Next Article in Journal
FishSegNet-PRL: A Lightweight Model for High-Precision Fish Instance Segmentation and Feeding Intensity Quantification
Previous Article in Journal
Salient Object Detection Guided Fish Phenotype Segmentation in High-Density Underwater Scenes via Multi-Task Learning
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Fishes
Volume 10
Issue 12
10.3390/fishes10120628
fishes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Transcriptome Analysis Reveals the Mechanisms of Organismal Response in Exopalaemon carinicauda Infected by Metschnikowia bicuspidata

by
Ran Zhao
1,2,3,
Hui Li
1,
Libao Wang
1,
Wenjun Shi
1,2,* and
Xihe Wan
1,2,*
1
Institute of Oceanology & Marine Fisheries, Nantong 226007, China
2
National Demonstration Center for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China
3
Key Laboratory of Aquatic Animal Diseases and Immune Technology of Heilongjiang Province, Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin 150070, China
*
Authors to whom correspondence should be addressed.
Fishes 2025, 10(12), 628; https://doi.org/10.3390/fishes10120628
Submission received: 4 November 2025 / Revised: 2 December 2025 / Accepted: 4 December 2025 / Published: 8 December 2025
(This article belongs to the Section Welfare, Health and Disease)
Browse Figures
Versions Notes

Abstract

Exopalaemon carinicauda is a commercially significant aquaculture species in China. However, outbreaks of “zombie disease” caused by Metschnikowia bicuspidata infection have led to substantial economic losses in its farming industry. Despite its growing impact, the molecular basis of E. carinicauda’s response to M. bicuspidata infection remains unexplored. To elucidate the molecular mechanisms involved, this study conducted a transcriptomic analysis of the E. carinicauda hepatopancreas under M. bicuspidata infection and non-infection conditions. Following transcriptome assembly, 67,811 unigenes were generated, exhibiting high N50 value of 1977 base pairs and high complete BUSCO of 94.68%. Among these, 22,561 unigenes were successfully annotated. Comparative gene expression analysis of M. bicuspidata-infected and uninfected samples at 60 h post-infection revealed 1991 DEGs, comprising 1224 upregulated and 767 downregulated transcripts. Functional enrichment analysis revealed that numerous DEGs participate in immune-associated pathways, particularly those related to pattern recognition, lysosomal function, cellular stress responses, and programmed cell death. In addition, a significant proportion of DEGs were linked to metabolic processes such as glycerophospholipid metabolism and protein digestion and absorption. To verify the reliability of the transcriptomic results, eight DEGs were randomly chosen for qRT-PCR validation, and their expression profiles showed strong agreement with the RNA-Seq data. Overall, this study provides a transcriptomic overview of the hepatopancreatic response of E. carinicauda to M. bicuspidata infection, offering insights into the underlying molecular mechanisms and a theoretical foundation for the prevention and management of “Zombie disease.”
Keywords:
Exopalaemon carinicauda; Metschnikowia bicuspidata; transcriptome; immunity; metabolism
Key Contribution: After invasion by M. bicuspidata, genes related to pattern recognition receptors, the lysosome, and apoptosis were activated to fight the foreign pathogen, and genes related to the antioxidant system and glycerophospholipid metabolism were suppressed.

1. Introduction

The ridgetail white prawn (Exopalaemon carinicauda) is a commercially significant crustacean species that is naturally distributed along the coastal waters of the Yellow Sea and Bohai Sea in China. Owing to its high fecundity, rapid growth, and strong adaptability to environmental conditions, it has become a key species in aquaculture, particularly in coastal regions of China, with Jiangsu Province being a primary area of cultivation [1,2]. However, with the increase in stocking density and the degradation of germplasm resources, disease outbreaks caused by a variety of pathogens, such as Hematodinium [3], Vibrio Parahaemolyticus [4], and White Spot Syndrome Virus [5], have unfortunately become increasingly frequent, posing significant challenges to the sustainable development of E. carinicauda aquaculture. From 2018 to 2022, a novel epidemic of the so-called “zombie disease” occurred in several ridgetail white prawn farms across the coastal areas of Jiangsu Province, leading to reduced production yields and significant economic losses. Infected prawns exhibited distinct clinical symptoms, including reddened bodies, muscle whitening, swollen appendages, and diminished swimming activity, and reported morbidity and mortality rates were between 5% and 30% and 3% and 10%, respectively, across different farming systems [6]. The causative pathogen was first isolated and identified by our team as the aquatic pathogen Metschnikowia bicuspidata [6], which is capable of infecting crustaceans such as Macrobrachium rosenbergii [7], Portunus trituberculatus [8], and Eriocheir sinensis [9]. Previous studies mainly focused on pathogen isolation and identification, as well as epidemiological investigations, and rarely considered the molecular response mechanisms of aquatic animals after infection. Likewise, the specific molecular mechanisms governing the host response to M. bicuspidata infection remain relatively unexplored, despite the growing impact of M. bicuspidata infection in E. carinicauda. Therefore, elucidating these response mechanisms is essential to establish a theoretical foundation for effective disease prevention and control. It is well established that crustaceans such as E. carinicauda lack an acquired immune system and instead rely on innate immune mechanisms, including humoral and cellular responses, to recognize and eliminate invading microorganisms [10]. The hepatopancreas is an important organ of immunity capable of secreting innate immune molecules such as synthetic ferritin, agglutinin, and antioxidant enzymes [11,12,13], and multiple immune signaling pathways, namely, the immune deficiency (IMD), Janus kinase/signal transducer and activator of transcription (JAK/STAT), and AMP-activated protein kinase (AMPK) pathways, have been identified in the hepatopancreas of crustaceans, indicating its crucial role in immune regulation [14]. It is also an important organ in crustacean physiological processes, including nutrient accumulation, energy metabolism, and lipid metabolism [15,16]. In our previous study, it was found that the hepatopancreas is an important tissue in the infection of E. carinicauda by Metschnikowia bicuspidata.
RNA-seq is an ideal analytical method for studying the molecular response mechanisms of crustaceans to pathogenic invasion, allowing a better understanding of the pathways involved in the immune response and the expression of relevant genes associated with the fight against pathogenic invasion [17,18]. Nian et al. identified by transcriptome analysis a substantial number of differentially expressed genes (DEGs) associated with immune response and metabolic processes in Procambarus clarkii before and after infection with infectious hypodermal and hematopoietic necrosis virus (IHHNV), revealing that IHHNV inhibits shrimp growth by suppressing the expression of trypsin [19]. Gao et al. discovered through a comparative transcriptomic method that M. rosenbergii responded to Enterobacter cloacae invasion by upregulating immune genes such as HSP70, SOD, and ALF2 [20].
While the “zombie disease” caused by M. bicuspidata has been described at the pathological and epidemiological levels in E. carinicauda, there is no transcriptomic characterization of host responses to this yeast infection. To explore this transcriptomic response, RNA-seq was conducted on hepatopancreatic tissue, primarily focusing on identifying DEGs and key signaling pathways involved in the host’s response to infection. The findings shed light on the immune and metabolic responses activated in the hepatopancreas during fungal invasion, offering valuable insights into host–pathogen interactions in aquatic species and providing a theoretical foundation for the prevention and control of fungal diseases in aquaculture.

