RBIV are unclear. While red blood cells (RBCs) are known to be involved in the immune response against viral infections, the participation of rock bream RBCs in the immune response against RBIV has not been studied yet. In this study, we examined induction of the immune response in rock bream RBCs after RBIV infection. Each fish was injected with RBIV, and virus copy number in RBCs gradually increased from 4 days post-infection (dpi), peaking at 10 dpi. A total of 318 proteins were significantly regulated in RBCs from RBIV-infected individuals, 183 proteins were upregulated and 135 proteins were downregulated. Differentially upregulated proteins included those involved in cellular amino acid metabolic processes, cellular detoxification, snRNP assembly, and the spliceosome. Remarkably, the MHC class I-related protein pathway was upregulated during RBIV infection. Simultaneously, the regulation of apoptosis-related proteins, including caspase-6 (CASP6), caspase-9 (CASP9), Fas cell surface death receptor (FAS), desmoplakin (DSP), and p21 (RAC1)-activated kinase 2 (PAK2) changed with RBIV infection. Interestingly, the expression of genes within the ISG15 antiviral mechanism-related pathway, including filamin B (FLNB), interferon regulatory factor 3 (IRF3), nucleoporin 35 (NUP35), tripartite motif-containing 25 (TRIM25), and karyopherin subunit alpha 3 (KPNA3) were downregulated in RBCs from RBIV-infected individuals. Overall, these findings contribute to the understanding of RBIV pathogenesis and host interaction.

Keywords: rock bream, RBIV, red blood cells, erythrocyte, proteome, MHC class I, apoptosis, ISG15

Introduction

Rock bream iridovirus (RBIV) is a dsDNA virus that belongs to family Iridoviridae, genus Megalocytivirus (1). This virus causes severe mass mortality in Korean rock bream (Oplegnathus fasciatus) populations. RBIV was first reported in the summer of 1998 in southern coastal areas of Korea (2). Since then, high mortality resulting from RBIV occurs every year, causing important economic losses in rock bream aquaculture. RBIV is known to cause strong pathogenicity in rock bream individuals (3–7). To date, the immune response of rock bream with RBIV infection remains unclear, although it represents an important aquaculture health concern. Therefore, it is necessary to further detail the immune response mechanisms underlying the RBIV infection process in rock bream. Over the years, a considerable number of studies have investigated the immune response of rock bream at both physiological and molecular levels by transcriptomic and microarray analyses (8, 9). Recently, an increasing number of studies have been focused on the transcriptional immune responses of rock bream against RBIV (10–15). However, most have focused on kidney-mediated immune responses to determine the pathways responsible for fish mortality or survivability. Therefore, evaluation of the immune response or immune defense mechanisms in different organs is useful for the understanding host-RBIV interactions.

In contrast to mammalian red blood cells (RBCs) or erythrocytes, which lack a cell nucleus and organelles (16), nonmammalian RBCs are nucleated and contain organelles in their cytoplasm (17). Although the main physiological role for RBCs is the transportation of respiratory gases, their role in the antiviral response has recently been uncovered (18). Importantly, teleost RBCs can induce toll-like receptor (TLR) and peptidoglycan recognition protein (PGRP) receptor families (19), pathogen presentation to macrophages (20), and cytokine or interferon production (21–25). In addition, transcriptomic and proteomic studies of rainbow trout (Oncorhynchus mykiss) showed that nucleated RBCs contribute to several immune functions such as antigen presentation, leukocyte activation or immune cytokine production (26, 27).

To date, the impact of RBIV on rock bream RBCs in the global fish immune response has not been studied yet. In the present study, we aimed to investigate the differentially expressed proteins (DEPs) in rock bream RBCs upon RBIV in vivo infection in order to understand the molecular contribution of this cell type in the fish immune response against RBIV infection. Proteomic profiling of RBCs from RBIV-infected fish revealed upregulation of apoptosis, antigen processing, and presentation of peptide antigen via MHC class I (MHC-I) pathways. However, the ISG15 antiviral mechanism pathway appeared to be downregulated.

Materials and Methods

Isolation of RBIV

RBIV was obtained from naturally infected rock bream individuals as previously described (11). RBIV major capsid protein (MCP) gene copy number was quantified from supernatant preparations by quantitative real-time polymerase chain reaction (RT-qPCR). Virus titer was calculated as 1.1 × 107/100 μL MCP gene copies. Although some studies have demonstrated the use of cell lines to culture Megalocytivirus (28, 29), RBIV does not replicate well in in vitro cell culture conditions, so the TCID50 method was not used in this study.

Quantification of RBIV Viral Copy Number

RBIV-free rock bream individuals were obtained from a local farm. Thirty fish (11.2 ± 1.2 cm, 28.1 ± 3.2 g) were maintained at 23°C in an aquarium containing 250 L of UV-treated seawater. Fish were injected intraperitoneally (i.p.) with RBIV (100 μL/fish, 1.1 × 107 MCP gene copies) or phosphate-buffered saline (PBS) (100 μL/fish) as a control. Blood (200 μL/fish) and organs (spleen, kidney, and liver) were collected from RBIV-infected rock bream individuals at 1, 2, 4, 7, and 10 days post infection (dpi) (4 fish per time point). RBCs were isolated from blood (100 μL/fish) and purified by 2 consecutive density gradient centrifugations (7,206 g, Ficoll 1.007, Sigma-Aldrich). For RBIV copy number analysis, genomic DNA was isolated from the RBCs, blood, spleen, kidney, and liver of each fish using High Pure PCR Template Preparation Kit (Roche) following standard protocol. A standard curve was generated to determine RBIV MCP gene copy number by RT-qPCR as described previously (11). Virus copy number was determined from 100 μL of total genomic DNA. Statistical analyses were performed using GraphPad Prism software version 5.0 (GraphPad Software, USA). One-way analysis of variance (ANOVA) was performed between conditions, with Tukey's multiple comparison test. P < 0.05 were considered to indicate statistical significance.

