Transcriptome Analysis Reveals Comprehensive Insights into the Early Immune Response of Large Yellow Croaker (Larimichthys crocea) Induced by Trivalent Bacterial Vaccine

Xin Zhang; Yinnan Mu; Pengfei Mu; Jingqun Ao; Xinhua Chen

doi:10.1371/journal.pone.0170958

Abstract

Vaccination is an effective and safe strategy for combating bacterial diseases in fish, but the mechanisms underlying the early immune response after vaccination remain to be elucidated. In the present study, we used RNA-seq technology to perform transcriptome analysis of spleens from large yellow croaker (Larimichthys crocea) induced by inactivated trivalent bacterial vaccine (Vibrio parahaemolyticus, Vibrio alginolyticus and Aeromonas hydrophila). A total of 2,789 or 1,511 differentially expressed genes (DEGs) were obtained at 24 or 72 h after vaccination, including 1,132 or 842 remarkably up-regulated genes and 1,657 or 669 remarkably down-regulated genes, respectively. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichments revealed that numerous DEGs belong to immune-relevant genes, involved in many immune-relevant pathways. Most of the strongly up-regulated DEGs are innate defense molecules, such as antimicrobial peptides, complement components, lectins, and transferrins. Trivalent bacterial vaccine affected the expressions of many components associated with bacterial ligand–depending Toll-like receptor signaling pathways and inflammasome formation, indicating that multiple innate immune processes were activated at the early period of vaccination in large yellow croaker. Moreover, the expression levels of genes involved in antigen processing were also up-regulated by bacterial vaccine. However, the expression levels of several T cell receptors and related CD molecules and signal transducers were down-regulated, suggesting that the T cell receptor signaling pathway was rapidly suppressed after vaccination. These results provide the comprehensive insights into the early immune response of large yellow croaker to vaccination and valuable information for developing a highly immunogenic vaccine against bacterial infection in teleosts.

Citation: Zhang X, Mu Y, Mu P, Ao J, Chen X (2017) Transcriptome Analysis Reveals Comprehensive Insights into the Early Immune Response of Large Yellow Croaker (Larimichthys crocea) Induced by Trivalent Bacterial Vaccine. PLoS ONE 12(1): e0170958. https://doi.org/10.1371/journal.pone.0170958

Editor: Tzong-Yueh Chen, National Cheng Kung University, TAIWAN

Received: September 12, 2016; Accepted: January 14, 2017; Published: January 30, 2017

Copyright: © 2017 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All transcriptome data files are available from the NCBI Sequence Read Archive database (accession number SRP092778).

Funding: This work was supported by the National Natural Science Foundation of China (31530080 and 31372556) and National Basic Research Program of China (2015CB755903). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Large yellow croaker (Larimichthys crocea) is one of the most important aquaculture species in China, with the annual yield exceeding any other net-cage-farmed marine fish species [1]. However, the diseases caused by bacteria, such as Vibrio parahaemolyticus [2], Vibrio alginolyticus [3], and Aeromonas hydrophila [4], outbreak frequently and result in tremendous economic losses in large yellow croaker aquaculture industry. Chemotherapeutants and antibiotics are useful for preventing bacterial infection, but long term treatment often leads to resistance and environmental pollution [5]. Vaccination is an effective and safe strategy for combating bacterial diseases in fish [6]. A number of vaccines are commercially available for use in the aquaculture industry, such as formalin-inactivated Yersinia ruckeri [7], Aeromonas salmonicida [8], and Vibrio anguillarum [9]. The effects of vaccines were mainly evaluated by serum or mucus antibody titers and survival rate [10]. Recently, several studies on the gene expression changes have been performed to understand the immune response to bacterial vaccines in fish. In Atlantic salmon (Salmo salar), the increased expressions of antibacterial proteins and proteases were observed after vaccination with live Aeromonas salmonicida [11]. In zebrafish (Danio rerio), multiple pathways including acute phase response, complement activation, and antigen processing and presentation were remarkably affected during the early stage of vaccination [12]. The genes involved in inflammation and antioxidant defense were also up-regulated in Atlantic cod (Gadus morhua) following vaccination with heat-killed Vibrio anguillarum [13].

An inactivated trivalent bacterial vaccine, consisting of V. alginolyticus, V. parahaemolyticus, and A. hydrophila, was developed and provided an effective protection against bacterial infection in large yellow croaker, with a relative percent survival (RPS) of 88.9% [14]. This trivalent bacterial vaccine has been used to study the expression patterns of immune-relevant genes in large yellow croaker, such as goose-type lysozyme [15], caspase 9 [16], C-type lectin-like receptor [17], CXCL8 [18], CXCL13 [19], and stefin [20], indicating that this bacterial vaccine could induce the expression of innate immunity molecules in large yellow croaker. Currently, high-throughput RNA sequencing (RNA-seq) technology provides a powerful and cost-effective approach to understand the immune response evoked by different stimulus. For instance, RNA-seq was applied to identify immune-candidate genes, infection markers, and putative signaling pathways in rainbow trout (Oncorhynchus mykiss) [21], tilapia (Oreochromis niloticus) [22], and grass carp (Ctenopharyngodon idellus) [23] after bacterial infection.

Here, we used RNA-seq to examine the transcriptional profiles of the large yellow croaker spleens at early time points (0, 24, and 72 h) following immunization with inactivated trivalent vaccine (V. alginolyticus, V. parahaemolyticus and A. hydrophila). A series of differentially expressed genes (DEGs) were identified and found to be involved in the innate immunity and acquired immunity processes. Moreover, quantitative real-time PCR was used to verify expression changes of partial immune-relevant genes. These data provide valuable information to better understand the early immune response after vaccination in large yellow croaker.

Materials and Methods

Ethics statement

All handling of fish was approved by the Institutional Animal Care and Use Committee of Fujian Province, and performed in strict accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals, under protocol license number: SYXK (MIN) 2007–0004. All surgeries were carried out under Tricaine-S anesthesia, and all efforts were made to minimize suffering.

Inactivated trivalent bacterial vaccine and fish samples

The V. parahaemolyticus, V. alginolyticus and A. hydrophila were isolated from the diseased large yellow croaker previously [14]. For vaccine preparation, the three bacteria were cultured in Luria-Bertain (LB) for 16 h in a shaker incubator (180 rpm) at 30°C, respectively. After collected and washed with the sterilized phosphate-buffered saline (PBS, pH 7.4), V. parahaemolyticus, V. alginolyticus and A. hydrophila were mixed at same proportion (1.0×10⁹ CFU/mL each) and inactivated with 0.5% formalin (v/v) at 4°C for 4 h. The mixed inactivated trivalent vaccine was washed with the sterilized PBS. To evaluate the effectiveness of the formalin-inactivation, 50 μL of formalin-inactivated suspensions were spread on LB agar (1.5%, w/v) and incubated at 37°C for 24 h. No bacterial growth was observed, indicating that the bacterial cells were completely inactivated.

Large yellow croakers (length: 20 ± 1.76 cm; weight: 100 ± 21.5 g) were obtained from the Mari-culture farm in Lianjiang, Fuzhou, China. The fish were maintained at 20°C in aerated water tanks with a flow-through seawater supply. After one week of acclimatization, a group of 30 fish were injected intraperitoneally with inactivated trivalent bacterial vaccine (1.0×10⁹ CFU/mL each) at a dose of 0.2 mL/100 g fish. The spleen tissues were harvested from 10 large yellow croakers at each time point (0, 24, and 72 h) after vaccination.

RNA extraction, library preparation, and sequencing

Total RNA was isolated from pooled spleen tissues of 6 fish sampled at each time point for RNA-seq analysis using TRIZOL® Reagent (Invitrogen, USA), respectively, and treated with RNase-free DNase I (Takara, China) at 37°C for 1 h to remove residual genomic DNA. The RNA samples (5 μg each) were used to construct RNA-seq libraries by Illumina mRNA-Seq Prep Kit, and the libraries were sequenced by paired-end sequencing on the Illumina HiSeq 2000 sequencing platform (Illumina, USA).

