Differentially expressed genes in head kidney of Pelteobagrus fulvidraco following Vibrio cholerae challenge

The yellow catfish (Pelteobagrus fulvidraco) is a freshwater fish with high economic value in eastern China. Nevertheless, pathogens causing bacterial diseases in P. fulvidraco have brought about huge economic loss and high mortality in artificial aquaculture. For disease control, it is critical to further understand the immune system of yellow catfish and immune-related genes with which they respond to pathogenic infections. In this study, high-throughput sequencing methods were used to analyze the transcriptomic spectrum of the head kidney from P. fulvidraco challenged by Vibrio cholera. A total of 45,544 unique transcript fragments (unigenes) were acquired after assembly and annotation, with an average length of 1,373 bp. Additionally, 674 differentially expressed genes (DEGs) were identified after stimulation with V. cholerae, 353 and 321 genes were identified as remarkably up- or downregulated, respectively. To further study the immune-related DEGs, we performed KEGG enrichment and GO enrichment. The results showed gene regulation of response to stimulus, immune response, immune system progress, response to external stimuli and cellular response to stimuli. Analysis of KEGG enrichment is important to identify chief immune related pathways. Real-time quantitative reverse transcription-PCR (qRT-PCR) results indicated 10 immune response genes that were found to be upregulated compared to a control group after 6 h of V. cholerae challenging. In summary, the results of our study are helpful to determine the defense mechanisms and immune system responses of yellow catfish in reaction to bacterial challenges.

Introduction

Yellow catfish has been extensively farmed and is an economically significant freshwater species in China, South Korea, Japan, and South Asia (1–3). The popularity of this species has rapidly increased recently because of its tender flesh, few bones, and good taste (4, 5). Consequently, the market demand for yellow catfish in China is very large, and its price very high. In recent years, the rapid growth of P. fulvidraco aquaculture has caused a huge decline in their population due to microbial disease, including viruses, parasites, and bacteria, which has brought about huge economic losses (6). However, little is known about the molecular mechanisms relevant to immunity. Recently, P. fulvidraco has been employed as an experimental model fish to investigate breeding techniques, development, lipid metabolism, immunology and toxicology (7–11). Vibrio cholerae, is an aquatic, gram-negative bacterium, which is responsible for pandemics of cholera disease worldwide (12). To decrease the danger of aquaculture, understanding molecular defense mechanisms of yellow catfish against microbial diseases is indispensable to establish reasonable control measures.

High-throughput RNA-sequencing (RNA-Seq) is a low-cost technique with high sensitivity, wide genome coverage, and unbiased quantification of transcript expression which is a relatively new technique that allows transcriptome analysis (13). Transcriptome analysis is widely used in genome research and functional gene identification, particularly for understanding hereditary responses to pathogens (14). In addition, transcriptome research has been increasingly applied to many fields of research including physiology, ecology, evolution and genetics, and has been critical for gene expression analysis, genetic marker mining, and gene discovery in many species (15). Recently, a variety of comparative transcriptomic studies focusing on fish immune responses after exposure to microbial pathogens were performed, such as in crucian carp (16), rainbow trout (17), half-smooth tongue sole (18), blunt snout bream (19), tilapia (20), soiny mullet (21), and miiuy croaker (22).

In this study, based on the head kidney of P. fulvidraco from PBS-control and V. cholerae infected groups, we established two transcriptome sequence libraries. Similar to the mammalian adrenal gland, the head kidney is an important endocrine and haematopoietic-lymphoid organ which is unique for teleost fish and participates in innate immune responses to pathogen infections (23). By comparison among the libraries, differentially expressed genes (DEGs) were recognized. Through gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, these DEGs were enriched and the immune-related DEGs were identified that maybe provide insights into the potential molecular immune mechanisms of P. fulvidraco.

Materials and methods

Experimental fish models

Yellow catfish were collected from the aquatic market, Yancheng, Jiangsu Province, China, in October 2020 and were acclimatized in tanks at 24°C for two weeks before the experiment commenced. The fish were then divided into two groups, each containing three fish: a control group and the V. cholerae group. The control group was injected with 100 µL PBS whilst the V. cholerae group were injected with the same dose of bacterial suspension that had a final concentration of 1 × 10⁷ CFU/mL and were treated as the experimental group. The head kidneys were gathered 6 h after injection and stored at -80°C.