Experimental Infection for RBC Proteomic Analysis

Fish (11.0 ± 0.8 cm, 29.3 ± 4.7 g) were randomly divided into two groups (20 fish per group): a virus-injected group and a PBS-injected group. The experimental group was injected i.p. with RBIV (100 μL/fish) containing 1.1 × 107 MCP gene copies, and the control group was injected i.p. with PBS (100 μL/fish). Each group of fish were maintained at 23°C in the aquarium containing 250 L of UV-treated seawater. Blood (100 μL/fish) was collected from 8 fish at 7 dpi. Then, RBCs were purified by 2 consecutive density gradient centrifugations (7,206 g, Ficoll 1.007, Sigma-Aldrich). All rock bream experiments were carried out in strict accordance with the recommendations of the Institutional Animal Care and Use Committee of Chonnam National University (permit number: CNU IACUC-YS-2015-4).

Proteomic Analysis

Ficoll-purified RBCs from 5 fish in each group were pelletized by centrifugation (1,600 rpm). The cell pellet was washed with PBS, digested, cleaned-up/desalted, and pooled for each group (2 control groups and 2 RBIV-infected fish groups). Then, samples were subjected to liquid chromatography and mass spectrometry analysis (LC-MS) as previously described (26), except that the Pierce High pH Reversed-Phase Peptide Fractionation Kit (Thermo Fisher Scientific, Inc.) was used and 3 peptide fractions were collected. Progenesis QI v4.0 (Nonlinear Dynamics, Newcastle, UK) was used for protein differential expression analysis according to “between-subject design.” Log2 peptide ratios followed a normal distribution that was fitted using least squares regression. Mean and standard deviation values were derived from Gaussian fit and were used to estimate P-values and false discovery rates (FDRs). The confidence interval for protein identification was set to ≥95% (P ≤ 0.05). Only proteins having ≥2 quantitated peptides were considered. Peptides with an individual ion score above the 1% FDR threshold were considered correctly identified.

Pathway Enrichment Analysis

DEP pathway enrichment analysis was performed using ClueGO (30), CluePedia (31), and Cytoscape (32). The GO Biological Process, GO Immune Process, Kegg, Reactome, and Wikipathways databases were used. A P ≤ 0.05 and Kappa score of 0.4 were used as threshold values. Proteins were identified by sequence homology with Homo sapiens using Blast2GO version 4.1.9 (33).

Quantitative Real-Time PCR Analysis of Gene Expression

For immune gene expression analysis, total RNA was extracted from RBCs using RNAiso Plus reagent (TaKaRa) following standard protocol. Total RNA was treated with DNase I (TaKaRa) and reverse transcribed using a ReverTra Ace qPCR RT Kit (Toyobo) according to manufacturer's protocol. Real-time PCR was carried out in an Exicycler 96 Real-Time Quantitative Thermal Block (Bioneer) using an AccuPre® 2x Greenstar qPCR Master Mix (Bioneer) as described previously (11). Each assay was performed in duplicate using β-actin genes as the endogenous control. The primers used are listed in Table 1. Relative gene expression was determined by the 2−ΔΔCt method (34). Statistical analyses were performed using GraphPad Prism software. Unpaired T-tests were performed between conditions. P < 0.05 were considered to indicate statistical significance. Data are represented as mean ± standard deviation.

Table 1.

List of primers used.

Name Sequence Accession number
β-actin F CAGGGAGAAGATGACCCAGA R CATAGATGGGCACTGTGTGG FJ975145
MCP F GTGTCTAAAGGGACTGAACATCG R CCCTCAAACGTTACTGGATACTG AY849394
IRF3 F TGGGAGTAACCCTTATGTCCTG R CTTCCTCGTCTGTTCCTTCTTG KF267453.1
MHC class I F AGATTACTGGGAAAAAGGCACA R TCATTCGTTTCATCAGGATGTC KC193602
Fas F GTTTCGTGCGTCGTTTATCA R CAAACCTGCAGCACACAGACA AB619804
Caspase 9 F TCTTGGAGAGACACCCAGTCG R GCCCTTTTGCAGAGTTTTGG KF501038
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Results

RBIV Levels in Rock Bream RBCs

RBIV copy number was quantified in RBC, blood, spleen, kidney, and liver samples. At 2, 4, 7, and 10 dpi, increased viral copy numbers were observed in the spleen, kidney, and liver. The maximum copy number for all samples was reached at 10 dpi (average value of 4.99 × 107 in the spleen, 2.56 × 107 in the kidney, and 2.44 × 107/100 μL in the liver) (Figures 1A–C).

Figure 1.

Figure 1

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RBIV MCP gene copy number in different rock bream organs. Fish i.p. injected with RBIV (1.1 × 107) were maintained at 23°C. Virus copy number in spleen (A), kidney (B), liver (C), blood (D), and RBCs (E) were analyzed at 1, 2, 4, 7, and 10 days post infection (dpi). One-way analysis of variance (ANOVA) was performed between conditions, with Tukey's multiple comparison test. Different superscript letters denote significant differences (P < 0.05). a≠ b. Data are represented as individual values. Line represents mean value.

In blood samples, the viral transcription level was 7.16 × 101/100 μL at 1 dpi, gradually increased to 3.81 × 102/100 μL at 2 dpi, and reached maximum values of 9.36 × 103/100 μL at 7 dpi and 2.04 × 104/100 μL at 10 dpi (Figure 1D). In Ficoll-purified RBCs from fish at 1, 2, 4, 7, and 10 dpi, virus copy numbers gradually increased with time; the average number of virus copies was 1.25 × 102, 2.31 × 102, 8.42 × 102, 9.22 × 103, and 3.54 × 104/100 μL, respectively (Figure 1E).

