1 INTRODUCTION

The oriental river prawn Macrobrachium nipponense, belonging to the Palaemonidae family of decapod crustaceans, is an important aquaculture prawn and is widely reared in China, Japan, and other South-East Asian countries (Cai and Dai, 1999; Cai and Ng, 2002). Owing to the short breeding period and high economic value, this species is popular in aquaculture and has become one of the four major freshwater shellfish species cultivated in China (Yao et al., 2004). However, various diseases caused by bacteria in M. nipponense have placed significant constraints on aquaculture production and have led to severe economic losses in prawn farming (Yao et al., 2004). Thus, it is urgent to understand the immune defence mechanism of M. nipponense at the molecular level after bacterial infection.

Aeromonas veronii, a motile, mesophilic aeromonad, is a gram-negative pathogen that consists of motile strains and grows well at optimal growth temperatures between 35 and 37 ℃ (Janda and Abbott, 2010). This pathogen has been characterized as a "highly virulent pathogen" that can cause motile aeromonad septicaemia in a wide range of species, from invertebrates to mammals (Havixbeck et al., 2017). A. veronii has had devastating effects on the aquaculture industry and has led to disastrous economic losses for farmers (Vazquez-Juarez et al., 2005; Sahoo et al., 2008; Zhang et al., 2017). A. veronii has been reported to cause motile aeromonad septicaemia in many cultured species, including Litopenaeus vannamei (Zhang et al., 2017), Eriocheir sinensis (Fang et al., 2008), and Procambarus clarkii (Jiang et al., 2016). Fang et al. (2008) isolated one dominant bacterial strain, AVZ01, from sick L. vannamei and identified A. veronii as the pathogen via in vitro tests, indicating that A. veronii might also lead to crustacean death in the aquaculture industry.

Staphylococcus aureus is a gram-positive cocci bacterium that can invade host cells and persist intracellularly for various durations in cell culture models (Garzoni and Kelley, 2009). Pathogenic strains often promote infections by producing a large repertoire of virulence factors such as secreted toxins, potent haemolysins and leukotoxins (Otto, 2014). Toxins damage biological membranes and inhibit the complement cascade or prevent recognition by host defences. Among haemolysins and leukotoxins, some represent powerful weapons against bacterial elimination through the innate host defence system (Wang et al., 2008). S. aureus is a global pathogen of species ranging from mammals to invertebrates and can induce an innate immune response in invertebrates such as Haliotis diversicolor (Wang et al., 2008) and M. nipponense (Pan et al., 2019).

Previous studies have given a few introductions on the anti-bacterial immunity of M. nipponense. After challenge with Aeromonas hydrophila, the expression of anti-lipopolysaccharide factors (ALFs) and extracellular copper/zinc superoxide dismutase (ECSOD) in the hepatopancreas were increased responsively (Xiu et al., 2013; Wang et al., 2015). Upon infected by Vibrio parahaemolyticus and S. aureus, the expression levels of Toll1 in gills were significantly up-regulated (Pan et al., 2019). After infection with A. veronii, M-type lectin was increased significantly while L-type lectin was significantly down-regulated in intestine (Xiu et al., 2015a). Besides, a novel C-type lectin and two 2-transmembrane C-type lectin also participated in antibacterial activity and were up-regulated significantly after S. aureus, A. veronii, or V. parahaemolyticus infection (Xiu et al., 2016; Huang et al., 2019).