RNA extraction, library construction and Illumina sequencing

Library constructions were performed at the Novogene Experimental Department (Beijing, China). RNA -easy isolation reagent (Vazyme, China) was used to extract the total RNA content of the head kidney. RNA degradation, purity, and contamination were measured by 1% agarose gels, NanoPhotometer^® spectrophotometer (IMPLEN, CA, USA), and Qubit^® 2.0 Fluorometer. RNA integrity was evaluated by the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA). We made use of the NEBNext^® Ultra™ RNA Library Prep Kit for Illumina^® (NEB, USA) to generate sequencing libraries. Random hexamers primers and M-MuLV were utilized for first strand cDNA synthesis, using DNA Polymerase I and RNase H for synthesis of the second strand. Purification of the PCR products involved the following steps: purification, adapter addition, and cDNA fragment selection, and PCR by universal PCR primers and Index (X) Primers. Finally, the insert size of the library from the libraries was sequenced using an Illumina HiSeq platform at Novogene.

Sequencing data processing and assembly

Through in-house Perl scripts, we first processed raw reads of FASTA formatted sequences. In this procedure, by deleting reads such as those generated by adapters, clean reads were obtained, consisting of poly-N and low-quality reads from raw reads. Then, to obtain the reference sequence for subsequent analysis, we concatenated the clean reads. By using Trinity software, the compilation of de novo transcriptome data was executed by three independent components: Butterfly, Chrysalis, and Inchworm (24). Finally, the longissimus transcript of every gene was named unigenes. Meanwhile, based on clean reads with high quality, Q-value 20, Q-value 30, GC-content, and sequence duplication level of the clean reads were calculated.

Unigenes annotation and functional enrichment

Unigenes were annotated by comparison to seven databases and processed by BLAST. The databases included: NT (NCBI non-redundant nucleotide sequences, e-value=1e-5), NR (NCBI non-redundant protein database, e-value=1e-5), Eukaryotic Orthologous Groups (KOG/COG) (http://www.ncbi.nlm.nih.gov/COG/, e-value=1e-3), Pfam (http://pfam.sanger.ac.uk/, e-value=0.01), GO (http://www.geneontology.org/, e-value=1e-6) (25), KEGG (http://www.genome.jp/kegg, e-value=1e-10), and Swiss-prot (http://www.ebi.ac.uk/uniprot/, e-value=1e-5). GO annotation of unigenes was derived from NR annotation by the Blast2GO program, and WEGO software was used to perform GO functional classification (26). Pathway assignments were executed using the KEGG database (27).

Identification of DEGs

To estimate DEGs between two datasets, expression levels of unigenes were calculated using the FPKM method, the universal method for detecting gene expression (28). For the sake of calculating the expression profiles between PBS and V. cholerae-injected head kidney tissues, we made use of RSEM software to map the clean data (29). We obtained a read count for each gene from the mapping results. Before DEGs analysis, all read counts were normalized using edgeR (30). DEGs analysis of two libraries was carried out using the DEGseq R package (31). The p-value was adjusted according to the q-value. Q-value<0.005 and |log₂(fold change)|>1 were assigned as differential expression genes. Then DEGs were subjected to KEGG pathway analysis and GO functional enrichment analysis. By Wallenius noncentral hypergeometric distribution, we employed GOseqR to implement GO enrichment analysis of DEGs, which can be adjusted for gene length bias in DEGs (32). KOBAS software was used to test the statistical enrichment of DEGs in the KEGG pathway (33).

qRT-PCR of candidate gene expression

qRT-PCR was employed to check the expression level of the 10 candidate DEGs. Following the manufacturer’s instructions, MightyScript Plus First Strand cDNA Synthesis Master Mix (gDNA digester) (Sangon, China) was used to produce synthesized cDNA that acted as a template for qRT-PCR. Primer premier 5.0 software was then used to design candidate DEGs primers with reference to the cDNA sequence. The β-actin gene from P. fulvidraco was used as an internal reference. The sequences of PCR primers are shown in Table 1. By using Mastercycler ep realplex (Eppendorf, Germany) with the AceQ Universal SYBR qPCR Master Mix (Vazyme, China), qRT-PCR was performed in 20 µl reaction mixtures consisting of 10 µl 2×SYBR Green mix, 1 µl cDNA, 7 µl RNase-free H₂O, and 1 µl forward and reverse primers. The steps of PCR were as follows: 20 s at 95°C, followed by 40 cycles of 15 s at 95°C and 15 s at 55°C, then at 72°C 20 s and 60°C for 1 min. Each independent experiment was performed in triplicate and determined the relative expression levels of the genes which was calculated with the 2^-△△CT comparative threshold cycle (Ct) method (34).