Identification of the differentially expressed genes

Clean reads were picked out from the raw reads of each library following removal of the reads containing adaptor sequences, reads with an N (unknown bases in read) percentage higher than 10%, and low quality reads (> 50% of bases with a quantity score Q-value ≤ 10) using an in-house C⁺⁺ program. The clean reads were aligned to the large yellow croaker genome (JRPU00000000) [24] using the software Burrows-Wheeler Aligner (BWA, parameter: -o 1 -e 63 -i 90 -L -k 2 -l 31 -t 4 -q 10) [25], and mapped to the coding sequences (CDS) of large yellow croaker genome using Bowtie2 (Parameter: -q --phred64 --sensitive --dpad 0 --gbar 99999999 --mp 1,1 --np 1 --score-min L,0,-0.1 -I 1 -X 1000 --no-mixed --no-discordant -p 1 -k 200) [26]. The gene expression levels were calculated based on FPKM (fragments per kilobase of transcripts per million fragments mapped) values by using RSEM (RNA Seq by Expectation Maximization) with default setting [27]. Comparisons of gene expression difference between control (0 h) and other time points after vaccination (24 and 72 h) were performed by strict Poisson distribution algorithm. Genes with the absolute value of the log₂Ratio ≥ 1 and FDR (false discovery rate) ≤ 0.001 were defined as DEGs [28].

Gene ontology and kyoto encyclopedia of genes and genomes (KEGG) analysis

All the DEGs were mapped to the gene ontology (GO) database (http://www.geneontology.org/) using Blast2GO software [29]. KEGG Orthology (KO) was carried out by BLASTx based on the KEGG database (http://www.genome.jp/kegg/). Finally, GO and KO enrichment analysis were performed according to the hypergeometric distribution test. For GO enrichment analysis, all of the P-values were performed with Bonferroni correction. We have selected a corrected P-value of 0.05 as a threshold to determine significant enrichment of the gene sets. In contrast, for KO enrichment analysis, we have used a Q-value of 0.05 as the threshold to determine significant enrichment of the gene sets.

Quantitative real-time PCR

Quantitative real-time PCR was performed using Mastercycler epgradient realplex4 (Eppendorf, Germany) with SYBR Green (Takara, China). Primer sets were designed based on the coding sequences of identified genes in large yellow croaker genome and specific PCR product of each gene was observed on the agarose gels (S1 Table and S1 Fig). Total RNA was extracted from pooled spleen tissues of three fish sampled at each time point (0, 24, and 72 h) after vaccination for Real-time PCR analysis. Real-time PCR was performed in a total volume of 20 μL, and cycling conditions were 95°C for 1 min, followed by 40 cycles of 95°C for 15 s, 58°C for 15 s, 72°C for 20 s. Each real-time PCR assay was repeated three times with different batches of fish. The expression level of target gene was normalized by that of β-actin using the 2^-ΔΔCT method [30]. The fold change was calculated as the average expression level of target gene in trivalent vaccine-challenged samples at each time point (24 and 72 h) divided by that in the control sample (0 h). The data of real-time PCR was analyzed using GraphPad Prism 5 software and expressed as the standard error of the mean (SEM). Two-tailed Student’s t test was used for the significance test between the experimental group and the control group. A P-value <0.05 was considered to be statistically significant.

Results

Sequence analysis of the transcriptomes

Three transcriptomes were sequenced from pooled spleens of large yellow croaker after vaccination. More than 5.4 gigabase (Gb) of data were generated in each library (Table 1). After eliminating adaptor sequences and low-quality sequences, a total of 63,568,408, 60,346,074, and 60,445,278 clean reads were obtained from the three libraries (0, 24, and 72 h), respectively. Average 70% of the clean reads could be mapped to the genome of large yellow croaker with 19,648, 19,106, and 19,145 genes, respectively. Raw sequencing reads data has been deposited in SRA (NCBI) under the accession number of SRP092778.

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Table 1. Summary of the data for transcriptomes.

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Analysis of differential expression genes

The gene expression levels were calculated based on FPKM values, and gene expression difference was analyzed between each time point (24 and 72 h) after vaccination and control (0 h). At 24 h, 2,789 genes were differentially expressed (log₂Ratio ≥ 1, FDR ≤ 0.001), including 1,132 up-regulated genes and 1,657 down-regulated genes (Fig 1). Meanwhile, a total of 1,511 differentially expressed genes were found at 72 h after vaccination, including 842 up-regulated genes and 669 down-regulated genes. All the differentially expressed genes were provided in S2 Table.

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Fig 1. Statistic of differentially expressed genes (DEGs) at different time points after vaccination.

The comparisons of gene expression difference between control (0 h) and each time point after vaccination (24 and 72 h) were performed based on FPKM values. The significant DEGs are defined as log₂Ratio ≥ 1 and FDR ≤ 0.001.

https://doi.org/10.1371/journal.pone.0170958.g001

Gene ontology and KEGG enrichment analysis of DEGs

Gene ontology functional enrichment analysis for DEGs at 24 h (or 72 h) showed that most of DEGs were classified into three major functional categories: ‘‘biological process”, ‘‘molecular function”, and ‘‘cellular component”, represented by 606 (or 389), 643 (or 390), and 420 (or 283) genes, respectively (S3 Table). The largest subcategories were “cellular processes” (299 or 223 genes), “catalytic activity” (390 or 235 genes), and “cell” (299 or 223 genes) at 24 h or 72 h in corresponding major functional categories. Moreover, two immune-relevant subcategories, “response to stimulus” (120 or 57 genes) and “immune system process” (21 or 13 genes) were also enriched (Fig 2).

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Fig 2. Enrichment of Gene Ontology classifications for the DEGs.

The DEGs were annotated into three major functional categories: biological process, cellular component, and molecular function. The X-axis indicates the names of GO terms (2nd level) and the Y-axis indicates the number of DEGs. A, Gene Ontology classifications of DEGs at 24 h after vaccination; B, Gene Ontology classifications of DEGs at 72 h after vaccination.

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KEGG analysis showed that 439 (or 279) DEGs were assigned to 216 (or 173) pathways at 24 (or 72 h) after vaccination, respectively (S4 Table). Immune-relevant KEGG pathways were listed in Table 2, including cytokine-cytokine receptor interaction (17 or 8 genes), T cell receptor signaling pathway (10 or 4 genes), NF-κB signaling pathway (14 or 4 genes), and antigen processing and presentation (8 or 4 genes) at 24 or 72 h. The metabolic pathway had the largest number of DEGs (66 or 39 genes, S4 Table), indicating that vaccination not only can activate immune-relevant pathways, but also may influence metabolic process.

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Table 2. Immune-relevant KEGG pathways.

https://doi.org/10.1371/journal.pone.0170958.t002

Annotation of immune-relevant genes

To better understand the early immune response of large yellow croaker immunized with bacterial vaccine, the immune-relevant DEGs were collected and clustered (Table 3). Lots of important elements of innate immunity were significantly up-regulated at 24 or 72 h after vaccination, including complement components (C2, C3, C7, HF, BF, DF), coagulation system factors (F7, F8, THBS1), lectins (CLEC4E, COLEC12, CLEC17A, F-lectin 1, F-lectin 5, PTX), transferrins (TF, HP), antimicrobial proteins (BPI, lysG, Hep-1), pattern recognition receptors (TLR5M, MMR1, CTLR, PGRP-SC2, NLRP1, NLRP3, Fig 3), signal transducers (IκBα, ERK), transcriptional factors (RelB, AP-1), interleukins and interleukin receptors (IL-1β, IL-6, IL-10, IL-12, IL-27, IL-34, IL-1R, IL-12R, IL-22R), chemokines and chemokine receptors (CCL4, CCL19, CCL20, CCR1, CXCR3), apoptosis-related genes (CASP8, CASP10, BAX, BCL6), cathepsin (CTSL, CTSO), and other immune molecules (TNF-α, MMP-19).