Recently, next-generation RNA-sequencing (RNA-Seq) techniques have been widely applied for both mapping and quantifying transcriptomes from plants and animals (Garber et al., 2011). RNA-Seq has been verified as an adequate tool for investigating the transcriptomic response of aquatic animals to ambient stress (Xia et al., 2013). Immune-related transcriptomes have been characterized in many aquatic animals such as Sinonovacula constricta (Zhao et al., 2017), Mytilus chilensis (Núñez-Acuña and Gallardo-Escárate, 2013) and M. nipponense (Xu et al., 2016). RNA-Seq of Ruditapes philippinarum infected by Vibrio anguillarum identified mRNAs as important effectors in the intricate host-pathogen interaction network (Ren et al., 2017). It was reported that the ability to respond to pathogen stimulation of an organism depends on its ability to initiate changes in gene expression (Wang et al., 2016; Bao and Xia, 2017). Thus, based on RNA-Seq, we first identified potential different functional genes participating in the transcriptomic responses of M. nipponense against A. veronii or S. aureus infection and provided insight into the differential response mechanism of crustaceans infected by gram-positive and gramnegative bacteria.

2 MATERIAL AND METHOD 2.1 Experimental animals and bacterial stimulation

Healthy juvenile M. nipponense (2–4 g per prawn) were obtained from a farm in Shaoguan, Guangdong Province, China. These oriental river prawns were acclimatized for one week in three aquariums (120 L) in the laboratory at room temperature, which was maintained at approximately 26 ℃, and fed a commercial diet weighing 5% of the body weight at 18꞉00 once daily. First, a trial challenge of the prawns with A. veronii or S. aureus was conducted to determine the optimal concentration using three concentrations of bacterial cells (10⁵, 10⁶, and 10⁷ colony-forming unit (cfu)/mL) administered via second abdominal muscle injection; 25 μL of each concentration of bacterial cells was injected (20 prawns per group). After one week, the results showed that the mortality rate was more than 80% using 10⁶ and 10⁷ cfu/mL bacterial suspension with about 30% using 10⁵ cfu/mL. The infection and dissection experiments were all performed under MS-222 anaesthesia to minimize suffering. The prawns in both the experimental and control groups were intramuscularly injected with equal volumes (25 μL) of a bacterial suspension at 10⁵ cfu/mL and phosphatebuffered saline (PBS). According to the groups into an aquarium, the tested prawns were separately observed for mortality and sampled.

2.2 Sampling and RNA extraction

The prawns were sampled at 24-h post injection. Before sampling, twelve prawns from each group were anaesthetized with MS-222 and surgically dissected (including six female prawns and six male prawns). The hepatopancreatic tissue was sampled and immediately placed in RNA Keeper tissue stabilizer (Vazyme, China), stored at 4 ℃ for overnight and cryopreserved at -20 ℃ until RNA extraction. Total RNA extraction from the hepatopancreatic tissue was conducted by RNA Isolater (Vazyme, China) according to the manufacturer's protocol. The integrity and quality of the total RNA were further measured using an Agilent 2100 bioanalyzer. RNA samples from two males and two females from each group were pooled as one biological duplicate for cDNA synthesis and sequencing.

2.3 Library construction and Illumina sequencing

After evaluation of RNA quality, a total of 1-μg RNA per sample was used for library preparation. The VAHTS mRNA-seq v2 Library Prep Kit for Illumina^® (Vazyme, NR601) was further used to generate sequencing libraries following the manufacturer's protocol. The following procedures, including RNA fragmentation, cDNA synthesis, size selection, PCR amplification and RNA-seq, were performed at Vazyme Biotech Co., Ltd. (Nanjing, China). In the typical procedure, mRNAs were fragmented into small pieces in Vazyme Frag/Prime buffer. Subsequently, random hexamer primers were used to synthesize the first-strand cDNA using Super Script II reverse transcriptase (Thermo Scientific, Delaware, USA) according to the manufacturer's protocol. Using the QiaQuick PCR extraction kit (Qiagen, Germany), the short fragments were further purified to repair the end by adding a poly (A) tail. The library preparations were sequenced on an Illumina HiSeq X Ten platform with a 150-bp paired-end module.