Protein Profiling of RBCs From RBIV-Infected Rock Bream

Cytoscape pathway enrichment analysis was performed in order to evaluate the functional pathways involved in the response of rock bream RBCs to RBIV (Figure 2). Proteins with a FDR < 0.001 and−1.5>log2 Fold Change (FC)>1.5 were selected for functional network analysis. A total of 318 proteins were differentially regulated at a significant level in RBCs from RBIV-infected individuals: 183 proteins were upregulated and 135 were downregulated. Upregulated pathways were categorized into 13 main categories, while downregulated pathways were categorized into 2 (Figures 2–6 and Tables 2–4). Within upregulated pathways, proteins were involved in synthesis of active ubiquitin, E1 and E2 enzymatic roles, pyridine-containing compound metabolic processes, RNA transport, the spliceosome, cytosolic tRNA aminoacylation, the vitamin B6 biosynthetic process, snRNP assembly, cellular detoxification, the cholesterol biosynthetic process, the cellular amino acid metabolic process, the Parkin-Ubiquitin proteasomal system pathway, apoptosis, and antigen processing and presentation of peptide antigen via MHC class I (Figures 2–4 and Tables 2, 3). Within downregulated pathways, proteins were mainly involved in the ISG15 antiviral mechanism and p130Cas linkage to MAPK signaling for integrins (Figures 2, 5, 6 and Table 4).

Figure 2.

Figure 2

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Cytoscape network analysis of differentially expressed protein (DEPs) in RBCs from RBIV-infected rock bream. DEPs in RBCs from RBIV-infected rock bream at 7 dpi, with −1.5 < log2FC < 1.5 and FDR P < 0.001. Overrepresented terms were identified by the Cytoscape ClueGo app, with GO Biological Process, Kegg, Reactome, and Wikipathways term databases. Red circles indicate upregulated/overrepresented terms, and green circles indicate downregulated/overrepresented terms. Gray circles indicate unspecific regulation. Color intensity represents the degree of overrepresentation.

Figure 6.

Figure 6

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Comparative protein levels in upregulated and downregulated overrepresented pathways in RBCs from RBIV-infected rock bream. Data represent the number of proteins represented in each pathway. Red bars indicate upregulated proteins and dashed bars indicate downregulated proteins.

Table 2.

List of upregulated pathways in RBCs from RBIV-infected rock bream.