TABLE 1

Table 1 Primers used for qRT-PCR in this paper.

Statistical analysis

Statistical analysis was used to examine the differences of mRNA expression levels and performed using the statistical software SPSS 17.0 and p<0.05 results were considered significant. All quantitative data were expressed as means ± SD at least three independent experiments.

Results and discussion

Sequencing and de novo assembly

To acquire the transcriptomic analysis data of the P. fulvidraco head kidney following injection of V. cholerae, we employed Illumina HiSeq sequencing platform to construct two libraries, and the results are summarized in Table 2 (13). Approximately, 53,492,522 and 47,733,280 clean reads were noted from the yellow catfish head kidney in V. cholerae challenged and PBS-challenged fish. Each sample had a quality score over 96% and 91% with Q-value 20 and Q-value 30, respectively, and that the GC content of each library was approximately equal (44%). We spliced all the clean data into 135,097 transcripts (total length of 226,790,028) with a mean length of 1,697, N50 length of 2,854, and N90 length of 677 (Table 3). We further assembled 45,544 unigenes (total length of 62,537,256) with an average length of 1,373, N50 length of 1,439, and N90 length of 536. These results show that the transcriptome data were reliable, and the sequence data were high-quality.

TABLE 2

Table 2 The quality of raw and clean reads.

TABLE 3

Table 3 Distribution of splicing length.

After assembly, the length of unigenes extended from 301 bp to 19,263 bp with a length of 1,373 bp on average. The length of assembled unigenes indicated that 12,679 of unigenes extended from 300 bp to 500 bp, 15,482 of unigenes extended from 500 bp to 1000 bp, 7,917 of unigenes extended from 1,000 bp to 2,000 bp, and 9,466 of unigenes were more than 2,000 bp. In addition, the length of transcripts showed that 30,391 transcripts ranged from 500 bp to 1,000 bp, 36,228 of transcripts ranged from 300 bp to 500 bp, 28,521 of transcripts ranged from 1,000 bp to 2,000 bp, and 39,957 of transcripts exceeded 2,000 bp (Figure 1).

FIGURE 1

Figure 1 The line plot shows the sequence length distribution of the unigenes and transcripts.

Annotation of assembled unigenes

To gain a comprehensive view of gene function information, 45,544 unigenes were annotated by seven databases including NR, NT, Swiss-Port, KOG, PFAM, GO, and KO (35). Of these unigenes, 29,004 unigenes (63.68%) were annotated in one database at least, and 5,544 unigenes (12.17%) were constructed in all databases. The number of unigenes that may be annotated in diverse databases was 24,521 in NR (53.84%), 20,034 in NT (43.98%), 11,300 in KO (24.81%), 16,032 in Swiss-Prot (35.20%), 17,372 in PFAM (38.14%), 17,372 in GO (38.14%), and 7,878 in KOG (17.29%) (Figures 2, 3 and Table 4).

FIGURE 2

Figure 2 Annotated unigenes in seven databases.

FIGURE 3

Figure 3 Map of species distribution in the NR database.

TABLE 4

Table 4 Statistics of annotation.

Using a BLAST search compared to the NR database, matching these unigenes by species classification revealed that the number of hits between P. fulvidraco and Ictalurus punctatus were the highest (70.1%), followed by Pygocentrus nattereri (4.7%), Astyanax mexicanus (3.9%), Cyprinus carpio (1.7%), Oncorhynchus mykiss (1.6%), and other vertebrates (18.0%) (Figure 4).

FIGURE 4

Figure 4 Venn diagram of overlap of the seven databases.

Functional annotation of genes

GO is widely used to classify genes and gene products over species (36). To further study the biological importance of the unigenes, we made use of Blast2GO to determine the functional categories (25). According to the NR annotation from NCBI, 17,372 unigenes were classified into three major categories (cellular components, biological processes, and molecular functions) and 55 subcategories. In the biological process category, most unigenes were assigned to single-organism processes, metabolic process subcategories and cellular processes. Many unigenes were associated with the cell fraction and cell, in the cellular component category. In the molecular function category, most of the unigenes were found to participate in binding and catalytic activity (Figure 5).