2.4 Cleaning of raw data and de novo assembly

Before de novo assembly, the raw reads were trimmed by removing the dirty reads, which included reads with adaptors, low-quality sequences (reads with ambiguous 'N' bases at a ratio greater than 5%), and short-read-length sequences (in which the number of bases with Q≤10 was more than 50% of the entire read). Then they were further assembled into expressed sequence tag (EST) clusters (contigs) using the Trinity software with default parameters. The transcripts were further assembled and clustered by the Chrysalis clusters software with the default parameters. The longest assembled sequences obtained in each cluster were further designated as "unigenes".

2.5 Functional unigene annotation and classification

The contigs that were assembled using the combined sequence data from the infected and noninfected samples were used as queries to search against three public databases by BLAST. All unigenes were further aligned against NCBI nonredundant protein database (Nr; http://www.ncbi.nlm.nih.gov/), the Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg/), and the Clusters of Orthologous Groups of proteins database (COG; http://www.ncbi.nlm.nih.gov/COG/) with an E-value of 10^-5 using BLASTp (version 2.2.25). The BLAST results of the best hit of the unigenes were extracted for unigene description. Blast2GO was used to assign Gene Ontology (GO) terms to annotated contigs based on BLASTx hits against the NCBI Nr database (Ashburner et al., 2000). The unigenes associated with GO term were subsequently grouped into three categories including cellular component, biological process, and molecular function. The unigenes were also annotated against the COG database to identify the possible functional categories of the genes based on sequence similarities. Unigene information with respect to the KEGG pathways was obtained based on BLASTx hits against the KEGG database.

2.6 Differential gene expression analysis

All clean reads from each of the two groups (hepatopancreatic control (HC) vs. hepatopancreatic A. veronii (HA) and HC vs. hepatopancreatic S. aureus (HS)) were mapped to reference sequences (unigenes from the assembled transcriptome data) using Bowtie2 (Langmead and Salzberg, 2012). Gene expression levels were further calculated according to the fragments per kilobase per million mapped reads (FPKM). The differentially expressed genes (DEGs) between hepatopancreatic tissues of the two groups was identified using the R package edgeR (Robinson et al., 2010). To assess the significance of differential gene expression, the threshold for defining significant DEGs was set as a P-value less than 0.05 and an absolute log2(fold change) value greater than 1. When the log2(fold change) was > 1, the transcript was considered to be up-regulated, while the log2(fold change) was < -1, the transcript was considered to be down-regulated. In addition, DEGs across the samples were further annotated by GO and KEGG pathway analysis. Only DEGs with annotation were considered candidates of interest for further analysis.

2.7 Validation of differentially expressed genes using real-time PCR

To validate the reliability of the DEGs identified by RNA-Seq, we selected 15 genes involved in the immune system for quantitative Real-time polymerase chain reaction (qRT-PCR) validation. Based on each identified gene from the transcriptome library (Premier Biosoft, USA), PCR primers were designed using Primer Premier 6 software (Supplementary Table S1). qRT-PCR was performed using the AceQ qPCR SYBR Green master mix (Vazyme, Nanjing) by a LightCycle 480 system following the manufacturer's instructions. The amplifications were performed with the following program: 95 ℃ for 30 s, followed by 40 cycles of 94 ℃ for 15 s, 58 ℃ for 20 s, and 72 ℃ for 20 s. Target gene expression levels were normalized using β-actin and expressed as relative expression levels (relative mRNA expression). The dissolution curve was obtained at temperatures from 60.0 to 95.0 ℃, increasing the temperature by 0.5 ℃ per 0.05 s. The actin gene was used as the reference gene (Xiu et al., 2013), and relative fold changes of DEGs were further calculated using the 2^-∆∆Ct method (Livak and Schmittgen, 2001).