Category Accession Protein name Protein description Log2FC
Synthesis of active ubiquitin: roles of E1 and E2 enzymes A0A096M453 UCHL3 Ubiquitin C-terminal hydrolase L3 +4.54169
A0A060YC09 UBE2L3 Ubiquitin conjugating enzyme E2 L3 +3.28977
E7EXC7 USP9X Ubiquitin specific peptidase 9 X-linked +1.86819
A0A1A8BMW9 USP5 Ubiquitin specific peptidase 5 +1.73518
A0A1A7XFZ1 UBA6 Ubiquitin like modifier activating enzyme 6 −5.67014
Pyridine-containing compound metabolic process A0A0P7UQB0 NUP98 Nucleoporin 98 +6.56510
A0A060W490 PNPO Pyridoxamine 5′-phosphate oxidase +6.54472
A0A1A8DQA8 PHGDH Phosphoglycerate dehydrogenase +5.96297
A0A060X3S4 PDXK Pyridoxal kinase +3.52413
A0A060X2R3 NUP93 Nucleoporin 93 +3.41500
A0A023UJE3 ENO1 Enolase 1 +2.47019
A0A060YZP7 MPC2 Mitochondrial pyruvate carrier 2 +2.35431
A0A087XLW0 PGAM1 Phosphoglycerate mutase 1 +2.21249
J3QRQ2 DCXR Dicarbonyl and L-xylulose reductase +1.89013
A0A087Y0K3 PSAT1 Phosphoserine aminotransferase 1 +1.65664
A0A087Y968 TPI1 Triosephosphate isomerase 1 −2.53038
H3CAN5 GALK1 Galactokinase 1 −3.00322
A0A146MRI7 NUP35 Nucleoporin 35 −6.06319
A0A1A7XVE8 MDH1 Malate dehydrogenase 1 −7.96449
RNA transport A0A0P7UQB0 NUP98 Nucleoporin 98 +6.56510
A0A146RA28 EIF5B Eukaryotic translation initiation factor 5B +4.94553
A0A087XQU0 PYM1 PYM homolog 1, exon junction complex associated factor +4.00632
H2MNB4 EIF2B3 Eukaryotic translation initiation factor 2B subunit gamma +3.75534
A0A060X2R3 NUP93 Nucleoporin 93 +3.41500
C3KH96 RBM8 RNA binding motif protein 8A +3.16004
A0A060WH91 PABPC1 Poly(A) binding protein cytoplasmic 1 +2.51108
A0A1A7XKU0 RANGAP1 Ran GTPase activating protein 1 +2.40663
A0A087XK21 TRNT1 tRNA nucleotidyl transferase 1 +1.52564
A0A087XJ99 EIF3I Eukaryotic translation initiation factor 3 subunit I −2.81793
A0A060XCL3 ALYREF Aly/REF export factor −3.15159
H2LP66 EIF3J Eukaryotic translation initiation factor 3 subunit J −4.12793
A0A146MRI7 NUP35 Nucleoporin 35 −6.06319
Spliceosome A0A0P7XD74 SNRPF Small nuclear ribonucleoprotein polypeptide F +8.79320
A0A087Y346 SNRPD1 Small nuclear ribonucleoprotein D1 polypeptide +4.98734
I3KZX4 LSM3 LSM3 homolog, U6 small nuclear RNA and mRNA degradation associated +3.60900
C3KH96 RBM8 RNA binding motif protein 8A +3.16004
A0A060XGY3 SF3A3 Splicing factor 3a subunit 3 +2.23314
A0A1L3A6A6 HSPA8 Heat shock protein family A (Hsp70) member 8 +1.81502
A0A0P7UL65 SNRPG Small nuclear ribonucleoprotein polypeptide G +1.70328
A0A087Y0E9 PPIH Peptidylprolyl isomerase H −3.11189
A0A060XCL3 ALYREF Aly/REF export factor −3.15159
H2RJ37 SNRPA1 Small nuclear ribonucleoprotein polypeptide A' −3.29532
Cytosolic tRNA aminoacylation G3NSI9 FARSLA Phenylalanyl-tRNA synthetase subunit alpha +3.43435
A0A1A7ZJC0 MARS Methionyl-tRNA synthetase +3.27543
A0A087YJF0 EPRS Glutamyl-prolyl-tRNA synthetase +2.78295
A0A060YC35 SARS Seryl-tRNA synthetase +2.61934
A0A060WQF7 LARS Leucyl-tRNA synthetase −1.93372
A0A060W490 PNPO Pyridoxamine 5′-phosphate oxidase +6.54472
A0A060X3S4 PDXK Pyridoxal kinase +3.52413
A0A087Y0K3 PSAT1 Phosphoserine aminotransferase 1 +1.65664
snRNP Assembly A0A0P7XD74 SNRPF Small nuclear ribonucleoprotein polypeptide F +8.79320
A0A0P7UQB0 NUP98 Nucleoporin 98 +6.56510
A0A087Y346 SNRPD1 Small nuclear ribonucleoprotein D1 polypeptide +4.98734
A0A060X2R3 NUP93 Nucleoporin 93 +3.41500
A0A0P7UL65 SNRPG Small nuclear ribonucleoprotein polypeptide G +1.70328
A0A146MRI7 NUP35 Nucleoporin 35 −6.06319
Cellular detoxification A0A087YGW8 CLIC2 Chloride intracellular channel 2 +6.00740
H2RV41 GSTM3 Glutathione S-transferase mu 3 +5.94070
I3IV50 FAS Fas cell surface death receptor +5.88751
W5KQL6 APOE Apolipoprotein E +4.62692
A0A0S7HP87 FAM213B Family with sequence similarity 213 member B +4.13534
B9MSR2 SOD1 Superoxide dismutase 1 +2.53220
A0A087X9L9 TXNRD3 Thioredoxin reductase 3 +2.07657
A0A060VRY4 XPA XPA, DNA damage recognition and repair factor +1.76996
A0A087YMH6 ADH5 Alcohol dehydrogenase 5 (class III), chi polypeptide +1.57015
W5NF82 NEFL Neurofilament light +1.50524
A0A087YDB9 TRPM6 Transient receptor potential cation channel subfamily M member 6 −2.90258
B3VTP4 APOA4 Apolipoprotein A4 −3.50052
A0A087WSW9 TXNRD1 Thioredoxin reductase 1 −3.51362
C9DTM6 EPX Eosinophil peroxidase −5.96073
A0A0F8BVI8 MPO Myeloperoxidase −5.96073
Cholesterol biosynthetic process W5KQL6 APOE Apolipoprotein E +4.62692
W5NG17 GGPS1 Geranylgeranyl diphosphate synthase 1 +3.68607
A0A0S7LJM9 CNBP CCHC-type zinc finger nucleic acid binding protein +3.65477
A0A060X0E0 ERLIN2 ER lipid raft associated 2 +3.09663
A0A060WK05 PMVK Phosphomevalonate kinase +3.00278