FIGURE 5

Figure 5 Gene ontology classifications of assembled unigenes. A total of 17,372 unigenes were categorized into three functional categories: biological process, cellular component, and molecular function.

The KOG is a database that can classify isogenous gene products. It is assumed that each KOG protein comes from an ancestor protein (37). To predict their possible functions and classify them by the KOG database, 7,878 unigenes were classified into 26 functional categories (Figure 6). Among these, the signal transduction mechanisms (T, 1,335) included the most unigenes, followed by general function prediction only (R, 1,282) and post-translational modification, protein turnover, and chaperones (O, 854). A number of unigenes (V, 59) were classified to the defense mechanisms category, which indicated these unigenes may participate in immunity protection of yellow catfish. The unigenes resembled those acquired from the Megalobrama amblycephala (38).

FIGURE 6

Figure 6 Function annotations of unigenes by KOG.

The KEGG is a bioinformatic database for the systematic analysis of gene functions (39). In this study, 11,300 unigenes in total were designated to 232 known pathways. The largest group was “PI3K-Akt signaling pathway”, which contains 351 unigenes, followed by “Endocytosis” (330), “MAPK signaling pathway” (286), “Focal adhesion” (271), and “Rap1 signaling pathway” (257) (Table 5). Moreover, these 232 pathways were divided into five categories: environmental information processing, cellular processes, metabolism and organismal systems, and genetic information processing (Figure 7). Within the organismal systems, “endocrine system” (771) and “immune system” (785) were the two richest subcategories. In the metabolism category, the most common categories were “amino acid metabolism” (252), “lipid metabolism” (331) and “carbohydrate metabolism” (320). In the signal transduction category, the unigenes were mostly associated with environmental Information Processing (1686).

TABLE 5

Table 5 KEGG annotation of assembled unigenes.

FIGURE 7

Figure 7 KEGG pathway assignment of the assembled unigenes. Different colored bars represent different groups.

Identification of DEGs analysis

To recover the expression levels in the PBS- and V. cholerae-injected libraries, all unigenes were analyzed by RSEM software, and DEG-seq was applied to determine the DEGs when the Q-value < 0.005 and |log₂(fold change)|>1. A total of 674 differential expression genes were induced, of which 352 were significantly upregulated and 321 were significantly downregulated unigenes (Figure 8).

FIGURE 8

Figure 8 Volcano plot of the differentially expressed genes in head kidney of yellow catfish.

DEGs analysis

To further investigate the function of DEGs implicated in the immune response of P. fulvidraco challenged with V. cholerae, DEGs were compared with the KEGG database for pathway enrichment to understand the pathway, and 210 pathways in total were annotated. The top 20 of these divided pathways were shown in Table 6 and Figure 9. The largest quantities of DEGs appeared in the category “Ribosome”, followed by “Endocytosis”, and “Oxidative phosphorylation”. Additionally, from 11 immune-related signal pathways, we identified 29 genes, including “Antigen processing and presentation” (9 DEGs), “Fc gamma R-mediated phagocytosis” (2 DEGs), “Leukocyte transendothelial migration” (10 DEGs), “TNF signaling pathway” (3 DEGs), “Toll-like receptor signaling pathway” (1 DEG), “Chemokine signaling pathway” (2 DEGs), “MAPK signaling pathway” (1 DEG), “NOD-like receptor signaling pathway” (2 DEGs), “Platelet activation” (2 DEGs), “Intestinal immune network for IgA production” (3 DEGs), and “NF-kappa B signaling pathway” (3 DEGs).

TABLE 6

Table 6 KEGG annotation of assembled unigenes.

FIGURE 9

Figure 9 Top 20 significantly enriched KEGG pathways of DEGs.