3 RESULT 3.1 Sequencing and de novo assembly

A total of 410.36 million raw reads were generated, including 134.75 million, 135.67 million, and 139.93 million reads from the hepatopancreatic tissue of the HC (HC1=42.97 million, HC2=44.27 million, and HC3=47.51 million), HS (HS1=48.06 million, HS2=45.66 million, and HS3=41.94 million), and HA (HA1=46.47 million, HA2=50.09 million, and HA3=43.36 million) groups, respectively (Table 1). After stringent quality assessment and data filtering, a total of 400.19 million clean reads (97.52% of the total reads) were used for subsequent transcriptome assembly. The clean reads were assembled by Trinity after splicing and removing redundancy to create a total of 701 103 contigs. The Q20 value for each sample was more than 97%, and the N50 value was in the range of 892–1 184 bp, including 247 513 contigs in the HC group, 225 778 contigs in the HS group, and 227 812 contigs in the HA group. Most of the assembled unigenes (~69%) in each sample were shorter than 500 bp with the N50 value ranging from 1 371 to 1 743 bp (Table 2). When the reads of all the samples were merged for assembly, 56 944 unigenes were obtained with a total length of 71.34 Mbp. The unigenes shorter than 500 bp decreased to ~45% with the N50 value increase to 2 584 bp, indicating a marked increase in the quality.

3.2 Annotation of all unigenes

Unigene annotation provides information on the function of the unigene. First, using the BLAST tools, the 56 944 unigene sequences assembled from the combined reads were aligned to major databases, including the Nr, NT, Swiss-Prot, KEGG, COG, and GO databases (E-value < 0.000 01). It was found that 21 754, 10 726, 18 595, 16 669, 9 907, and 11 578 unigenes had significant hits to these major databases, respectively. Totally, 24 688 unigenes were annotated by at least one database. According to the Nr annotation, approximately 46.6% of the unigenes had E-values less than 1e-45 and 61.5% shared greater than 40% similarity with known sequences (Fig. 1). In terms of the species distribution of the most significant hits, 10.8% of the unigenes matched to sequences of Daphnia pulex, which had the highest BLAST-matched ratio of the matched species.

In the COG classification, 9 907 unigenes were categorized into 25 functional COG clusters. The top three enriched categories were general function prediction only (20.50%); replication, recombination and repair (8.19%); translation, ribosomal structure and biogenesis (7.67%) (Fig. 2). In the biological process category of GO classification, the three most common subcategories were cellular process (7 927 unigenes), metabolic process (6 497 unigenes), and single-organism process (6 155 unigenes). Some immune-related GO terms were found in the biological process category, in which 2 887 unigenes were assigned to the term "response to stimulus", followed by "immune system process" (551 unigenes) and "cell killing" (15 unigenes) (Fig. 3).

KEGG pathway annotation was also conducted to study the associated biological pathways of the assembled genes. The results show that a total of 16 669 unigenes were associated with 258 biological pathways in the KEGG database, such as metabolic pathways (2 404 genes), ubiquitin-mediated proteolysis (732 genes), regulation of the actin cytoskeleton (693 genes), and focal adhesion (556 genes). In addition, 15 pathways related to the immune system, mainly including the chemokine signalling pathway, leukocyte transendothelial migration, and the T-cell receptor signalling pathway, were further identified (Supplementary Table S2).

3.3 Identification and annotation of differentially expressed genes

Comparison of gene expression levels in the HC vs. HA and HC vs. HS groups revealed 1 857 and 1 061 significant DEGs (|log2Ratio|≥1, and P-value ≤0.05), respectively. Among these DEGs, 677 genes were up-regulated and 1 180 were down-regulated in the HC vs. HA group (Supplementary Table S3; Fig. 4a). A total of 390 genes were up-regulated and 671 were down-regulated in the HC vs. HS group (Supplementary Table S3; Fig. 4a). About 446 DEGs were found in both HC vs. HA and HC vs. HS groups (Supplementary Table S3; Fig. 4b).