2. Materials and Methods

2.1. Experimental Infection and Sample Collection of E. carinicauda

Healthy E. carinicauda individuals (average weight: 3.08 ± 0.3 g; body length: 5.8 ± 0.2 cm) were obtained from the Rudong Aquaculture Base of the Institute of Oceanology and Marine Fisheries, Jiangsu Province, Nantong, China. All shrimps were reared in two 500 L tanks at 18 ± 0.5 °C and 25 ppt for 7 days prior to experiments and were continuously aerated. During this period, 1/3 of the water in the tanks was changed every day and the shrimps were fed commercial diets. To ensure freedom from Metschnikowia bicuspidata infection, 10 individuals were randomly selected from the rearing tanks for detection. Shrimps were randomly assigned to challenge and control groups, each containing three biological replicates with 30 individuals in each replicate (n = 30).
M. bicuspidata strain MQ2101 was isolated from infected E. carinicauda and maintained under laboratory conditions. Based on preliminary experimental results, the fungal cells were resuspended in sterile normal saline and adjusted to a concentration of 2.0 × 108 cells/mL for experimental infection. Each shrimp in the challenge group was administered a 20 μL intramuscular injection of the prepared suspension, while individuals in the control group received an equivalent volume of sterile saline. At 60 h post-injection (hpi), cumulative mortality in the infected group reached 55.56%, and most surviving shrimp exhibited typical clinical signs, such as slow movement, reduced food intake, and red body color, whereas shrimp in the control group behaved normally and no deaths were recorded. The hepatopancreas tissues from three individuals were pooled to constitute one biological replicate, and a total of three replicates were collected per group (Figure 1). All samples were immediately snap-frozen in liquid nitrogen and stored at −80 °C for subsequent analysis.

2.2. RNA Extraction, cDNA Library Preparation, and Sequencing

Total RNA was extracted from the hepatopancreas of control and experimental groups using the TRIzol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer’s instructions. RNA quality was assessed with an Agilent 4200 Bioanalyzer (Agilent, Santa Calra, CA, USA) and agarose gel electrophoresis. The mRNA was enriched using Oligo(dT) beads to remove DNA, rRNA, and other artifacts, then fragmented and reverse-transcribed into cDNA. Second-strand synthesis was performed with DNA polymerase I, RNase H, and dNTPs. The cDNA was purified (Qiagen, Venlo, The Netherlands), end-repaired, A-tailed, and ligated to Illumina adapters. After size selection and PCR amplification, libraries were sequenced on the Illumina NovaSeq 6000 platform (Gene Denovo, Guangzhou, China). All the samples were processed for library construction and analysis in the same batch.

2.3. Unigene Denovo Assembly and Annotation

Raw paired-end reads generated by the Illumina platform were filtered using fastp (v0.18.0) [21] to remove adapters, reads with >10% unknown bases, or >50% low-quality bases (Q ≤ 20). The transcripts of Metschnikowia bicuspidata were removed based on the genome of Metschnikowia bicuspidata that we previously determined (BioSample: SAMN31358899). Clean reads were assembled de novo using Trinity (v2.8.4, k-mer size 31, min_k-mer_cov 4) [22]. Unigenes were functionally annotated against the Nr, Swiss-Prot, KEGG, and KOG databases using BLASTx (v2.17.0, E-value < 1 × 10−5). Protein functions were assigned based on the best alignment results.