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Fig 3. Pattern-recognition receptors and putative signaling pathways.

The predicted pathway was constructed based on the references [43, 56]and the knowledge of mammalian species. Red background indicates significantly up-regulated expression, and yellow background indicates no significant differential expression. The arrows represent promotion, the solid lines indicate direct relationships between genes, and the dashed lines indicate that more than one step is involved in the process. After binding to flagellin, TLR5M triggers sequential recruitment of MyD88, members of IRAK (interleukin-1 receptor-associated kinase) family and TRAF6 that resulted in activation of nuclear factor NF- κB and AP-1, thus inducing production of inflammatory cytokines such as IL-1β, IL-6, IL-12, and TNF-α. After recognizing corresponding ligands (LPS, Muramyl Dipeptide, or bacterial RNA), NLRP1 or NLRP3 can bind with their adaptor proteins ASC and capase-1 to form the inflammasome complex, and the latter promotes cleavage and secretion of biologically active pro-inflammatory cytokine IL-1β.

https://doi.org/10.1371/journal.pone.0170958.g003

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Table 3. Immune-relevant DEGs found in the trivalent vaccine-induced transcriptome.

https://doi.org/10.1371/journal.pone.0170958.t003

Additionally, many adaptive immune-relevant genes, such as proteasome molecules (PA28, PSMA, PSMB), antigen processing-related genes (CLAR, TAP, TAPBP, HSP70, Fig 4), and regulatory factors (IFN-γ, IL-10, TNF-α) were up-regulated after vaccination, whereas T cell receptor (TCR) signaling molecules (CD3γ, CD4, CD8, TCRα, TCRβ, FYN, ZAP-70, PLC-γ1, Table 3), and some immunoglobulins (Ig heavy chain V region, Ig heavy chain V-III region CAM, Ig heavy chain V-III region HIL, Ig kappa chain V-IV region JI) were down-regulated (S2 Table).

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Fig 4. Putative antigen processing and presentation pathway.

The predicted antigen processing and presentation pathway of large yellow croaker was constructed based on the knowledge of mammalian species. Red background indicates significantly up-regulated expression, and yellow background indicates no significant differential expression. The arrows represent promotion, the solid lines indicate direct relationships between genes, and the dashed lines indicate that more than one step is involved in the process. Bacterial antigens are internalized into host cells via phagosomes or endosomes. Specifically, the antigenic peptides are degraded in the cytoplasm by proteasome, and then transported to the endoplasmic reticulum by TAP and loaded onto MHC-I molecules with the help of ERAP, TAP, TAPBP, and CLAR. Antigenic peptides can also be captured and degraded in endosome and lysosome with the help of CTS, HSP70, and PPT2, and then loaded onto MHC-II molecules.

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Verification of the expression changes of partial immune-relevant genes

Partial DEGs were validated by quantitative real-time PCR. The mRNA transcripts of C3, CLEC4E, F-lectin 1, LysG, Hep-1, TLR5M, AP-1, IL-1β, IL-12, TNF-α, TAP1, PSMA1, CTSL, and CTSO were observably increased at 24 or 72 h after vaccination, while the expression levels of TCRβ were down-regulated (Fig 5). Fold changes of those genes from quantitative real-time PCR were well corresponding to the results of RNA-seq expression analysis, supporting the reliability of the transcriptome data.

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Fig 5. Real-time PCR analysis of selected DEGs.

Real-time PCR was used to validate DEGs associated with innate defense (A), ligand recognition and signal transduction (B), antigen processing and presetation and TCR signaling pathway (C). The expression levels of target gene were expressed relative to those of β-actin in each sample using the 2^-ΔΔCT method. Two-tailed Student’s t test was used for the significance test analysis, ^*P < 0.05, ^**P < 0.01.

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Discussion

To date RNA-seq based transcriptome profiling has been widely used in fish for identifying host determinants of response to bacterial infection [22, 23, 31–33]. In previous study, we have demonstrated that A. hydrophila infection could activate Toll-like receptor, JAK-STAT, and MAPK pathways, while inhibit TCR signaling pathway at the early period in large yellow croaker [34]. In this study, we analyzed the spleen transcriptome profiles of large yellow croaker after vaccination and found abundant DEGs were involved in innate defense, ligand recognition, antigen processing, and TCR signaling processes.

Innate immune response is considered as the first line of host defense in opposing pathogenic infection in fish. The components of the innate defense are evolutionarily conserved in organisms, including antimicrobial peptides, lysozymes, complement, lectins, and transferrins [35]. In this study, the expression of several innate defense molecules was increased obviously after vaccination (Table 3). Their up-regulations were further confirmed by real-time PCR, which were well corresponding to the results from transcriptome analysis (Fig 5A). The similar findings were also found in the studies on Atlantic salmon [11]and Atlantic cod [13], indicating that bacterial vaccine immunization could significantly increase the expression of innate immunity molecules in fish. The activation of complement system usually initiates a cascade of biochemical reactions, resulting in antigen elimination via cell membrane lysis [36]. C3 and C7 of large yellow croaker have been proved to participate in the response to bacterial challenge [37, 38]. Lectins possess binding activity towards carbohydrate residues located on bacterial surfaces and aid neutralization of pathogens [39]. The transferrins, lysozymes, and antibacterial peptides function as the growth inhibitors of bacteria against the infection of bacterial pathogens [15, 40, 41]. These data suggest that immunization with trivalent vaccine intensely enhances the innate defense of large yellow croaker.

The activation of innate immune system against invading microbes mainly relies on the recognition of microbial components by pattern-recognition receptors (PRRs) [42]. Several PRRs, including TLR5M, NLRP1, NLRP3, MMR1, PGRP-SC2, and CTLR were up-regulated significantly after vaccination (Table 3 and Fig 5B). TLR5M is known to recognize bacterial flagellin, signal through MyD88 and TRAF6, trigger the activation of MAPK and NF-κB, and induce inflammatory factors production [43]. Due to V. alginolyticus, V. parahaemolyticus and A. hydrophila are all flagellated bacteria, TLR5M was up-regulated by 7.8-fold at 24 h after vaccination with trivalent bacterial vaccine. Eventually, its downstream signal transducers (TRAF6, IκBα, ERK), transcriptional factors (RelB, AP-1), and effectors (TNF-α, IL-6, IL-12, CCL4) were also up-regulated, indicating TLR5M mediated signaling pathway was activated by trivalent vaccine (Fig 3). Other signal transducers, such as IRAK1/4, TAK1, and IKKα/β/γ were changed slightly after vaccination, perhaps due to these genes play their roles through the changes in phosphorylation levels [44]. NLRP1 or NLRP3 can bind with their adaptor proteins ASC and capase-1 to form the inflammasome complex after recognizing corresponding ligands (LPS, Muramyl Dipeptide, or bacterial RNA), and then promote cleavage and secretion of biologically active pro-inflammatory cytokine IL-1β [45–47]. In this study, NLRP1, NLRP3, ASC, and IL-1β were significantly induced by vaccination (Fig 3), which may result in increase of the biologically active IL-1β to recruit inflammatory cells for eliminating pathogens. These results demonstrate that multiple innate immune processes were activated at the early stage of vaccination in large yellow croaker.

Spleen is a major secondary lymphoid organ in the fish, containing a large number of B cells, T cells, neutrophils, and macrophages. The Neutrophils and macrophages as antigen-presenting cells, possess heterogeneous intracellular pathways responsible for generating complexes of MHC class I and class II molecules with peptide antigens, for presentation to T cells [48–51]. Bacterial antigens are internalized into host cells via phagosomes or endosomes. Specifically, the antigenic peptides are degraded in the cytoplasm by proteasome, and then transported to the endoplasmic reticulum by TAP and loaded onto MHC-I molecules with the help of ERAP, TAP, TAPBP, and CLAR [52]. Antigenic peptides also can be captured and degraded in endosome and lysosome with the help of CTS, HSP70, and PPT2, and then loaded onto MHC-II molecules [53]. In our study, CTS, PPT2, CLAR, TAP, HSP70, and TAPBP were significantly up-regulated after vaccination (Fig 4), while slightly changes were found in the MHC-I and MHC-II expression levels (Table 3). These results suggest that antigen processing may be activated at the early stage of vaccination, but the antigen presentation was in the process of being started.