To determine the biological functions of DEGs stimulated by A. veronii or S. aureus in M. nipponense, GO classification and KEGG pathway enrichment analysis were performed. During A. veronii stimulation, GO functional analysis showed that the 287 significant DEGs could be annotated into 13 cellular components, 12 molecular functions, and 24 biological processes (Supplementary Table S4). Among the 24 categories of biological processes, the DEGs mostly participated in cellular process (189 genes), followed by the categories of single-organism process (183 genes). Within the 13 cellular component categories, the DEGs mostly participated in the cell (155 genes) and cell part (155 genes) categories. In the 12 molecular function categories, the DEGs mostly participated in the catalytic activity (146 genes) and binding (134 genes) categories. The KEGG pathway analysis annotated a total of 490 DEGs during A. veronii stimulation, which were assigned to 220 KEGG pathways (Supplementary Table S5). Many immune-related pathways also exhibited significant unigene enrichment, including Pathways in cancer (81 genes), Natural killer cell mediated cytotoxicity (21 genes), Toll-like receptor signaling pathway (30 genes), and B cell receptor signaling pathway (15 genes) (Fig. 5a).

After stimulation by S. aureus, the 189 significant DEGs could be annotated into 11 molecular functions, 14 cellular components, and 25 biological processes by GO functional analysis (Supplementary Table S4). Among the 25 biological process categories, the DEGs mostly participated in the categories of cellular process (123 genes) and single-organism process (118 genes). Among the 14 cellular component categories, the DEGs were enriched in the cell (98 genes) and cell part (98 genes) categories. Within the 11 molecular function categories, the DEGs were annotated into the categories of catalytic activity (103 genes) and binding (85 genes). In addition, 42 DEGs were annotated in the response to stimulus, while 9 DEGs were annotated in the immune system process. A total of 312 DEGs during S. aureus stimulation were annotated and assigned to 197 KEGG pathways (Supplementary Table S5). Metabolic pathways (46 genes) was the predominant category. Moreover, many immunerelated pathways were significantly enriched, including pathways in cancer (48 genes), B cell receptor signaling pathway (10 genes), and NOD-like receptor signaling pathway (17 genes) (Fig. 5b).

3.4 Validation of differentially expressed genes

To validate the reliability of DEGs identified by RNA-Seq, some DEGs involved in the immune system were randomly selected for qRT-PCR validation. Levels of expression for the target genes isolated from hepatopancreatic tissue were determined in the infected M. nipponense and compared with those in the controls at 24 h post infection. These results are largely consistent with the transcriptomic profile analysis (Fig. 6).

4 DISCUSSION

Macrobrachium nipponense is an economically important aquaculture species throughout China and in some other Asian countries. The aquaculture of M. nipponense has developed rapidly in recent years, but aquaculture environments with high stock density have experienced frequent disease breakouts. Comparative transcriptomic analysis has been widely used to understand the physiological response to various stimuli in crustaceans (Rao et al., 2015; Chen et al., 2017). In our study, comparative transcriptomic analysis was firstly performed to assess the transcriptional response in the hepatopancreas of M. nipponense after infection with A. veronii or S. aureus. A total of 400.19 million clean reads were obtained and further assembled into 56 944 unigenes. Compared with the control samples (HC), 1857 DEGs were found in the A. veronii-infected (HA) samples and 1 061 DEGs were found in the S. aureus-infected (HS) samples. This research enriches the M. nipponense transcriptome database and provides insight into the immune regulation of prawn in response to bacterial infection.