2.4. Analysis of DEGs

The FPKM algorithm was used for gene expression calculation. Differential expression analysis of RNA transcripts was conducted using DESeq2 [23] for comparisons between experimental groups. Genes with an absolute fold change ≥ 2 and a false discovery rate (FDR) < 0.05 were identified as DEGs. GO and KEGG enrichment analyses were conducted to annotate DEGs’ functions and related pathways [24,25]. The results of the PCA are shown in Figure S1.

2.5. Validation of DEGs from RNA-Seq

To validate the RNA-seq results, 8 randomly selected DEGs were analyzed by qRT-PCR using E. carinicauda 18S rRNA as the endogenous control. Gene-specific primers (Table 1) were designed using AlleleID software (v6.0). First-strand cDNA synthesis was performed with the PrimeScript™ RT reagent kit (Takara, Beijing, China) strictly following the manufacturer’s protocol. The qRT-PCR reactions, with a final volume of 20 μL, comprised 2× Power SYBR Green PCR Master Mix, 200 nM each of forward and reverse primers, and 1 μL of cDNA template. qPCR amplification was performed under the following conditions: 95 °C for 5 min, followed by 40 cycles of 95 °C for 10 s, 57 °C for 20 s, and 72 °C for 20 s, and finally, 4 °C for 5 min. Relative mRNA expression levels, quantified using the 2−ΔΔCT method [26], and results were reported as fold changes in mRNA expression.

2.6. Statistical Analysis

Data of relative mRNA expression levels from qRT-PCR are presented as means ± standard deviations (SDs) of 3 biological replicates per group. Statistical analyses were performed using SPSS (version 18.0) only for qRT-PCR data.

3. Results

3.1. RNA-Seq Data Quality and De Novo Transcriptome Assembly

To examine transcriptional responses in the hepatopancreas of E. carinicauda following M. bicuspidata infection, total RNA was isolated from both infected and control samples. The cDNA libraries were subsequently constructed from these RNA extracts and sequenced using the Illumina high-throughput platform. Each group consisted of three biological replicates. In total, 418,308,274 high-quality clean reads were generated from the six samples. The Q30 scores exceeded 93% in all libraries, and the GC content was above 43.42%, reflecting high sequencing quality (Table 2).
Clean reads were assembled de novo using Trinity, generating 67,811 unigenes with an average length of 905 bp and an N50 value of 1977 bp. Evaluation using BUSCO indicated that the assembled transcriptome was 94.68% complete, confirming its quality and integrity (Table 3). Analysis of unigene-length distribution showed that the majority of transcripts ranged from 200 to 1000 bp (Figure 2).

3.2. Function Annotation of Unigenes

To investigate the responses of E. carinicauda to M. bicuspidata infection, we obtained the comprehensive function in the formation of unigenes by annotation with BLASTX. Of the 67,811 unigenes obtained by assembly, 22,561 (33.27%) were annotated in the Nr, KEGG, KOG, and Swissprot databases, with 12,281 (18.11%) being annotated in all four, and the remaining 45,250 (66.73%) were not matched with any database (Figure 3).
A total of 908 species were involved in the annotation of the genes obtained by assembly in the NR database, with the most homologous genes occurring in Penaeus vannamei, followed by Homo sapiens, Sparus aurata, Hyalella azteca, Armadillidium nasatum, and Trinorchestia longiramus (Figure 4). It is worth noting that the apparent enrichment of vertebrate hits (e.g., Homo sapiens and Sparus aurata) primarily reflects the biased composition and better annotation of vertebrate genomes in the NR database and homology to conserved protein domains, rather than genuine vertebrate contamination of our samples.
GO analysis showed that the predicted functions of the genes were clustered in molecular functions, biological processes, and cellular components. In biological processes, the most frequent enrichment categories were cellular processes (16,083 unigenes), metabolic processes (14,111 unigenes), and single-organism processes (13,679 unigenes). In molecular functions, the top three categories were binding (13,566 unigenes), catalytic activity (9908 unigenes), and transport activity (1887 unigenes). In cellular components, the most frequent enrichment categories were cells (12,284 unigenes), cell parts (12,271 unigenes), and organelles (9939 unigenes) (Figure 5).
The KEGG database facilitates the systematic analysis of gene product functions and their involvement in cellular metabolic pathways. After enrichment analysis, a total of 20,165 unigenes were found to be annotated in the KEGG pathway and were then further classified into 6 first category pathways and 47 subcategory pathways. Among the 47 subclasses of KEGG pathways, global and overview maps were dominant, containing 2406 unigenes, followed by infectious diseases (1982 unigenes), signal transduction (1760 unigenes), and cancers (1210 unigenes). Notably, the immune system pathway was also annotated to 873 unigenes (Figure 6).

3.3. Identification and Analysis of DEGs

To identify DEGs involved in the hepatopancreatic response of E. carinicauda to M. bicuspidata infection, transcriptome data were analyzed using a false discovery rate (FDR) < 0.05 and an absolute fold change ≥ 2 (Figure 7A). Clustering of DEGs from three biological replicates per group was performed to evaluate expression consistency (Figure 7B). A total of 1991 DEGs were identified, including 1224 upregulated and 767 downregulated genes.