Moreover, the expression levels of several genes involved in TCR signaling pathway, including TCRα, TCRβ, related CD molecules (CD3γ, CD4, and CD8β), and downstream signaling molecules (FYN, ZAP-70, PLC-γ1, PDK, and PKCθ), were down-regulated by trivalent bacterial vaccine (Table 3), suggesting that the TCR signaling pathway may be suppressed at the early stage of vaccination. The similar results were also found in other teleost fish [22, 34, 54, 55]. In zebrafish, expression of TCR pathway-related genes was found to decrease at 24 h following immunization with attenuated Edwardsiella tarda vaccine [54]. In half-smooth tongue sole (Cynoglossus semilaevis), TCR pathway was suppressed at 20 h after Vibrio anguillarum infection [55]. Expression levels of TCRα, β, and δ in tilapia (Oreochromis niloticus) were down-regulated by Streptococcus iniae at 24 h post-infection [22]. In our previous study, TCR pathway was also suppressed at 24 h after Aeromonas hydrophila infection in large yellow croaker [34]. However, the mechanism by which TCR pathway was suppressed at the early period of immunization with bacterial vaccine or bacterial infection remains unknown.

In conclusion, transcriptome analysis was utilized to investigate the early immune response of large yellow croaker to bacterial vaccine immunization. The most of strongly up-regulated genes are innate defense molecules, bacterial ligand—depending PRRs, inflammatory factors, and antigen processing related molecules, indicating that multiple innate immune processes and acquired immune initiation were activated at the early stage of vaccination in large yellow croaker. However, TCR signaling pathway was suppressed after vaccination. The findings observed in this study are similar to immune responses of large yellow croaker infected by live A. hydrophila, implying that inactivated vaccine has the similar effects on induction of host defense by bacterial infection. These results comprehensively reveal the early immune response in the large yellow croaker induced by trivalent vaccine and provide valuable information for developing a highly immunogenic vaccine in teleosts.

Supporting Information

S1 Fig. Agarose gel electrophoresis analysis of the specificity of primers.

https://doi.org/10.1371/journal.pone.0170958.s001

(PDF)

S1 Table. Primer sequences for real-time PCR.

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(DOC)

S2 Table. Details of all differentially expressed genes identified in the spleen transcriptomes of the large yellow croaker after vaccination.

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(XLS)

S3 Table. Gene Ontology classifications of all DEGs at 24 and 72 h after vaccination.

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(XLS)

S4 Table. KEGG mapping of all DEGs at 24 and 72 h after vaccination.

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(XLS)

Author Contributions

Conceptualization: XHC JQA YNM.
Formal analysis: XZ YNM.
Project administration: XHC JQA.
Resources: XZ YNM PFM JQA XHC.
Supervision: XHC JQA.
Validation: XZ YNM.
Visualization: XZ YNM.
Writing – original draft: XZ YNM XHC.
Writing – review & editing: XZ YNM.