C1BJ00 VDAC2 Voltage dependent anion channel 2 +2.784311
B9MSR2 SOD1 Superoxide dismutase 1 +2.53220
B3VTP4 APOA4 Apolipoprotein A4 −3.50052
C1BKM7 APOA1 Apolipoprotein A1 −3.58118
I6QFY3 CFTR Cystic fibrosis transmembrane conductance regulator −3.85295
Cellular amino acid metabolic process A0A146NIL6 HNMT Histamine N-methyltransferase +7.33475
Q19A30 ALDH9A1 Aldehyde dehydrogenase 9 family member A1 +7.08477
H2M1L3 GCLC Glutamate-cysteine ligase catalytic subunit +7.05565
A0A1A8DQA8 PHGDH Phosphoglycerate dehydrogenase +5.96297
A0A087YCZ2 SBDS SBDS, ribosome maturation factor +5.38388
H2SS02 PYCR3 Pyrroline-5-carboxylate reductase 3 +4.13757
A0A0P7USQ3 PSMD11 Proteasome 26S subunit, non-ATPase 11 +3.83617
W5UAL8 GSS Glutathione synthetase +3.49635
A0A087X9P9 RPS28 Ribosomal protein S28 +3.46599
G3NSI9 FARSLA Phenylalanyl-tRNA synthetase subunit alpha +3.43435
A0A1A7ZJC0 MARS Methionyl-tRNA synthetase +3.27543
A0A147AHI6 PSMB6 Proteasome subunit beta 6 +3.23477
Q66HW0 COASY Coenzyme A synthase +2.88808
A0A087YJF0 EPRS Glutamyl-prolyl-tRNA synthetase +2.78295
A0A087WUL2 PSMB3 Proteasome subunit beta 3 +2.74293
A0A060YC35 SARS Seryl-tRNA synthetase +2.61934
H2VBD9 PSMD5 Proteasome 26S subunit, non-ATPase 5 +2.46929
A0A060YZH5 RPS21 Ribosomal protein S21 +2.03250
A0A0N8K350 ARG2 Arginase 2 +1.90666
H2MN42 NIT2 Nitrilase family member 2 +1.87753
Q45VN8 PSMB4 Proteasome subunit beta 4 +1.84703
A0A087Y0K3 PSAT1 Phosphoserine aminotransferase 1 +1.65664
A0A087XKC8 ALDH4A1 Aldehyde dehydrogenase 4 family member A1 −1.60365
A0A0F8C9G0 AASDHPPT Aminoadipate-semialdehyde dehydrogenase-phosphopantetheinyl transferase −1.8438
W5M476 SARDH Sarcosine dehydrogenase −1.86083
A0A060WQF7 LARS Leucyl-tRNA synthetase −1.93372
A0A060Z3T7 MRI1 Methylthioribose-1-phosphate isomerase 1 −2.64492
A0A087WSW9 TXNRD1 Thioredoxin reductase 1 −3.51362
Parkin-ubiquitin proteasomal system pathway A0A146UQZ0 CCT3 Chaperonin containing TCP1 subunit 3 +4.20768
A0A0P7USQ3 PSMD11 Proteasome 26S subunit, non-ATPase 11 +3.83617
A0A060YC09 UBE2L3 Ubiquitin conjugating enzyme E2 L3 +3.28977
A0A147AHI6 PSMB6 Proteasome subunit beta 6 +3.23477
A0A146VFH4 TUBA4A Tubulin alpha-4A chain +2.86588
A0A060WLR9 TUBA3C Tubulin alpha 3c +2.86588
A0A087WUL2 PSMB3 Proteasome subunit beta 3 +2.74293
H2VBD9 PSMD5 Proteasome 26S subunit, non-ATPase 5 +2.46929
Q45VN8 PSMB4 Proteasome subunit beta 4 +1.84703
A0A146PU69 ACTB Actin beta +1.83645
A0A1L3A6A6 HSPA8 Heat shock protein family A (Hsp70) member 8 +1.81502
A0A189JAM4 TUBA1C Tubulin alpha 1c −2.55283
H6QXT0 CASP1 Caspase 1 −2.90548
F2Z2E2 IQGAP3 IQ motif containing GTPase activating protein 3 −4.82941
Apoptosis A0A0P7UQB0 NUP98 Nucleoporin 98 +6.56510
I3IV50 FAS Fas cell surface death receptor +5.88751
A0A060WPW9 RUVBL1 RuvB like AAA ATPase 1 +5.68115
A0A060X986 CASP9 Caspase 9 +5.34643
A0A096M453 UCHL3 Ubiquitin C-terminal hydrolase L3 +4.54169
W5LA34 ABCB1 ATP binding cassette subfamily B member 1 +4.23220
A0A146UQZ0 CCT3 Chaperonin containing TCP1 subunit 3 +4.20768
A0A0P7USQ3 PSMD11 Proteasome 26S subunit, non-ATPase 11 +3.83617
A0A060X2R3 NUP93 Nucleoporin 93 +3.41500
A0A060YC09 UBE2L3 Ubiquitin conjugating enzyme E2 L3 +3.28977
A0A147AHI6 PSMB6 Proteasome subunit beta 6 +3.23477
A0A060X0E0 ERLIN2 ER lipid raft associated 2 +3.09663
C1BJ00 VDAC2 Voltage dependent anion channel 2 +2.78431
A0A087WUL2 PSMB3 Proteasome subunit beta 3 +2.74293
A0A060XWP8 RPN2 Ribophorin II +2.51942
A0A060WH91 PABPC1 Poly(A) binding protein cytoplasmic 1 +2.51108
H2VBD9 PSMD5 Proteasome 26S subunit, non-ATPase 5 +2.46929
A0A087XG68 HMGB2 High mobility group box 2 +2.41814
A0A1A7XKU0 RANGAP1 Ran GTPase activating protein 1 +2.40663
A0A146RM67 DSP Desmoplakin +2.25958
A0A060VUK9 ACTL6A Actin like 6A +1.92039
E7EXC7 USP9X Ubiquitin specific peptidase 9 X-linked +1.86819
Q45VN8 PSMB4 Proteasome subunit beta 4 +1.84703
A0A1L3A6A6 HSPA8 Heat shock protein family A (Hsp70) member 8 +1.81502
A0A1A8BMW9 USP5 Ubiquitin specific peptidase 5 +1.73518
H2MXM9 CASP6 Caspase 6 +1.65460
A0A060W5L7 USP47 Ubiquitin specific peptidase 47 −1.85717
A0A1A8GUB0 YWHAB Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein beta −2.17782
A0A060WMK5 PAK2 p21 (RAC1) activated kinase 2 −2.39132
G3NDG3 PLEC Plectin −3.20510
G3NRU2 RNF146 Ring finger protein 146 −3.25047
C1BKM7 APOA1 Apolipoprotein A1 −3.58118
I6QFY3 CFTR Cystic fibrosis transmembrane conductance regulator −3.85294
F2Z2E2 IQGAP3 IQ motif containing GTPase activating protein 3 −4.82941
X1WEE8 TRIM25 Tripartite motif containing 25 −5.61605
A0A146MRI7 NUP35 Nucleoporin 35 −6.06319
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Table 4.