3.4. Analysis of Differentially Expressed Genes

According to GO classification, the DEGs were categorized into 26 biological process subcategories, 23 cellular component subcategories, and 16 molecular function subcategories. Among the biological processes, cellular processes, single-organism processes, and metabolic processes were the most enriched. In the cellular component category, cells, cell parts, and organelles were predominant. For molecular functions, the most represented terms were binding, catalytic activity, and transporter activity (Figure 8). Notably, some DEGs were classified as pattern recognition receptors and antioxidant systems and may be directly involved in the immune response of shrimp. In addition, KEGG pathway enrichment analysis was conducted to investigate the functional implications of gene expression alterations associated with Metschnikowia bicuspidata infection. As a result, the identified DEGs were mapped to a total of 322 KEGG pathways. The top 15 most enriched pathways are shown in Figure 9, among which the immune-related pathways are mainly the lysosome, apoptosis, and AMPK signaling pathways. Moreover, we found that the metabolic pathways of the infected E. carinicauda were significantly affected, such as glycerophospholipid metabolism, protein digestion, and absorption. We list some representative DEGs associated with immunity and metabolism in Table 4.

3.5. Validation of DEGs from RNA-Seq

To further validate the reliability of our transcripts, we randomly selected eight genes, four upregulated and four downregulated, to perform RT-PCR validation analysis. Figure 10 shows that the expression trends of the randomly selected genes are consistent with the RNA-seq results, indicating that the gene expression results obtained from sequencing data analysis are reliable.

4. Discussion

E. carinicauda is an important economic aquaculture species in coastal areas of China, but its culture has been limited due to frequent disease outbreaks. The newly recognized pathogen M. bicuspidata has caused serious economic losses in E. carinicauda culture, yet the molecular interactions between E. carinicauda and this yeast remain uncharacterized. In the absence of adaptive immunity, E. carinicauda predominantly relies on innate immune mechanisms, comprising humoral and cellular responses, with the hepatopancreas functioning as a central immune organ [27]. Therefore, this study investigated the molecular response mechanisms in the hepatopancreas of E. carinicauda at 60 hpi using comparative transcriptome sequencing. A total of 1991 DEGs were detected from the transcriptome data, comprising 1224 upregulated and 767 downregulated genes. Further functional characterization of these DEGs revealed their involvement in innate immunity and metabolic functions, and the results provide insights into the molecular mechanisms underlying E. carinicauda’s response to M. bicuspidata infection. The immune competence of shrimp is governed mainly by the innate immune system, the activation of which begins when pattern recognition receptors (PRRs) recognize and bind to conserved molecular patterns on pathogens, subsequently inducing coordinated cellular and humoral defense responses [28]. Scavenger receptor class B (SR-B) is a transmembrane receptor that mediates ligand recognition based on its heavily glycosylated extracellular structural domain with specific ligand binding sites [29,30] and has been identified as a PPR in shrimp, for example, contributing to innate immunity in Marsupenaeus japonicus [31]. In agreement with this, our results showed a significant upregulation of SR-B expression. C-type lectin (CTL) is a well-studied PRR in crustaceans, relying mainly on its carbohydrate recognition structure for its function [32]. Here, we found and verified that CTL was upregulated 60 h after infection in E. carinicauda. β-1,3-glucan constitutes the main component of the yeast cell wall, and, interestingly, CTL has been reported to be a β-glucan recognition receptor in aquatic animals [33]. Therefore, after infection of E. carinicauda, it may be possible to recognize the pathogen by upregulating PRRs such as CTL and SRB, which, in turn, stimulates a series of immune responses in the shrimp.
The lysosome is involved in a variety of physiological processes, such as maintaining cellular homeostasis [34], and participates in body metabolism and immune responses [35,36]. Cathepsin B (CTSB) is a typical lysosomal cysteine protease that takes part in pathological and physiological processes in living organisms [37]. In lysosomal degradation of exogenous pathogens, the pathogen is first endocytosed through cellular endocytosis, leading to microbial DNA exposure and recognition by TLR9 in the lysosome, and CTSB plays an integral role in TLR9 recognition [38]. In addition, CTSB is also involved in immune responses such as post-translational processing of TNF-a in macrophages [39]. Previous studies have found increased CTSB expression after infection with pathogens in Trachinotus ovatus [37] and Fenneropenaeus chinensis [40]. Similarly, in our DEG analysis, we found that CTSB was upregulated after infection, and a large number of genes in the lysosome pathway were significantly altered, among which CTSA and LIPA were upregulated (and their involvement in the innate immune process has been confirmed [36,41]). These findings suggest that lysosomal function in the hepatopancreas is activated after infection to protect the shrimp from invasion by exogenous pathogens.
Pathogen infestation increases the production of reactive oxygen species (ROS) in the body, leading to oxidative stress [42]. Excessive cellular ROS production can damage a range of cellular macromolecules such as proteins, lipids, and DNA, and it is also regulated by the antioxidant system [43]. Glutathione S-transferase (GST) functions as a key enzyme in cellular antioxidant defense, protecting cells from oxidative damage and restoring systemic redox homeostasis by promoting glutathione conjugation with toxic molecules to facilitate detoxification and eliminating lipid peroxidation products that disrupt redox balance [44]. In our dataset, a GST transcript was significantly downregulated in the infected hepatopancreas at 60 hpi, which suggests that antioxidant-related processes may be modulated during M. bicuspidata challenge. However, because we did not directly measure ROS levels, antioxidant enzyme activities, or tissue damage, we cannot distinguish whether the decrease in GST expression is a primary effect of infection on the antioxidant system or a secondary response to pre-existing oxidative injury. Therefore, future studies combining transcriptomics with biochemical assays of ROS and antioxidant enzymes are required to clarify the causal relationship between oxidative stress, tissue damage, and GST regulation in E. carinicauda.
The hepatopancreas is a key metabolic organ, and our results revealed substantial DEG enrichment in several metabolic pathways following infection, including the glycerophospholipid and glycerolipid metabolism, tryptophan metabolism, ascorbate and aldarate metabolism, and glycine, serine, and threonine metabolism, suggesting infection-induced disturbance of essential metabolic processes. It is suggested that M. bicuspidata infection may affect the health of E. carinicauda by affecting changes in the metabolic function of the organism. It is worth mentioning that numerous DEGs are involved in the glycerophospholipid metabolic pathway, which corresponds to the results following V. alginolyticus infestation of L. vannamei. As universal components of biological membranes, glycerophospholipids contribute to the recognition of signaling proteins transmitted across cell membranes and are crucial for cellular recognition, signal transduction, and adaptive responses to environmental stimuli [35]. Acyltransferases play a central role in glycerophospholipid metabolism by mediating the remodeling of phospholipid fatty acid chains, thereby maintaining membrane integrity and preventing damage caused by lysophospholipids [45,46]. Our results showed that LPCAT1 and AGPAT1 expressions were significantly reduced at 60 hpi. Given their roles in phospholipid remodeling, these transcriptional changes suggest a potential disturbance of hepatopancreatic lysophospholipid metabolism during M. bicuspidata infection, which may contribute to hepatopancreatic dysfunction and the host pathology. This remains a working hypothesis and should be tested in future studies incorporating lipid profiling and functional assays.
Apoptosis serves as an essential defense mechanism against both pathogen invasion and environmental stress [47]. By precisely regulating programmed cell death, organisms can suppress pathogen replication within infected cells while simultaneously promoting immune activation through cytokine secretion from apoptotic cells [48]. In our DEG analysis, we found that apoptosis pathway-related genes such as those encoding CASP2, CASP7, CYTC, and CTSL were significantly differentially expressed. The activation of the caspase family cascade is a key process in apoptosis [49]. Based on transcriptomic data, we found that the expression of CASP2 and CASP7 was upregulated in the hepatopancreas of the infected E. carinicauda, consistent with the response of Chinese mitten crabs affected by microcystin-LR [50]. Cytochrome c (CYTC) plays the following crucial role in apoptosis: In the initial stage of apoptosis, dissipation of the mitochondrial membrane potential results in the detachment of CYTC from the inner membrane. The protein is then translocated into the cytoplasm via outer membrane pores, ultimately initiating CASP7 activation and apoptotic progression [51,52,53]. Lack of CTSL was reported to induce apoptosis in a mouse model of pancreatitis [54], and, notably, in the present experiment, CTSL expression was inhibited, which may have promoted the apoptotic process in the organism. In this experiment, the majority of genes in the apoptotic pathway, including CASP2, CASP7, and CYTC, were significantly upregulated, whereas CTSL was downregulated, indicating that apoptosis-related processes are activated during M. bicuspidata infection. We speculate that apoptosis may be associated with metabolic disorders and sustained immune activation after pathogen infestation and could help remove excess, damaged, or potentially dangerous cells. These interpretations are based solely on transcriptomic data, and future studies should verify them by performing specific apoptosis assays.