References

1. Hong W, Zhang Q. Review of captive bred species and fry production of marine fish in China. Aquaculture. 2003;227(1–4):305–18.
- View Article
- Google Scholar
2. Yan Q, Wang J, Yuan SU, Jiao Z. Studies on Vibriosis in Caged-Cultured Pseudosciaena crocea (Richardson). J Jeimei Univ. 2001;6(3):191–6. [Abstract in English]
- View Article
- Google Scholar
3. Chen Q, Yan Q, Wang K, Zhuang Z, Wang X. Portal of entry for pathogenic Vibrio alginolyticus into large yellow croaker Pseudosciaena crocea, and characteristics of bacterial adhesion to mucus. Dis Aquat Organ. 2008;80(3):181–8. pmid:18814543
- View Article
- PubMed/NCBI
- Google Scholar
4. Cao J, Feng XZ, Feng ZB, Chang Y, Lei XU. Isolation and Identification of Aeromonas Hydrophila from Large Yellow Croaker. Hubei Agr Sci. 2007;46(5):808–10. [Abstract in English]
- View Article
- Google Scholar
5. Schjorring S, Krogfelt KA. Assessment of bacterial antibiotic resistance transfer in the gut. Int J Microbiol. 2011;2011:312956. PubMed Central PMCID: PMC3034945. pmid:21318188
- View Article
- PubMed/NCBI
- Google Scholar
6. Sommerset I, Krossoy B, Biering E, Frost P. Vaccines for fish in aquaculture. Expert Rev Vaccines. 2005;4(1):89–101. pmid:15757476
- View Article
- PubMed/NCBI
- Google Scholar
7. Villumsen KR, Neumann L, Ohtani M, Strom HK, Raida MK. Oral and anal vaccination confers full protection against enteric redmouth disease (ERM) in rainbow trout. PLoS One. 2014;9(4):e93845. PubMed Central PMCID: PMC3976340. pmid:24705460
- View Article
- PubMed/NCBI
- Google Scholar
8. Villumsen KR, Koppang EO, Raida MK. Adverse and long-term protective effects following oil-adjuvanted vaccination against Aeromonas salmonicida in rainbow trout. Fish Shellfish Immunol. 2015;42(1):193–203. pmid:25281580
- View Article
- PubMed/NCBI
- Google Scholar
9. Dec C, Angelidis P, Laurencin FB. Effects of oral vaccination against vibriosis in turbot, Scophthalmus maximus (L.), and sea bass, Dicentrarchus labrax (L.). J Fish Dis. 1990;13(5):369–76.
- View Article
- Google Scholar
10. Dan XM, Zhang TW, Li YW, Li AX. Immune responses and immune-related gene expression profile in orange-spotted grouper after immunization with Cryptocaryon irritans vaccine. Fish Shellfish Immunol. 2013;34(3):885–91. pmid:23291105
- View Article
- PubMed/NCBI
- Google Scholar
11. Martin SA, Blaney SC, Houlihan DF, Secombes CJ. Transcriptome response following administration of a live bacterial vaccine in Atlantic salmon (Salmo salar). Mol Immunol. 2006;43(11):1900–11. pmid:16313960
- View Article
- PubMed/NCBI
- Google Scholar
12. Yang D, Liu Q, Yang M, Wu H, Wang Q, Xiao J, et al. RNA-seq liver transcriptome analysis reveals an activated MHC-I pathway and an inhibited MHC-II pathway at the early stage of vaccine immunization in zebrafish. BMC Genomics. 2012;13(1):1.
- View Article
- Google Scholar
13. Caipang CMA, Brinchmann MF, Kiron V. Profiling gene expression in the spleen of Atlantic cod, Gadus morhua upon vaccination with Vibrio anguillarum antigen. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology. 2009;153(3):261–7.
- View Article
- Google Scholar
14. Wu Z, Wang S. Experimental study on immune protection of trivalent vaccine to common bacterial diseases of Pseudosciaena crocea. J Xiamen Univ. 2004;43(1):112–8. [Abstract in English]
- View Article
- Google Scholar
15. Zheng W, Tian C, Chen X. Molecular characterization of goose-type lysozyme homologue of large yellow croaker and its involvement in immune response induced by trivalent bacterial vaccine as an acute-phase protein. Immunol Lett. 2007;113(2):107–16. pmid:17850883
- View Article
- PubMed/NCBI
- Google Scholar
16. Mu Y, Xiao X, Zhang J, Ao J, Chen X. Molecular cloning and functional characterization of caspase 9 in large yellow croaker (Pseudosciaena crocea). Dev Comp Immunol. 2010;34(3):300–7. pmid:19887081
- View Article
- PubMed/NCBI
- Google Scholar
17. Ao J, Ding Y, Chen Y, Mu Y, Chen X. Molecular Characterization and Biological Effects of a C-Type Lectin-Like Receptor in Large Yellow Croaker (Larimichthys crocea). Int J Mol Sci. 2015;16(12):29631–42. PubMed Central PMCID: PMC4691118. pmid:26690423
- View Article
- PubMed/NCBI
- Google Scholar
18. Mu Y, Wang K, Ao J, Chen X. Molecular characterization and biological effects of a CXCL8 homologue in large yellow croaker (Larimichthys crocea). Fish Shellfish Immunol. 2015;44(2):462–70. pmid:25827624
- View Article
- PubMed/NCBI
- Google Scholar
19. Tian C, Chen YY, Ao JQ, Chen XH. Molecular characterization and bioactivity of a CXCL13 chemokine in large yellow croaker Pseudosciaena crocea. Fish Shellfish Immunol. 2010;28(3):445–52. pmid:20005294
- View Article
- PubMed/NCBI
- Google Scholar
20. Li S, Yang Z, Ao J, Chen X. Molecular and functional characterization of a novel stefin analogue in large yellow croaker (Pseudosciaena crocea). Dev Comp Immunol. 2009;33(12):1268–77. pmid:19651153
- View Article
- PubMed/NCBI
- Google Scholar
21. Ali Ali CER, Thorgaard Gary H., Yao Jianbo, Salem Mohamed. Characterization of the rainbow trout spleen transcriptome and identification of immune-related genes. Frontiers in Genetics. 2014;5(8):1027–35.
- View Article
- Google Scholar
22. Zhu J, Li C, Ao Q, Tan Y, Luo Y, Guo Y, et al. Trancriptomic profiling revealed the signatures of acute immune response in Tilapia (Oreochromis niloticus) following Streptococcus iniae challenge. Fish Shellfish Immunol. 2015;46(2):346–53. pmid:26117728
- View Article
- PubMed/NCBI
- Google Scholar
23. Ying Y, Hui Y, Hua L, Wang A. Transcriptome profiling of Grass carp (Ctenopharyngodon idellus) infected with Aeromonas hydrophila. Fish Shellfish Immunol. 2016;51:329–36. pmid:26945937
- View Article
- PubMed/NCBI
- Google Scholar
24. Ao J, Mu Y, Xiang LX, Fan D, Feng M, Zhang S, et al. Genome sequencing of the perciform fish Larimichthys crocea provides insights into molecular and genetic mechanisms of stress adaptation. PLoS Genet. 2015;11(4):e1005118. PubMed Central PMCID: PMC4383535. pmid:25835551
- View Article
- PubMed/NCBI
- Google Scholar
25. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–60. PubMed Central PMCID: PMC2705234. pmid:19451168
- View Article
- PubMed/NCBI
- Google Scholar
26. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. PubMed Central PMCID: PMC3322381. pmid:22388286
- View Article
- PubMed/NCBI
- Google Scholar
27. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323. PubMed Central PMCID: PMC3163565. pmid:21816040
- View Article
- PubMed/NCBI
- Google Scholar
28. Audic S, Claverie JM. The significance of digital gene expression profiles. Genome Res. 1997;7(10):986–95. pmid:9331369
- View Article
- PubMed/NCBI
- Google Scholar
29. Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–6. pmid:16081474
- View Article
- PubMed/NCBI
- Google Scholar
30. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008;3(6):1101–8. pmid:18546601
- View Article
- PubMed/NCBI
- Google Scholar
31. Tran NT, Gao ZX, Zhao HH, Yi SK, Chen BX, Zhao YH, et al. Transcriptome analysis and microsatellite discovery in the blunt snout bream (Megalobrama amblycephala) after challenge with Aeromonas hydrophila. Fish Shellfish Immunol. 2015;45(1):72–82. pmid:25681750
- View Article
- PubMed/NCBI
- Google Scholar
32. Rebl A, Korytar T, Kobis JM, Verleih M, Krasnov A, Jaros J, et al. Transcriptome profiling reveals insight into distinct immune responses to Aeromonas salmonicida in gill of two rainbow trout strains. Mar Biotechnol. 2014;16(3):333–48. pmid:24122123
- View Article
- PubMed/NCBI
- Google Scholar
33. Qi Z, Wu P, Zhang Q, Wei Y, Wang Z, Qiu M, et al. Transcriptome analysis of soiny mullet (Liza haematocheila) spleen in response to Streptococcus dysgalactiae. Fish Shellfish Immunol. 2016;49:194–204. pmid:26707943
- View Article
- PubMed/NCBI
- Google Scholar
34. Mu Y, Ding F, Cui P, Ao J, Hu S, Chen X. Transcriptome and expression profiling analysis revealed changes of multiple signaling pathways involved in immunity in the large yellow croaker during Aeromonas hydrophila infection. BMC Genomics. 2010;11:506. PubMed Central PMCID: PMC2997002. pmid:20858287
- View Article
- PubMed/NCBI
- Google Scholar
35. Whyte SK. The innate immune response of finfish--a review of current knowledge. Fish Shellfish Immunol. 2007;23(6):1127–51. pmid:17980622
- View Article
- PubMed/NCBI
- Google Scholar
36. Gomez GD, Balcazar JL. A review on the interactions between gut microbiota and innate immunity of fish. FEMS Immunol Med Microbiol. 2008;52(2):145–54. pmid:18081845
- View Article
- PubMed/NCBI
- Google Scholar
37. Wang H, Qi P, Guo B, Li J, He J, Wu C, et al. Molecular characterization and expression analysis of a complement component C3 in large yellow croaker (Larimichthys crocea). Fish Shellfish Immunol. 2015;42(2):272–9. pmid:25463300
- View Article
- PubMed/NCBI
- Google Scholar
38. Guo B, Wu C, Lv Z, Liu C. Characterisation and expression analysis of two terminal complement components: C7 and C9 from large yellow croaker, Larimichthys crocea. Fish Shellfish Immunol. 2016;51:211–9. pmid:26902705
- View Article
- PubMed/NCBI
- Google Scholar
39. Ewart K, Johnson S, Ross N. Lectins of the innate immune system and their relevance to fish health. ICES J Mar Sci. 2001;58(2):380–5.
- View Article
- Google Scholar
40. Ellison RT 3rd, Giehl TJ, LaForce FM. Damage of the outer membrane of enteric gram-negative bacteria by lactoferrin and transferrin. Infect Immun. 1988;56(11):2774–81. PubMed Central PMCID: PMC259649. pmid:3169987
- View Article
- PubMed/NCBI
- Google Scholar
41. Wang Y, Ao J, Chen X. Expression of large yellow croaker (Pseudosciana crocea) hepcidin in Pichia pastoris and antibacterial activity of the recombinant protein [J]. J Appl Oceanogr. 2013;32(3):383–9. [Abstract in English]
- View Article
- Google Scholar
42. Wei YC, Pan TS, Chang MX, Huang B, Xu Z, Luo TR, et al. Cloning and expression of Toll-like receptors 1 and 2 from a teleost fish, the orange-spotted grouper Epinephelus coioides. Vet Immunol Immunopathol. 2011;141(3–4):173–82. pmid:21440311
- View Article
- PubMed/NCBI
- Google Scholar
43. Basu M, Swain B, Maiti NK, Routray P, Samanta M. Inductive expression of toll-like receptor 5 (TLR5) and associated downstream signaling molecules following ligand exposure and bacterial infection in the Indian major carp, mrigal (Cirrhinus mrigala). Fish Shellfish Immunol. 2012;32(1):121–31. pmid:22085689
- View Article
- PubMed/NCBI
- Google Scholar
44. Barton GM, Medzhitov R. Toll-like receptor signaling pathways. Science. 2003;300(5625):1524–5. pmid:12791976
- View Article
- PubMed/NCBI
- Google Scholar
45. Dinarello CA. Interleukin-1 beta, interleukin-18, and the interleukin-1 beta converting enzyme. Ann N Y Acad Sci. 1998;856:1–11. pmid:9917859
- View Article
- PubMed/NCBI
- Google Scholar
46. Laing KJ, Purcell MK, Winton JR, Hansen JD. A genomic view of the NOD-like receptor family in teleost fish: identification of a novel NLR subfamily in zebrafish. BMC Evol Biol. 2008;8:42. PubMed Central PMCID: PMC2268669. pmid:18254971
- View Article
- PubMed/NCBI
- Google Scholar
47. Compan V, Baroja-Mazo A, Lopez-Castejon G, Gomez AI, Martinez CM, Angosto D, et al. Cell volume regulation modulates NLRP3 inflammasome activation. Immunity. 2012;37(3):487–500. pmid:22981536
- View Article
- PubMed/NCBI
- Google Scholar
48. Reimann J, Kaufmann SH. Alternative antigen processing pathways in anti-infective immunity. Curr Opin Immunol. 1997;9(4):462–9. pmid:9287179
- View Article
- PubMed/NCBI
- Google Scholar
49. Mellman I, Cresswell P. Antigen processing and presentation. Curr Opin Immunol. 2010;22(1):78–80. pmid:20172702
- View Article
- PubMed/NCBI
- Google Scholar
50. Potter NS, Harding CV. Neutrophils process exogenous bacteria via an alternate class I MHC processing pathway for presentation of peptides to T lymphocytes. J Immunol. 2001;167(5):2538–46. pmid:11509593
- View Article
- PubMed/NCBI
- Google Scholar
51. Campbell DJ, Serwold T, Shastri N. Bacterial proteins can be processed by macrophages in a transporter associated with antigen processing-independent, cysteine protease-dependent manner for presentation by MHC class I molecules. J Immunol. 2000;164(1):168–75. pmid:10605008
- View Article
- PubMed/NCBI
- Google Scholar
52. Dijkstra JM, Fischer U, Sawamoto Y, Ototake M, Nakanishi T. Exogenous antigens and the stimulation of MHC class I restricted cell-mediated cytotoxicity: possible strategies for fish vaccines. Fish Shellfish Immunol. 2001;11(6):437–58. pmid:11556476
- View Article
- PubMed/NCBI
- Google Scholar
53. Watts C. Capture and processing of exogenous antigens for presentation on MHC molecules. Annu Rev Immunol. 1997;15:821–50. pmid:9143708
- View Article
- PubMed/NCBI
- Google Scholar
54. Yang D, Liu Q, Ni C, Li S, Wu H, Wang Q, et al. Gene expression profiling in live attenuated Edwardsiella tarda vaccine immunized and challenged zebrafish: insights into the basic mechanisms of protection seen in immunized fish. Dev Comp Immunol. 2013;40(2):132–41. pmid:23434462
- View Article
- PubMed/NCBI
- Google Scholar
55. Zhang X, Wang S, Chen S, Chen Y, Liu Y, Shao C, et al. Transcriptome analysis revealed changes of multiple genes involved in immunity in Cynoglossus semilaevis during Vibrio anguillarum infection. Fish Shellfish Immunol. 2015;43(1):209–18. pmid:25543033
- View Article
- PubMed/NCBI
- Google Scholar
56. Vojtech LN, Scharping N, Woodson JC, Hansen JD. Roles of inflammatory caspases during processing of zebrafish interleukin-1β in Francisella noatunensis infection. Infect Immun. 2012;80(8):2878–85. pmid:22689811
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Hong W, Zhang Q. Review of captive bred species and fry production of marine fish in China. Aquaculture. 2003;227(1–4):305–18.
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. Yan Q, Wang J, Yuan SU, Jiao Z. Studies on Vibriosis in Caged-Cultured Pseudosciaena crocea (Richardson). J Jeimei Univ. 2001;6(3):191–6. [Abstract in English]
View Article
Google Scholar