List of downregulated pathways in RBCs from RBIV-infected rock bream.

Category Accession Protein name Protein description Log2FC
ISG15 antiviral mechanism A0A0P7UQB0 NUP98 Nucleoporin 98 +6.56510
A0A060X2R3 NUP93 Nucleoporin 93 +3.41500
C7ATZ0 STAT1 Signal transducer and activator of transcription 1 +2.72893
A0A060W790 KPNA3 Karyopherin subunit alpha 3 −1.55875
A0A067ZTD7 IRF3 Interferon regulatory factor 3 −2.77578
X1WEE8 TRIM25 Tripartite motif containing 25 −5.61605
A0A087X811 FLNB Filamin B −5.77028
A0A146MRI7 NUP35 Nucleoporin 35 −6.06319
p130Cas linkage to MAPK signaling for integrins Q6PH06 CRK CRK proto-oncogene, adaptor protein +3.83669
A0A146RM67 DSP Desmoplakin +2.25958
A0A0F8ALN2 FGA Fibrinogen alpha chain −1.84245
H2LW76 FGG Fibrinogen gamma chain −3.25828
C1BKM7 APOA1 Apolipoprotein A1 −3.58117
A0A087X4W0 FGB Fibrinogen beta chain −4.94492
A0A0R4ICS1 ITGA4 Integrin subunit alpha 4 −5.35249
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Figure 4.

Figure 4

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GO Immune System Process terms in the proteome profile of RBIV-infected RBCs. Upregulated/overrepresented terms in DEPs of RBCs from RBIV-infected rock bream at 7 dpi, with −1.5<log2FC<1.5 and FDR P < 0.001. (A) Bar graph and (B) multilevel pie chart. Overrepresented terms were identified by the Cytoscape ClueGo app with the GO Immune System Process database. Asterisks denote GO-term significance (**P < 0.01).

Table 3.

List of identified proteins related to antigen processing and presentation of peptide antigen via MHC class I.

Category Accession Protein name Protein description Log2FC
Antigen processing and presentation of peptide antigen via MHC class I A0A146MHT9 MR1 Major histocompatibility complex, class I-related +4.08719
A0A0P7USQ3 PSMD11 Proteasome 26S subunit, non-ATPase 11 +3.83617
Q5SRD4 TAP2 Transporter 2, ATP binding cassette subfamily B member +3.83464
A0A147AHI6 PSMB6 Proteasome subunit beta 6 +3.23477
A0A087WUL2 PSMB3 Proteasome subunit beta 3 +2.74293
H2VBD9 PSMD5 Proteasome 26S subunit, non-ATPase 5 +2.46929
Q45VN8 PSMB4 Proteasome subunit beta 4 +1.84703
I3J5Y7 CANX Calnexin −1.55500
A5A0E1 SNAP23 Synaptosome associated protein 23 −2.80077
Antigen processing and presentation of exogenous peptide antigen via MHC class I A0A0P7USQ3 PSMD11 Proteasome 26S subunit, non-ATPase 11 +3.83617
Q5SRD4 TAP2 Transporter 2, ATP binding cassette subfamily B member +3.83464
A0A147AHI6 PSMB6 Proteasome subunit beta 6 +3.23477
A0A087WUL2 PSMB3 Proteasome subunit beta 3 +2.74293
H2VBD9 PSMD5 Proteasome 26S subunit, non-ATPase 5 +2.46929
Q45VN8 PSMB4 Proteasome subunit beta 4 +1.84703
A5A0E1 SNAP23 Synaptosome associated protein 23 −2.80077
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Figure 5.

Figure 5

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Downregulated functional pathways in the proteome profile of RBIV-infected RBCs. Downregulated/overrepresented terms in DEPs of RBCs from RBIV-infected rock bream at 7 dpi, with −1.5 < log2FC < 1.5 and FDR P < 0.001. (A) Bar graph and (B) multilevel pie chart. Overrepresented terms were identified by the Cytoscape ClueGo app, with the GO Biological Process, Kegg, Reactome, and Wikipathways databases. Asterisks denote GO-term significance (*P < 0.05 and **P < 0.01).

Figure 3.

Figure 3

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Upregulated functional pathways in the proteome profile of RBIV-infected RBCs. Upregulated/overrepresented terms in DEPs of RBCs from RBIV-infected rock bream at 7 dpi, with −1.5 < log2FC < 1.5 and FDR P < 0.001. (A) Bar graph and (B) multilevel pie chart. Overrepresented terms were identified by the Cytoscape ClueGo app, with GO Biological Process, Kegg, Reactome, and Wikipathways term databases. Asterisks denote GO-term significance (*P < 0.05 and **P < 0.01).

Differentially Expressed Proteins Related to the Apoptosis Functional Pathway

A total of 36 apoptosis-related proteins were differentially regulated in RBCs from RBIV-infected individuals: 26 proteins were upregulated and 10 were downregulated (Figure 6). Among them, caspase-6 (CASP6), caspase-9 (CASP9), fas cell surface death receptor (FAS), and desmoplakin (DSP) were upregulated at 1.65, 5.35, 5.89, and 2.26 log2FC, respectively (Table 2). p21 (RAC1)-activated kinase 2 (PAK2) was downregulated at −2.39 log2FC (Table 2).

Differentially Expressed Proteins Related to the Spliceosome and snRNP Assembly Functional Pathways

Ten spliceosome-related proteins were differentially regulated in RBCs from RBIV-infected individuals: 7 proteins were upregulated and 3 were downregulated (Figure 6 and Table 2). Moreover, 6 snRNP assembly-related proteins were differentially expressed: 5 proteins upregulated and 1 protein downregulated (Figure 6 and Table 2). Among upregulated proteins, the top-scored was small nuclear ribonucleoprotein polypeptide F (SNRPF), with 8.79 log2FC. In addition, small nuclear ribonucleoprotein D1 polypeptide (SNRPD1) and small nuclear ribonucleoprotein polypeptide G (SNRPG) were highly upregulated (Table 2).