5. Conclusions

In this study, high-throughput sequencing technology was used to perform transcriptome sequencing analysis before and after infection of E. carinicauda with M. bicuspidata. The resulting genes were compared and annotated, revealing 1991 DEGs. We found that, after invasion by M. bicuspidata, the hepatopancreas activated genes related to pattern recognition receptors, the lysosome, and apoptosis to fight against the foreign pathogen, and genes related to the antioxidant system and glycerophospholipid metabolism were suppressed. Our results provide reliable transcriptomic data and useful information on the molecular response mechanism of E. carinicauda after infection with M. bicuspidate, offering valuable information for the control and prevention of the disease.
Nevertheless, this study has several limitations. First, we analyzed only one tissue (hepatopancreas) at a single time point (60 hpi), which limits our insight into both temporal dynamics and systemic responses. Second, fungal burden, oxidative stress markers, lipid composition, and apoptosis were not directly measured, so causal links between transcriptomic changes and clinical or histopathological outcomes cannot be established. Future studies incorporating time course sampling, multiple tissues, and targeted physiological and biochemical assays are needed to rigorously test the hypotheses generated from this transcriptomic dataset.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/fishes10120628/s1, Figure S1: Sample relationship. PCA (left) and Cluster (right).

Author Contributions

R.Z., W.S. and X.W. designed the study. R.Z., H.L. and L.W. performed the experiment. W.S., R.Z. and X.W. analyzed the data. W.S. and R.Z. wrote the manuscript. X.W. review the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by The Nantong City Natural Science Foundation Project (JC2023085) and Aquatic Breeding Germplasm Conservation Project (2025-SJCG-005-03).