[5] View Article

[6] Google Scholar

[ref3] 3. Chen Q, Yan Q, Wang K, Zhuang Z, Wang X. Portal of entry for pathogenic Vibrio alginolyticus into large yellow croaker Pseudosciaena crocea, and characteristics of bacterial adhesion to mucus. Dis Aquat Organ. 2008;80(3):181–8. pmid:18814543
View Article
PubMed/NCBI
Google Scholar

[8] View Article

[9] PubMed/NCBI

[10] Google Scholar

[ref4] 4. Cao J, Feng XZ, Feng ZB, Chang Y, Lei XU. Isolation and Identification of Aeromonas Hydrophila from Large Yellow Croaker. Hubei Agr Sci. 2007;46(5):808–10. [Abstract in English]
View Article
Google Scholar

[12] View Article

[13] Google Scholar

[ref5] 5. Schjorring S, Krogfelt KA. Assessment of bacterial antibiotic resistance transfer in the gut. Int J Microbiol. 2011;2011:312956. PubMed Central PMCID: PMC3034945. pmid:21318188
View Article
PubMed/NCBI
Google Scholar

[15] View Article

[16] PubMed/NCBI

[17] Google Scholar

[ref6] 6. Sommerset I, Krossoy B, Biering E, Frost P. Vaccines for fish in aquaculture. Expert Rev Vaccines. 2005;4(1):89–101. pmid:15757476
View Article
PubMed/NCBI
Google Scholar

[19] View Article

[20] PubMed/NCBI

[21] Google Scholar

[ref7] 7. Villumsen KR, Neumann L, Ohtani M, Strom HK, Raida MK. Oral and anal vaccination confers full protection against enteric redmouth disease (ERM) in rainbow trout. PLoS One. 2014;9(4):e93845. PubMed Central PMCID: PMC3976340. pmid:24705460
View Article
PubMed/NCBI
Google Scholar

[23] View Article

[24] PubMed/NCBI

[25] Google Scholar

[ref8] 8. Villumsen KR, Koppang EO, Raida MK. Adverse and long-term protective effects following oil-adjuvanted vaccination against Aeromonas salmonicida in rainbow trout. Fish Shellfish Immunol. 2015;42(1):193–203. pmid:25281580
View Article
PubMed/NCBI
Google Scholar

[27] View Article

[28] PubMed/NCBI

[29] Google Scholar

[ref9] 9. Dec C, Angelidis P, Laurencin FB. Effects of oral vaccination against vibriosis in turbot, Scophthalmus maximus (L.), and sea bass, Dicentrarchus labrax (L.). J Fish Dis. 1990;13(5):369–76.
View Article
Google Scholar

[31] View Article

[32] Google Scholar

[ref10] 10. Dan XM, Zhang TW, Li YW, Li AX. Immune responses and immune-related gene expression profile in orange-spotted grouper after immunization with Cryptocaryon irritans vaccine. Fish Shellfish Immunol. 2013;34(3):885–91. pmid:23291105
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref11] 11. Martin SA, Blaney SC, Houlihan DF, Secombes CJ. Transcriptome response following administration of a live bacterial vaccine in Atlantic salmon (Salmo salar). Mol Immunol. 2006;43(11):1900–11. pmid:16313960
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref12] 12. Yang D, Liu Q, Yang M, Wu H, Wang Q, Xiao J, et al. RNA-seq liver transcriptome analysis reveals an activated MHC-I pathway and an inhibited MHC-II pathway at the early stage of vaccine immunization in zebrafish. BMC Genomics. 2012;13(1):1.
View Article
Google Scholar

[42] View Article

[43] Google Scholar

[ref13] 13. Caipang CMA, Brinchmann MF, Kiron V. Profiling gene expression in the spleen of Atlantic cod, Gadus morhua upon vaccination with Vibrio anguillarum antigen. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology. 2009;153(3):261–7.
View Article
Google Scholar

[45] View Article

[46] Google Scholar

[ref14] 14. Wu Z, Wang S. Experimental study on immune protection of trivalent vaccine to common bacterial diseases of Pseudosciaena crocea. J Xiamen Univ. 2004;43(1):112–8. [Abstract in English]
View Article
Google Scholar

[48] View Article

[49] Google Scholar

[ref15] 15. Zheng W, Tian C, Chen X. Molecular characterization of goose-type lysozyme homologue of large yellow croaker and its involvement in immune response induced by trivalent bacterial vaccine as an acute-phase protein. Immunol Lett. 2007;113(2):107–16. pmid:17850883
View Article
PubMed/NCBI
Google Scholar