Immune-related DEGs are the target molecules involved in almost all transcriptomic analyses concerning the immune response. In fact, there were many immune-related DEGs potentially involved in responses to A. veronii or S. aureus infection, including prophenoloxidase (ProPO), mitochondrial manganese superoxide dismutase (mtMnSOD), tumor necrosis factor receptor-associated factor 6 (TRAF6), anti-lipopolysaccharide factor (ALF) and C-type lectin (Supplementary Table S3). Toll-like receptor signaling pathway plays an important role in the response to gram-negative and gram-positive bacteria by regulating a large number of genes (Pan et al., 2011). In Drosophila, the Toll pathway is triggered by spaetzle (Spz) cleavage, which starts an intracellular signaling cascade including DmMyD88, Tube (considered as the IRAK4 homologue), Pelle (the human IRAK1 homologue) and DmTRAF6, resulting in the translocation of Dorsal-related immunity factor or Dorsal (the homologue of human NF-kB) and the expression of Drosomycin (Belvin and Anderson, 1996). As an extracellular ligand, the activated Spz binds as a dimer to the Toll ectodomain with high affinity and with a stoichiometry of one Spz dimer to two receptor proteins: necrotic and persephone (Hoffmann, 2003; Weber, 2003). TRAF6, identified as a downstream target of Pelle, is a key signal adaptor that is involved in the interleukin-1 receptor/Toll-like receptor (IL-1/TLR) superfamily (Sun et al., 2017). Some studies have shown that TRAF6 acted as a bridge to link the upstream TLRs, IRAKs, and MyD88 with the NF-kB and MAPK signalling pathways (Arch et al., 1998; Kim and Rikihisa, 2002). In our data, Spz mRNA was up-regulated in the hepatopancreas after challenged with A. veronii or S. aureus. Meanwhile, the TRAF6 was only up-regulated in the A. veronii-infected group. Shi et al. (2009) also demonstrated that the expression of the FcSpz transcript in the haemolymph, hepatopancreas and other tissues of Fenneropenaeus chinensis was upregulated after injection with V. anguillarum and white spot syndrome virus. It has been reported that both Spz and TRAF6 could activate the promoters of certain antimicrobial peptide genes in vitro (Wang et al., 2007, 2011; Sun et al., 2017). In our transcriptomic data, ALF-3 that contains a conserved disulfide loop and can neutralize lipopolysaccharide was significantly up-regulated after A. veronii or S. aureus infection. Taken together, Spz and TRAF6 might play important roles in host defence against gram-positive and gram-negative bacteria invasion via regulating the expression of ALFs in crustaceans.

Most research attention on C-type lectin has focused on their roles in antimicrobial immunity. Classical C-type lectins contain carbohydrate recognition domains (CRDs) that bind carbohydrate structures in a Ca²⁺-dependent manner. Some C-type lectins are produced as transmembrane proteins, and others are secreted as soluble proteins (Cambi and Figdor, 2005). The C-type CRDs generate a subfamily including protein domains called C-type lectin-like domains (CTLDs). Some CTLDs can bind protein or lipid moieties, which are Ca²⁺ independent (Zhang et al., 2009). C-type lectins have a binding site with affinity for gram-negative bacteria, which have lipopolysaccharide (LPS) on their surface, and grampositive bacteria, which have other surface polysaccharides (Yu et al., 1999). In our study, several lectins, including C-type lectin and C-type lectin 1, were significantly up-regulated in the hepatopancreas of M. nipponense after infection with A. veronii or S. aureus. Similar expression of C-type lectins has also been observed in M. nipponense infected with Aeromonas hydrophila or Vibrio parahaemolyticus (Xiu et al., 2015b, 2016). In summary, these various types of lectins with structural and functional diversities were mainly expressed in the hepatopancreas of the prawn, which indicated that these proteins played essential roles in the defence system of the prawn.