Institutional Review Board Statement

All samples and methods used in the present study were conducted in accordance with the Laboratory Animal Management Principles of China. The animal study protocol was approved by the Laboratory Animal Ethic Committee of the Institute of Oceanology & Marine Fisheries, Jiangsu (protocol code LAEC-IOMFJ-2022-02-001XX and approval date: 28 February 2022). All shrimps handling performed under ice anaesthesia.

Data Availability Statement

Transcriptome data involved in this present study have been deposited in Sequences Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra (accessed on 14 October 2023)), the accession number of our submission is SUB12155917 or PRJNA890436.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Wang, J.; Feng, G.; Han, Z.; Zhang, T.; Chen, J.; Wu, J. Insights into the Intestinal Microbiota of Exopalaemon annandalei and Exopalaemon carinicauda in the Yangtze River Estuary. Front. Cell. Infect. Microbiol. 2024, 14, 1420928. [Google Scholar] [CrossRef] [PubMed]
  2. Wang, J.; Lv, J.; Shi, M.; Ge, Q.; Wang, Q.; He, Y.; Li, J.; Li, J. Chromosome-Level Genome Assembly of Ridgetail White Shrimp Exopalaemon carinicauda. Sci. Data 2024, 11, 576. [Google Scholar] [CrossRef]
  3. Xiao, J.; Miao, X.; Li, C.; Xu, W.; Zhang, X.; Wang, Z. Genetic Variations of the Parasitic Dinoflagellate Hematodinium Infecting Cultured Marine Crustaceans in China. Protist 2016, 167, 597–609. [Google Scholar] [CrossRef]
  4. Ge, Q.; Li, J.; Li, J.; Wang, J.; Li, Z. Immune Response of Exopalaemon carinicauda Infected with an AHPND-Causing Strain of Vibrio parahaemolyticus. Fish Shellfish Immunol. 2018, 74, 223–234. [Google Scholar] [CrossRef]
  5. Duan, Y.; Liu, P.; Li, J.; Wang, Y.; Li, J.; Chen, P. Molecular Responses of Calreticulin Gene to Vibrio anguillarum and WSSV Challenge in the Ridgetail White Prawn Exopalaemon carinicauda. Fish Shellfish Immunol. 2014, 36, 164–171. [Google Scholar] [CrossRef]
  6. Zhao, R.; Shi, W.; Wang, L.; Li, H.; Yu, Z.; Hu, R.; Wu, X.; Shen, H.; Qi, Y.; Chen, J.; et al. A preliminary study on the “Zombie disease” of Exopalaemon carinicauda. J. Fish. China 2022, 47, 099414. (In Chinese) [Google Scholar] [CrossRef]
  7. Chen, S.; Chen, T.; Wang, P.; Chen, Y.; Huang, J.; Lin, Y.; Chaung, H. Metschnikowia bicuspidata and Enterococcus Faecium Co-Infection in the Giant Freshwater Prawn Macrobrachium rosenbergii. Dis. Aquat. Org. 2003, 55, 161–167. [Google Scholar] [CrossRef] [PubMed]
  8. Wang, L.; Yue, L.; Chi, Z.; Wang, X. Marine Killer Yeasts Active against a Yeast Strain Pathogenic to Crab Portunus trituberculatus. Dis. Aquat. Org. 2008, 80, 211–218. [Google Scholar] [CrossRef]
  9. Bao, J.; Jiang, H.; Shen, H.; Xing, Y.; Feng, C.; Li, X.; Chen, Q. First Description of Milky Disease in the Chinese Mitten Crab Eriocheir sinensis Caused by the Yeast Metschnikowia bicuspidata. Aquaculture 2021, 532, 735984. [Google Scholar] [CrossRef]
  10. Shi, T.; Gao, J.; Xu, W.; Liu, X.; Yan, B.; Azra, M.N.; Baloch, W.A.; Wang, P.; Gao, H. The Mannose-Binding Lectin (MBL) Gene Cloned from Exopalaemon carinicauda Plays a Key Role in Resisting Infection by Vibrio parahaemolyticus. Comp. Biochem. Physiol. Part B Biochem. Mol. Biol. 2024, 274, 111001. [Google Scholar] [CrossRef] [PubMed]
  11. Yang, H.; Liu, Z.; Jiang, Q.; Xu, J.; An, Z.; Zhang, Y.; Xiong, D.; Wang, L. A Novel Ferritin Gene from Procambarus clarkii Involved in the Immune Defense against Aeromonas hydrophila Infection and Inhibits WSSV Replication. Fish Shellfish Immunol. 2019, 86, 882–891. [Google Scholar] [CrossRef] [PubMed]
  12. Zheng, J.; Mao, Y.; Su, Y.; Wang, J. Identification of Two Novel C-Type Lectins Involved in Immune Defense against White Spot Syndrome Virus and Vibrio parahaemolyticus from Marsupenaeus japonicus. Aquaculture 2020, 519, 734797. [Google Scholar] [CrossRef]