[51] View Article

[52] PubMed/NCBI

[53] Google Scholar

[ref16] 16. Mu Y, Xiao X, Zhang J, Ao J, Chen X. Molecular cloning and functional characterization of caspase 9 in large yellow croaker (Pseudosciaena crocea). Dev Comp Immunol. 2010;34(3):300–7. pmid:19887081
View Article
PubMed/NCBI
Google Scholar

[55] View Article

[56] PubMed/NCBI

[57] Google Scholar

[ref17] 17. Ao J, Ding Y, Chen Y, Mu Y, Chen X. Molecular Characterization and Biological Effects of a C-Type Lectin-Like Receptor in Large Yellow Croaker (Larimichthys crocea). Int J Mol Sci. 2015;16(12):29631–42. PubMed Central PMCID: PMC4691118. pmid:26690423
View Article
PubMed/NCBI
Google Scholar

[59] View Article

[60] PubMed/NCBI

[61] Google Scholar

[ref18] 18. Mu Y, Wang K, Ao J, Chen X. Molecular characterization and biological effects of a CXCL8 homologue in large yellow croaker (Larimichthys crocea). Fish Shellfish Immunol. 2015;44(2):462–70. pmid:25827624
View Article
PubMed/NCBI
Google Scholar

[63] View Article

[64] PubMed/NCBI

[65] Google Scholar

[ref19] 19. Tian C, Chen YY, Ao JQ, Chen XH. Molecular characterization and bioactivity of a CXCL13 chemokine in large yellow croaker Pseudosciaena crocea. Fish Shellfish Immunol. 2010;28(3):445–52. pmid:20005294
View Article
PubMed/NCBI
Google Scholar

[67] View Article

[68] PubMed/NCBI

[69] Google Scholar

[ref20] 20. Li S, Yang Z, Ao J, Chen X. Molecular and functional characterization of a novel stefin analogue in large yellow croaker (Pseudosciaena crocea). Dev Comp Immunol. 2009;33(12):1268–77. pmid:19651153
View Article
PubMed/NCBI
Google Scholar

[71] View Article

[72] PubMed/NCBI

[73] Google Scholar

[ref21] 21. Ali Ali CER, Thorgaard Gary H., Yao Jianbo, Salem Mohamed. Characterization of the rainbow trout spleen transcriptome and identification of immune-related genes. Frontiers in Genetics. 2014;5(8):1027–35.
View Article
Google Scholar

[75] View Article

[76] Google Scholar

[ref22] 22. Zhu J, Li C, Ao Q, Tan Y, Luo Y, Guo Y, et al. Trancriptomic profiling revealed the signatures of acute immune response in Tilapia (Oreochromis niloticus) following Streptococcus iniae challenge. Fish Shellfish Immunol. 2015;46(2):346–53. pmid:26117728
View Article
PubMed/NCBI
Google Scholar

[78] View Article

[79] PubMed/NCBI

[80] Google Scholar

[ref23] 23. Ying Y, Hui Y, Hua L, Wang A. Transcriptome profiling of Grass carp (Ctenopharyngodon idellus) infected with Aeromonas hydrophila. Fish Shellfish Immunol. 2016;51:329–36. pmid:26945937
View Article
PubMed/NCBI
Google Scholar

[82] View Article

[83] PubMed/NCBI

[84] Google Scholar

[ref24] 24. Ao J, Mu Y, Xiang LX, Fan D, Feng M, Zhang S, et al. Genome sequencing of the perciform fish Larimichthys crocea provides insights into molecular and genetic mechanisms of stress adaptation. PLoS Genet. 2015;11(4):e1005118. PubMed Central PMCID: PMC4383535. pmid:25835551
View Article
PubMed/NCBI
Google Scholar

[86] View Article

[87] PubMed/NCBI

[88] Google Scholar

[ref25] 25. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–60. PubMed Central PMCID: PMC2705234. pmid:19451168
View Article
PubMed/NCBI
Google Scholar

[90] View Article

[91] PubMed/NCBI

[92] Google Scholar

[ref26] 26. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. PubMed Central PMCID: PMC3322381. pmid:22388286
View Article
PubMed/NCBI
Google Scholar

[94] View Article

[95] PubMed/NCBI

[96] Google Scholar

[ref27] 27. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323. PubMed Central PMCID: PMC3163565. pmid:21816040
View Article
PubMed/NCBI
Google Scholar

[98] View Article

[99] PubMed/NCBI

[100] Google Scholar

[ref28] 28. Audic S, Claverie JM. The significance of digital gene expression profiles. Genome Res. 1997;7(10):986–95. pmid:9331369
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref29] 29. Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21(18):3674–6. pmid:16081474
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref30] 30. Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc. 2008;3(6):1101–8. pmid:18546601
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref31] 31. Tran NT, Gao ZX, Zhao HH, Yi SK, Chen BX, Zhao YH, et al. Transcriptome analysis and microsatellite discovery in the blunt snout bream (Megalobrama amblycephala) after challenge with Aeromonas hydrophila. Fish Shellfish Immunol. 2015;45(1):72–82. pmid:25681750
View Article
PubMed/NCBI
Google Scholar

[114] View Article

[115] PubMed/NCBI

[116] Google Scholar

[ref32] 32. Rebl A, Korytar T, Kobis JM, Verleih M, Krasnov A, Jaros J, et al. Transcriptome profiling reveals insight into distinct immune responses to Aeromonas salmonicida in gill of two rainbow trout strains. Mar Biotechnol. 2014;16(3):333–48. pmid:24122123
View Article
PubMed/NCBI
Google Scholar

[118] View Article

[119] PubMed/NCBI

[120] Google Scholar

[ref33] 33. Qi Z, Wu P, Zhang Q, Wei Y, Wang Z, Qiu M, et al. Transcriptome analysis of soiny mullet (Liza haematocheila) spleen in response to Streptococcus dysgalactiae. Fish Shellfish Immunol. 2016;49:194–204. pmid:26707943
View Article
PubMed/NCBI
Google Scholar

[122] View Article

[123] PubMed/NCBI

[124] Google Scholar

[ref34] 34. Mu Y, Ding F, Cui P, Ao J, Hu S, Chen X. Transcriptome and expression profiling analysis revealed changes of multiple signaling pathways involved in immunity in the large yellow croaker during Aeromonas hydrophila infection. BMC Genomics. 2010;11:506. PubMed Central PMCID: PMC2997002. pmid:20858287
View Article
PubMed/NCBI
Google Scholar

[126] View Article

[127] PubMed/NCBI

[128] Google Scholar

[ref35] 35. Whyte SK. The innate immune response of finfish--a review of current knowledge. Fish Shellfish Immunol. 2007;23(6):1127–51. pmid:17980622
View Article
PubMed/NCBI
Google Scholar

[130] View Article

[131] PubMed/NCBI

[132] Google Scholar

[ref36] 36. Gomez GD, Balcazar JL. A review on the interactions between gut microbiota and innate immunity of fish. FEMS Immunol Med Microbiol. 2008;52(2):145–54. pmid:18081845
View Article
PubMed/NCBI
Google Scholar

[134] View Article

[135] PubMed/NCBI

[136] Google Scholar

[ref37] 37. Wang H, Qi P, Guo B, Li J, He J, Wu C, et al. Molecular characterization and expression analysis of a complement component C3 in large yellow croaker (Larimichthys crocea). Fish Shellfish Immunol. 2015;42(2):272–9. pmid:25463300
View Article
PubMed/NCBI
Google Scholar

[138] View Article

[139] PubMed/NCBI

[140] Google Scholar

[ref38] 38. Guo B, Wu C, Lv Z, Liu C. Characterisation and expression analysis of two terminal complement components: C7 and C9 from large yellow croaker, Larimichthys crocea. Fish Shellfish Immunol. 2016;51:211–9. pmid:26902705
View Article
PubMed/NCBI
Google Scholar