Differentially Expressed Proteins Related to Cellular Amino Acid Metabolic Processes and Cellular Detoxification Pathways

A total of 28 DEPs in RBCs from RBIV-infected individuals were involved in cellular amino acid metabolic processes, including 22 upregulated and 6 downregulated proteins (Figure 6 and Table 2). Among upregulated proteins, histamine N-methyltransferase (HNMT), aldehyde dehydrogenase 9 family member A1 (ALDH9A1), glutamate-cysteine ligase catalytic subunit (GCLC), phosphoglycerate dehydrogenase (PHGDH), ribosome maturation factor (SBDS), and pyrroline-5-carboxylate reductase 3 (PYCR3) were highly upregulated with log2FC of 7.33, 7.08, 7.06, 5.96, 5.38, and 4.14, respectively (Table 2).

Of the 15 DEPs involved in cellular detoxification, 10 were upregulated (from 1.50 to 6.94 log2FC) and 5 were downregulated (from −2.90 to −5.96 log2FC) (Table 2). Of note, upregulated proteins included antioxidant enzymes such as glutathione S-transferase mu 3 (GSTM3), superoxide dismutase 1 (SOD1), and thioredoxin reductase 3 (TXNRD3).

Differentially Expressed Proteins Involved in Antigen Processing and Presentation of Peptide Antigen Via MHC Class I

Of 9 DEPs in RBCs from RBIV-infected individuals involved in antigen processing and presentation of peptide antigen via MHC class I (Figure 4), 7 were upregulated and 2 were downregulated (Figure 6 and Table 3). Among the upregulated proteins (with log2FC ranging from 1.85 to 4.08), were major histocompatibility complex class I-related protein (MR1), transporter 2 ATP binding cassette subfamily B member (TAP2), and 6 proteasome subunit proteins (proteasome 26S subunit non-ATPase 11 [PSMD11], proteasome subunit beta 6 [PSMB6], proteasome subunit beta 3 [PSMB3], proteasome 26S subunit non-ATPase 5 [PSMD5], and proteasome subunit beta 4 [PSMB4]).

Differentially Expressed Proteins Involved in ISG15 Antiviral Mechanism Pathway

The interferon-stimulated gene 15 (ISG15) antiviral mechanism pathway appeared to be mainly downregulated in RBCs from RBIV-infected rock bream (Figure 5). Within this pathway, 3 proteins were upregulated (signal transducer and activator of transcription 1 [STAT1], nucleoporin 93 [NUP93], and nucleoporin 98 [NUP98], with log2FC ranging from 2.73 to 6.57), and 5 were downregulated (filamin B [FLNB], nucleoporin 35 [NUP35], interferon regulatory factor 3 [IRF3], tripartite motif containing 25 [TRIM25], and karyopherin subunit alpha 3 [KPNA3], with log2FC ranging from −1.56 to −6.06) (Figure 6 and Table 4).

Validation of Representative Identified Proteins by Means of RT-qPCR

Representative proteins were selected from each overrepresented pathway for validation at the transcriptional level. The Fas and casp9 genes were selected as representatives of the apoptosis pathway, the mhcI gene was selected as a representative of antigen processing and presentation of peptide antigens via MHCI, and the irf3 gene was selected as a representative of the ISG15 antiviral mechanism. As shown in Figure 7, the expression levels of these proteins correlated with the RT-qPCR transcript levels.

Figure 7.

Figure 7

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Relative mRNA and protein expression analysis of IRF3, MHCI, FAS, and CASP9. RBCs from RBIV-infected rock bream compared to PBS-injected rock bream (control). (A) Gene expression analysis, relative to control individuals (red line), evaluated by means of RT-qPCR. The β-actin gene was used as an endogenous control. Bars represent the mean ± standard deviation (SD) (n = 4 individuals). Unpaired T-tests were performed between conditions.*P < 0.05. (B) Quantitative protein expression values of selected proteins for pathway validation from proteomic analysis. Bars indicate log2FC value. FDR values are indicated in Supplementary Table S1.

Discussion

In this study, we report relevant findings in which RBIV, an economically important virus in rock bream aquaculture production, induce an immune response in RBCs. The spleen is one of the major target organs for RBIV replication (2–4, 7). However, we found similarities in RBIV level patterns in the spleen, kidneys, liver, blood, and RBCs. RBIV copy numbers were not as high as in RBCs as in other organs. Nonetheless, RBIV time-dependent increments were found in rock bream blood or Ficoll-purified RBCs.

Previous microarray analyses of kidney samples from RBIV-infected rock bream have shown that hemoglobin (α and β) expression gradually decreased after RBIV replication reached its maximum levels (around 106 to 107/μL) at 20 to 25 dpi (unpublished data). In contrast, high levels of hemoglobin expression were observed at 70 dpi when low viral loads were detected (below 102/μL) (unpublished data). On the other hand, rock bream individuals treated with poly (I:C) exhibited high expression levels of irf3, isg15, and protein kinase RNA-activated (pkr) genes in blood samples, whereas no significant upregulation was observed in the spleen or kidney (6). Furthermore, the highest mhcI constitutive gene expression was detected in the blood of rock bream compared to other tissues such as spleen or kidney (10). Together, these findings emphasize the importance of evaluating blood-mediated immune responses in rock bream against RBIV infection.