  13. Zhao, W.; Wang, L.; Liu, M.; Jiang, K.; Wang, M.; Yang, G.; Qi, C.; Wang, B. Transcriptome, Antioxidant Enzyme Activity and Histopathology Analysis of Hepatopancreas from the White Shrimp Litopenaeus vannamei Fed with Aflatoxin B1(AFB1). Dev. Comp. Immunol. 2017, 74, 69–81. [Google Scholar] [CrossRef] [PubMed]
  14. Yi, C.; Lv, X.; Chen, D.; Sun, B.; Guo, L.; Wang, S.; Ru, Y.; Wang, H.; Zeng, Q. Transcriptome Analysis of the Macrobrachium nipponense Hepatopancreas Provides Insights into Immunoregulation under Aeromonas veronii Infection. Ecotoxicol. Environ. Saf. 2021, 208, 111503. [Google Scholar] [CrossRef] [PubMed]
  15. Fu, Y.; Zhang, F.; Ma, C.; Wang, W.; Liu, Z.; Chen, W.; Zhao, M.; Ma, L. Comparative Metabolomics and Lipidomics of Four Juvenoids Application to Scylla paramamosain Hepatopancreas: Implications of Lipid Metabolism During Ovarian Maturation. Front. Endocrinol. 2022, 13, 886351. [Google Scholar] [CrossRef]
  16. Zhu, J.; Shi, W.; Zhao, R.; Gu, C.; Shen, H.; Li, H.; Wang, L.; Cheng, J.; Wan, X. Integrated Physiological, Transcriptome, and Metabolome Analyses of the Hepatopancreas of Litopenaeus vannamei under Cold Stress. Comp. Biochem. Physiol. Part D Genom. Proteom. 2024, 49, 101196. [Google Scholar] [CrossRef]
  17. Metzker, M.L. Sequencing Technologies—The next Generation. Nat. Rev. Genet. 2010, 11, 31–46. [Google Scholar] [CrossRef]
  18. Wang, Z.; Gerstein, M.; Snyder, M. RNA-Seq: A Revolutionary Tool for Transcriptomics. Nat. Rev. Genet. 2009, 10, 57–63. [Google Scholar] [CrossRef]
  19. Nian, Y.-Y.; Chen, B.-K.; Wang, J.-J.; Zhong, W.-T.; Fang, Y.; Li, Z.; Zhang, Q.-S.; Yan, D.-C. Transcriptome Analysis of Procambarus clarkii Infected with Infectious Hypodermal and Haematopoietic Necrosis Virus. Fish Shellfish Immunol. 2020, 98, 766–772. [Google Scholar] [CrossRef]
  20. Gao, X.; Jiang, Z.; Zhang, S.; Chen, Q.; Tong, S.; Liu, X.; Jiang, Q.; Yang, H.; Wei, W.; Zhang, X. Transcriptome Analysis and Immune-Related Genes Expression Reveals the Immune Responses of Macrobrachium rosenbergii Infected by Enterobacter cloacae. Fish Shellfish Immunol. 2020, 101, 66–77. [Google Scholar] [CrossRef]
  21. Chen, S.; Zhou, Y.; Chen, Y.; Gu, J. Fastp: An Ultra-Fast All-in-One FASTQ Preprocessor. Bioinformatics 2018, 34, i884–i890. [Google Scholar] [CrossRef] [PubMed]
  22. Grabherr, M.G.; Haas, B.J.; Yassour, M.; Levin, J.Z.; Thompson, D.A.; Amit, I.; Adiconis, X.; Fan, L.; Raychowdhury, R.; Zeng, Q.; et al. Full-Length Transcriptome Assembly from RNA-Seq Data without a Reference Genome. Nat. Biotechnol. 2011, 29, 644–652. [Google Scholar] [CrossRef] [PubMed]
  23. Love, M.I.; Huber, W.; Anders, S. Moderated Estimation of Fold Change and Dispersion for RNA-Seq Data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef]
  24. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T.; et al. Gene Ontology: Tool for the Unification of Biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef]
  25. Kanehisa, M.; Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000, 28, 27–30. [Google Scholar] [CrossRef]
  26. Livak, K.J.; Schmittgen, T.D. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  27. Amparyup, P.; Charoensapsri, W.; Tassanakajon, A. Prophenoloxidase System and Its Role in Shrimp Immune Responses against Major Pathogens. Fish Shellfish Immunol. 2013, 34, 990–1001. [Google Scholar] [CrossRef]
  28. Sánchez-Salgado, J.L.; Pereyra, M.A.; Alpuche-Osorno, J.J.; Zenteno, E. Pattern Recognition Receptors in the Crustacean Immune Response against Bacterial Infections. Aquaculture 2021, 532, 735998. [Google Scholar] [CrossRef]
  29. Kar, N.S.; Ashraf, M.Z.; Valiyaveettil, M.; Podrez, E.A. Mapping and Characterization of the Binding Site for Specific Oxidized Phospholipids and Oxidized Low Density Lipoprotein of Scavenger Receptor CD36. J. Biol. Chem. 2008, 283, 8765–8771. [Google Scholar] [CrossRef]