The validation of DEGs by qRT-PCR

Furthermore, to verify the differentially expressed genes, 10 genes were selected for qPT-PCR analysis challenged by V. cholerae for 6 h. The results showed that, compared with the control group, most immune related genes were upregulated at different points (Figure 10). The cadherin gene family plays a key role in target recognition and cell adhesion (40). Compared with the control group, cadherin-5 expression was significantly increased by more than double in the experimental group. In addition, cadherin is a transmembrane cell adhesion molecule conserved in metazoan organisms and plays an important role in histomorphogenesis and homeostasis (41). CC chemokines are a group of 28 chemokines with N-terminal CC domain, which play key roles in regulating leukocyte transport to injury, infection, or inflammation sites (42). The CC chemokine SCYA101 gene in P. fulvidraco was overexpressed by more than two-fold in response to V. cholerae. Moreover, calumenin (calu) is a well-conserved multi-EF-hand-containing Ca²⁺-binding protein, which may provide a new target for bladder cancer and has multiple mechanisms, including TME remodeling, gene mutation, and ferroptosis (43). After injection of V. cholerae, the expression level of calu was higher than that of the control group. Additionally, C-type lectins (CTLs) are calcium-dependent, carbohydrate-binding, pattern recognition receptors that play important roles in the immune system and primarily bind carbohydrate-based or other ligands that are involved in recognizing pathogens and cell adhesion (44–46). Compared with PBS injection, expression of CTLs was increased by over 5-fold. As a closely related class I cytokine, Interleukin (IL)- 13 plays important roles in the T helper (Th)-2 immune response via heterodimeric receptors (47). The integrin family is included in an assortment of cell processes, including cell proliferation, separation, and migration, and in the pathogenesis of disease (48). Lysosomal membrane glycoprotein 1 (LAMP 1) is an integral membrane protein of the lysosome, which plays an important role in lysosomal biogenesis, autophagy, immune response, and cholesterol homeostasis (49). Mucin is synthesized and secreted by epithelial goblet cells, and is a key component of the innate immune system and plays an important part within the digestive system (50). The natterin protein family was first found in the venom of thalassophryne nattereri, a fish with medical significance. In the past decade, natterin-like genes have been found in various organisms, including genes that perform immune related functions (51). In conclusion, these immune genes may be related to the immune defense of P. fulvidraco after bacterial infection.

FIGURE 10

Figure 10 Validation of DEGs by qRT-PCR. The relative gene expression levels of 10 selected DEGs were examined. The β-actin gene was used as an internal standard. The means + SEM of three independent samples are shown (means ± SE, n = 3). Differences between treated and control samples were tested by one-way analysis of variance (ANOVA) followed by the Duncan’s new multiple range test. The P values are shown as *P < 0.05.

Conclusion

P. fulvidraco is a famous fresh-water fish with enormous economic value in eastern China. Raising a large number of P. fulvidraco leads to the outbreak of various diseases and thus, economic losses. In this study, the transcriptomic characteristics following V. cholerae injection in the liver of P. fulvidraco were analyzed in detail. We identified a great deal of genes and pathways involved in the immunization to V. cholerae in P. fulvidraco. A total of 674 DEGs were identified, including 321 downregulated genes and 352 upregulated genes, some of which are related to “Antigen processing and presentation”, “Fc gamma R-mediated phagocytosis”, “Toll-like receptor signaling pathway” and other signaling pathways. These results were obtained for the first time in this work. In conclusion, this study may provide an opportunity to explore the immune defense mechanism of P. fulvidraco against bacterial attack.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/genbank/, PRJNA902142.

Author contributions

The authors’ responsibilities were as follows: S-HJ and Q-NL: Analyzed data, Wrote the manuscript. L-XW, Y-TC, H-BZ, and R-TM: Analyzed data and conducted experiments. D-ZZ: Resources. Q-NL: Funding acquisition. B-PT and L-SD: Experiment design and manuscript review and editing, Resources. All authors contributed to the article and approved the submitted version.

Funding

This work was supported by the Natural Science Research General Program of Jiangsu Provincial Higher Education Institutions (22KJA240002, 21KJA240003), the Fishery High-Quality Development Research Project of Yancheng, China (YCSCYJ2021022),”Three Districts” Talent Program of Jiangsu Province, the Natural Science Foundation of Jiangsu Province (BE2020673), the National Key R&D Program of China (2019YFD0900404-05), the National Natural Science Foundation of China (32070526), The study was sponsored by the Qing Lan Project of Jiangsu Province, and the “Outstanding Young Talents” of YCTU.

Conflict of interest

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.

Publisher’s note

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