RBCs are the most common cell type in the blood, so understanding their immune response will be essential to identify future strategies for controlling RBIV infection. In the present study, we evaluated the proteome of RBCs from RBIV-infected rock bream. Among the upregulated proteins, the MHCI and apoptosis-related pathways were the most overrepresented in RBCs from RBIV-infected rock bream. MHCI plays a crucial role in the presentation of antigen peptides, which are produced by the degradation of intracellular pathogens. These antigen peptides then bind to MHCI molecules and are presented to CD8+ T lymphocytes to trigger cellular immune responses and induce the elimination of infected or apoptotic cells (35, 36). Apoptosis is a process of programmed cell death known to prevent the transmission of infection to uninfected healthy cells by killing infected cells (37). Cytotoxic lymphocytes (CTL) kill infected cells by 2 main pathways: i) releasing cytolytic granules such as pore-forming protein perforin and serine protease granzymes (38, 39) and ii) activating the caspase-dependent Fas ligand pathway (40, 41). In the present study, antigen processing and presentation of peptide antigen via MHCI was upregulated in RBCs from RBIV-infected rock bream. Simultaneously, FAS and CASP9, two proteins implicated in the caspase-dependent Fas ligand pathway, were upregulated in RBCs from RBIV-infected rock bream. Indeed, it has been reported that cytotoxic effector cells induce apoptosis in response to RBIV infection (11). In addition, perforin- and granzyme-related apoptosis initiation signals have been reported to be activated in the kidneys of RBIV-infected rock bream. However, the authors also reported that the Fas-induced, caspase-dependent apoptosis pathway was barely induced based on only slight increases in fas, casp3, casp8, and casp9 gene expression (11, 13). Conversely, based on our proteomic results, both FAS and CASP9 proteins were upregulated in RBCs from RBIV-infected individuals, indicating that RBIV-activated apoptosis in rock bream RBCs could occur via the caspase-dependent Fas ligand pathway. These results could also suggest that apoptosis-related genes may be differently expressed in kidneys and RBCs. Similarly, we have previously reported that a myristoylated membrane protein (MMP)-based DNA vaccine administered to rock bream triggered differential expression of apoptosis-related genes (including perforin, granzyme, Fas, Fas ligand, and caspases) depending on the tissue analyzed (spleen, kidney, liver, or muscle) (42). In addition, we have observed that other proteins involved in promoting or inducing apoptosis, such as DSP, PAK2, and heat shock protein family A (Hsp70) member 8 (HSPA8) proteins, were highly upregulated in rock bream RBCs upon RBIV infection. The induction of both the antigen processing and presentation via MHCI pathway and the apoptosis-related pathway against RBIV infection may indicate that RBCs attempt to activate CTLs and subsequently trigger them to induce apoptosis by perforin and granzyme production, which are critical factors for the inhibition of RBIV replication (13). Separately, MHCI-induced apoptosis has been also reported during differentiation and activation of certain hematopoietic cells (43).

Surprisingly, in the present study, proteins related to the ISG15 antiviral mechanism such as IRF3, NUP35, and TRIM25 were downregulated in RBCs from RBIV-infected individuals. In general, the first line of defense against viral infection is based on type I interferon (IFN) expression (44). ISG15 is known to play an antiviral role against different viral pathogens [reviewed in (45)]. In fish, the IFN-related immune response, as well as ISG15-related proteins, are known to exhibit an inhibitory effect on viral infections (46–53). In our previous studies, we have found that mx gene expression upregulation occurs soon after viral infection and is maintained in the kidneys of RBIV-infected rock bream at least till 10 dpi (15). However, the expression of the isg15 and pkr genes declined after 4 dpi. Therefore, type I IFN responses induced by RBIV infection seemed to be limited in time and were not able to maintain antiviral responses at later stages, leading to fish mortality (15). Many viruses have developed strategies to counteract the antiviral activity of ISG15 (54). In orange-spotted grouper (Epinephelus coioides) spleen cell line (GS), ISG15 was not significantly upregulated by Singapore grouper iridovirus (SGIV) infection, while it was overexpressed by grouper nervous necrosis virus (GNNV) (45). Moreover, SGIV infection could downregulate the expression of ISG15, IFN and Mx previously induced by poly I:C, suggesting that SGIV was able to counteract the cellular interferon-mediated antiviral activity. In this regard, the authors also speculated that SGIV encoded proteins could play vital roles in preventing ISG15 activity during SGIV infection. To our knowledge, nothing is known about the interactions between RBIV proteins and host innate immune responses, especially those related to IFN or ISG15 pathways proteins. Therefore, in light of evidences, further studies are needed to elucidate RBIV interactions and/or counteracting effects on rock bream innate immune response.

Finally, pathways related to the spliceosome, snRNP assembly, cellular amino acid metabolic processes, and cellular detoxification were differentially regulated in RBCs from RBIV-infected rock bream. In the same way, previous investigations by Nombela et al. have reported the regulation of proteins related to spliceosomal complex and antioxidant/antiviral response in RBCs exposed in vitro to VHSV (23). However, how these mechanisms contribute to rock bream immune response to RBIV remains to be studied.

In summary, we have demonstrated that rock bream RBCs are able to generate a response to RBIV infection. This response was characterized by the upregulation of apoptosis-, MHCI, cellular detoxification-, and spliceosome-related pathways and the downregulation of ISG15 antiviral mechanisms. We have therefore identified novel target proteins in RBCs that will be valuable tools for future studies on the elucidation of RBIV-rock bream interaction mechanisms. These relevant findings will contribute to mitigate an economically important viral disease affecting rock bream aquaculture.

Author Contributions

M-HJ performed experiments, analyzed data, and wrote the manuscript. VC performed experiments. SC and MM performed proteomic sequencing. MO-V conceived ideas, analyzed data, oversaw the research, and wrote the manuscript. VC and S-JJ contributed to the preparation of the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Remedios Torres and Efren Lucas for their technical assistance. The proteomic analysis was performed in the Proteomics Facility of The Spanish National Center for Biotechnology (CNB-CSIC) that belongs to ProteoRed, PRB3-ISCIII, supported by grant PT17/0019. We would also like to thank the two reviewers for their valuable comments and suggestions.

Footnotes

Funding. This research was supported by the European Research Council (ERC Starting Grant GA639249) and by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A1A01053685).

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2019.00160/full#supplementary-material

Click here for additional data file. (7MB, XLSX)

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