[142] View Article

[143] PubMed/NCBI

[144] Google Scholar

[ref39] 39. Ewart K, Johnson S, Ross N. Lectins of the innate immune system and their relevance to fish health. ICES J Mar Sci. 2001;58(2):380–5.
View Article
Google Scholar

[146] View Article

[147] Google Scholar

[ref40] 40. Ellison RT 3rd, Giehl TJ, LaForce FM. Damage of the outer membrane of enteric gram-negative bacteria by lactoferrin and transferrin. Infect Immun. 1988;56(11):2774–81. PubMed Central PMCID: PMC259649. pmid:3169987
View Article
PubMed/NCBI
Google Scholar

[149] View Article

[150] PubMed/NCBI

[151] Google Scholar

[ref41] 41. Wang Y, Ao J, Chen X. Expression of large yellow croaker (Pseudosciana crocea) hepcidin in Pichia pastoris and antibacterial activity of the recombinant protein [J]. J Appl Oceanogr. 2013;32(3):383–9. [Abstract in English]
View Article
Google Scholar

[153] View Article

[154] Google Scholar

[ref42] 42. Wei YC, Pan TS, Chang MX, Huang B, Xu Z, Luo TR, et al. Cloning and expression of Toll-like receptors 1 and 2 from a teleost fish, the orange-spotted grouper Epinephelus coioides. Vet Immunol Immunopathol. 2011;141(3–4):173–82. pmid:21440311
View Article
PubMed/NCBI
Google Scholar

[156] View Article

[157] PubMed/NCBI

[158] Google Scholar

[ref43] 43. Basu M, Swain B, Maiti NK, Routray P, Samanta M. Inductive expression of toll-like receptor 5 (TLR5) and associated downstream signaling molecules following ligand exposure and bacterial infection in the Indian major carp, mrigal (Cirrhinus mrigala). Fish Shellfish Immunol. 2012;32(1):121–31. pmid:22085689
View Article
PubMed/NCBI
Google Scholar

[160] View Article

[161] PubMed/NCBI

[162] Google Scholar

[ref44] 44. Barton GM, Medzhitov R. Toll-like receptor signaling pathways. Science. 2003;300(5625):1524–5. pmid:12791976
View Article
PubMed/NCBI
Google Scholar

[164] View Article

[165] PubMed/NCBI

[166] Google Scholar

[ref45] 45. Dinarello CA. Interleukin-1 beta, interleukin-18, and the interleukin-1 beta converting enzyme. Ann N Y Acad Sci. 1998;856:1–11. pmid:9917859
View Article
PubMed/NCBI
Google Scholar

[168] View Article

[169] PubMed/NCBI

[170] Google Scholar

[ref46] 46. Laing KJ, Purcell MK, Winton JR, Hansen JD. A genomic view of the NOD-like receptor family in teleost fish: identification of a novel NLR subfamily in zebrafish. BMC Evol Biol. 2008;8:42. PubMed Central PMCID: PMC2268669. pmid:18254971
View Article
PubMed/NCBI
Google Scholar

[172] View Article

[173] PubMed/NCBI

[174] Google Scholar

[ref47] 47. Compan V, Baroja-Mazo A, Lopez-Castejon G, Gomez AI, Martinez CM, Angosto D, et al. Cell volume regulation modulates NLRP3 inflammasome activation. Immunity. 2012;37(3):487–500. pmid:22981536
View Article
PubMed/NCBI
Google Scholar

[176] View Article

[177] PubMed/NCBI

[178] Google Scholar

[ref48] 48. Reimann J, Kaufmann SH. Alternative antigen processing pathways in anti-infective immunity. Curr Opin Immunol. 1997;9(4):462–9. pmid:9287179
View Article
PubMed/NCBI
Google Scholar

[180] View Article

[181] PubMed/NCBI

[182] Google Scholar

[ref49] 49. Mellman I, Cresswell P. Antigen processing and presentation. Curr Opin Immunol. 2010;22(1):78–80. pmid:20172702
View Article
PubMed/NCBI
Google Scholar

[184] View Article

[185] PubMed/NCBI

[186] Google Scholar

[ref50] 50. Potter NS, Harding CV. Neutrophils process exogenous bacteria via an alternate class I MHC processing pathway for presentation of peptides to T lymphocytes. J Immunol. 2001;167(5):2538–46. pmid:11509593
View Article
PubMed/NCBI
Google Scholar

[188] View Article

[189] PubMed/NCBI

[190] Google Scholar

[ref51] 51. Campbell DJ, Serwold T, Shastri N. Bacterial proteins can be processed by macrophages in a transporter associated with antigen processing-independent, cysteine protease-dependent manner for presentation by MHC class I molecules. J Immunol. 2000;164(1):168–75. pmid:10605008
View Article
PubMed/NCBI
Google Scholar

[192] View Article

[193] PubMed/NCBI

[194] Google Scholar

[ref52] 52. Dijkstra JM, Fischer U, Sawamoto Y, Ototake M, Nakanishi T. Exogenous antigens and the stimulation of MHC class I restricted cell-mediated cytotoxicity: possible strategies for fish vaccines. Fish Shellfish Immunol. 2001;11(6):437–58. pmid:11556476
View Article
PubMed/NCBI
Google Scholar

[196] View Article

[197] PubMed/NCBI

[198] Google Scholar

[ref53] 53. Watts C. Capture and processing of exogenous antigens for presentation on MHC molecules. Annu Rev Immunol. 1997;15:821–50. pmid:9143708
View Article
PubMed/NCBI
Google Scholar

[200] View Article

[201] PubMed/NCBI

[202] Google Scholar

[ref54] 54. Yang D, Liu Q, Ni C, Li S, Wu H, Wang Q, et al. Gene expression profiling in live attenuated Edwardsiella tarda vaccine immunized and challenged zebrafish: insights into the basic mechanisms of protection seen in immunized fish. Dev Comp Immunol. 2013;40(2):132–41. pmid:23434462
View Article
PubMed/NCBI
Google Scholar

[204] View Article

[205] PubMed/NCBI

[206] Google Scholar

[ref55] 55. Zhang X, Wang S, Chen S, Chen Y, Liu Y, Shao C, et al. Transcriptome analysis revealed changes of multiple genes involved in immunity in Cynoglossus semilaevis during Vibrio anguillarum infection. Fish Shellfish Immunol. 2015;43(1):209–18. pmid:25543033
View Article
PubMed/NCBI
Google Scholar

[208] View Article

[209] PubMed/NCBI

[210] Google Scholar

[ref56] 56. Vojtech LN, Scharping N, Woodson JC, Hansen JD. Roles of inflammatory caspases during processing of zebrafish interleukin-1β in Francisella noatunensis infection. Infect Immun. 2012;80(8):2878–85. pmid:22689811
View Article
PubMed/NCBI
Google Scholar

[212] View Article

[213] PubMed/NCBI

[214] Google Scholar

Figures

Abstract

Introduction

Materials and Methods

Ethics statement

Inactivated trivalent bacterial vaccine and fish samples

RNA extraction, library preparation, and sequencing

Identification of the differentially expressed genes

Gene ontology and kyoto encyclopedia of genes and genomes (KEGG) analysis

Quantitative real-time PCR

Results

Sequence analysis of the transcriptomes

Analysis of differential expression genes

Gene ontology and KEGG enrichment analysis of DEGs

Annotation of immune-relevant genes

Verification of the expression changes of partial immune-relevant genes

Discussion

Supporting Information

S1 Fig. Agarose gel electrophoresis analysis of the specificity of primers.

S1 Table. Primer sequences for real-time PCR.

S2 Table. Details of all differentially expressed genes identified in the spleen transcriptomes of the large yellow croaker after vaccination.

S3 Table. Gene Ontology classifications of all DEGs at 24 and 72 h after vaccination.

S4 Table. KEGG mapping of all DEGs at 24 and 72 h after vaccination.

Author Contributions

References