ProPO is regarded as a critical part of the immune system and plays an important role in the immune recognition process in the defence mechanism of invertebrates. Upon injury or infection, the ProPO zymogen is activated to PO by clip-domain serine proteases, which are called PPAFs (Jiang et al., 1998; Satoh et al., 1999). PO compounds can produce quinones, which may kill pathogens and be used for synthesis of melanin to encapsulate parasites and seal wounds. In our transcriptome data, unigenes annotated as PPAF, serine proteinase homologue (SPH) and ProPO were exhibited significantly up-regulated after A. veronii infection. Similar to this observation, in F. chinensis, both FcSP and FcSPH can respond to V. anguillarum challenge and displayed up-regulation (Ren et al., 2009). Serine proteases (SPs) and SPHs, which possess a trypsin-like domain at the C terminus and one or two cysteine-rich structural motif clip domains at the N terminus, are the essential components of extracellular signalling cascades in various biological processes of invertebrates (Lin et al., 2006; Jang et al., 2008). Furthermore, several groups have demonstrated that SPHs bind tightly to microbial cell wall components (Zhang et al., 2003) or pathogenic bacteria (Lee and Soderhall, 2001). Kan et al. (2008) determined that TmSPH1 specifically binds to curdlan polymers (β-1, 3-glucan fungal polymer) and three components, namely, the serine protease TmSPE, TmproPO, and TmSPH1, and participates in melanin synthesis. Moreover, previous findings demonstrated that one unique clip-domain serine protease (SPE) participated in the regulation of ProPO activation cascade and Toll signaling pathway (Kan et al., 2008). It is also noted that PO catalyses the production of quinones, which may be involved in the production of reactive oxygen species (ROS), such as superoxides and hydroxyl radicals.

ROS such as superoxides and hydroxyl radicals are constantly generated when the organism is attacked by pathogens, but overexpression of ROS will lead to cell damage. Therefore, a protective mechanism in the cell must exist to eliminate excess ROS. Cells are protected against oxidative stress by a series of antioxidant enzymes, such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), and peroxiredoxin (PRX). These antioxidant enzymes play important roles in sustaining homeostasis of the cell (Aruoma, 1998). In our transcriptomic data, antioxidant enzymes, thioredoxin (TRX), and mtMnSOD were up-regulated after A. veronii challenge, and in the HC vs. HS group, mtMnSOD was also significantly up-regulated. MtMnSOD can respond to various pathogenic invaders or foreign particles at the transcriptional level (Song et al., 2015). Meng et al. (2013) demonstrated that the expression level of the mtMnSOD gene was up-regulated in P. clarkii after challenge with Spiroplasma eriocheiris or A. hydrophila. It was also demonstrated that CfmtMnSOD mRNA transcripts could be significantly up-regulated by stimulation with three typical microbes in the hepatopancreas of Chlamys farreri (Wang et al., 2018). TRX is a major highly conserved and ubiquitous protein involving in protecting organisms against various oxidation pressures. Mu et al. (2009) reported that the expression of TRX in the hepatopancreas of Eriocheir sinensis was upregulated after a gram-negative marine bacterium A. veronii challenge. Song et al. (2012) further demonstrated that PtTRX1 transcripts are significantly up-regulated after challenged by the bacteria V. alginolyticus, while the expression level of PtTRX2 mRNA was up-regulated when injected with a grampositive bacteria M. luteus. These results suggest that TRX might be more sensitive to gram-negative bacteria.

5 CONCLUSION

In conclusion, a comparative transcriptomic profile analysis of hepatopancreatic tissue from M. nipponense stimulated by A. veronii or S. aureus was firstly completed, and a large number of transcripts and DEGs involved in immune system were obtained. Although the functions of most genes and their associated pathways remain to be explored, this study provides much valuable data regarding the anti-bacterial immune mechanisms in prawn and first reveals a similar response mechanism of crustaceans after infection by gram-positive and gram-negative bacteria in transcriptome level. Furthermore, the transcriptomic analysis identified a large number of novel transcripts in the hepatopancreas of M. nipponense that were absent from the prawn genome database and will provide a stepping stone for further genomic studies on the molecular mechanisms associated with the late development of the hepatopancreas in M. nipponense.

6 DATA AVAILABILITY STATEMENT

All the raw data of nine sequencing libraries have been submitted to NCBI Sequence Read Archive with accession numbers SRR7665577, SRR7665578, SRR7665579, SRR7665580, SRR7665581, SRR7665582, SRR7665583, SRR7665584, and SRR7665585.

Electronic supplementary material

Supplementary material (Supplementary Tables S1–S5) is available in the online version of this article at https://doi.org/10.1007/s00343-021-0364-y.