  30. Silverstein, R.L.; Febbraio, M. CD36, a Scavenger Receptor Involved in Immunity, Metabolism, Angiogenesis, and Behavior. Sci. Signal. 2009, 2, re3. [Google Scholar] [CrossRef]
  31. Bi, W.-J.; Li, D.-X.; Xu, Y.-H.; Xu, S.; Li, J.; Zhao, X.-F.; Wang, J.-X. Scavenger Receptor B Protects Shrimp from Bacteria by Enhancing Phagocytosis and Regulating Expression of Antimicrobial Peptides. Dev. Comp. Immunol. 2015, 51, 10–21. [Google Scholar] [CrossRef]
  32. Willment, J.A.; Gordon, S.; Brown, G.D. Characterization of the Human β-Glucan Receptor and Its Alternatively Spliced Isoforms. J. Biol. Chem. 2001, 276, 43818–43823. [Google Scholar] [CrossRef]
  33. Wiegertjes, G.F. Studies into β-Glucan Recognition in Fish Suggests a Key Role for the C-Type Lectin Pathway. Front. Immunol. 2019, 10, 280. [Google Scholar]
  34. Cui, X.; Liu, H.; Li, J.; Guo, K.; Han, W.; Dong, Y.; Wan, S.; Wang, X.; Jia, P.; Li, S.; et al. Heat Shock Factor 4 Regulates Lens Epithelial Cell Homeostasis by Working with Lysosome and Anti-Apoptosis Pathways. Int. J. Biochem. Cell Biol. 2016, 79, 118–127. [Google Scholar] [CrossRef]
  35. Yin, X.; Zhuang, X.; Liao, M.; Huang, L.; Cui, Q.; Liu, C.; Dong, W.; Wang, F.; Liu, Y.; Wang, W. Transcriptome Analysis of Pacific White Shrimp (Litopenaeus vannamei) Hepatopancreas Challenged by Vibrio Alginolyticus Reveals Lipid Metabolic Disturbance. Fish Shellfish Immunol. 2022, 123, 238–247. [Google Scholar] [CrossRef]
  36. Liang, F.; Sun, C.; Li, S.; Hou, T.; Li, C. Therapeutic Effect and Immune Mechanism of Chitosan-Gentamicin Conjugate on Pacific White Shrimp (Litopenaeus vannamei) Infected with Vibrio parahaemolyticus. Carbohydr. Polym. 2021, 269, 118334. [Google Scholar] [CrossRef] [PubMed]
  37. Shen, Y.; Zhang, H.; Zhou, Y.; Sun, Y.; Yang, H.; Cao, Z.; Qin, Q.; Liu, C.; Guo, W. Functional Characterization of Cathepsin B and Its Role in the Antimicrobial Immune Responses in Golden Pompano (Trachinotus ovatus). Dev. Comp. Immunol. 2021, 123, 104128. [Google Scholar] [CrossRef] [PubMed]
  38. Matsumoto, F.; Saitoh, S.; Fukui, R.; Kobayashi, T.; Tanimura, N.; Konno, K.; Kusumoto, Y.; Akashi-Takamura, S.; Miyake, K. Cathepsins Are Required for Toll-like Receptor 9 Responses. Biochem. Biophys. Res. Commun. 2008, 367, 693–699. [Google Scholar] [CrossRef]
  39. Garcia-Cattaneo, A.; Gobert, F.-X.; Müller, M.; Toscano, F.; Flores, M.; Lescure, A.; Del Nery, E.; Benaroch, P. Cleavage of Toll-like Receptor 3 by Cathepsins B and H Is Essential for Signaling. Proc. Natl. Acad. Sci. USA 2012, 109, 9053–9058. [Google Scholar] [CrossRef] [PubMed]
  40. Li, X.; Meng, X.; Kong, J.; Luo, K.; Luan, S.; Cao, B.; Liu, N.; Pang, J.; Shi, X. Molecular Cloning and Characterization of a Cathepsin B Gene from the Chinese Shrimp Fenneropenaeus chinensis. Fish Shellfish Immunol. 2013, 35, 1604–1612. [Google Scholar] [CrossRef]
  41. Ren, Q.; Zhang, X.-W.; Sun, Y.-D.; Sun, S.-S.; Zhou, J.; Wang, Z.-H.; Zhao, X.-F.; Wang, J.-X. Two Cysteine Proteinases Respond to Bacterial and WSSV Challenge in Chinese White Shrimp Fenneropenaeus chinensis. Fish Shellfish Immunol. 2010, 29, 551–556. [Google Scholar] [CrossRef] [PubMed]
  42. Velásquez, A.M.A.; Bartlett, P.J.; Linares, I.A.P.; Passalacqua, T.G.; Teodoro, D.D.L.; Imamura, K.B.; Virgilio, S.; Tosi, L.R.O.; Leite, A.D.L.; Buzalaf, M.A.R.; et al. New Insights into the Mechanism of Action of the Cyclopalladated Complex (CP2) in Leishmania: Calcium Dysregulation, Mitochondrial Dysfunction, and Cell Death. Antimicrob. Agents Chemother. 2022, 66, e00767-21. [Google Scholar] [CrossRef] [PubMed]
  43. Estrada-Cárdenas, P.; Camacho-Jiménez, L.; Peregrino-Uriarte, A.B.; Contreras-Vergara, C.A.; Hernandez-López, J.; Yepiz-Plascencia, G. P53 Knock-down and Hypoxia Affects Glutathione Peroxidase 4 Antioxidant Response in Hepatopancreas of the White Shrimp Litopenaeus vannamei. Biochimie 2022, 199, 1–11. [Google Scholar] [CrossRef]
  44. Miao, Z.Q.; Tu, Y.Q.; Guo, P.Y.; He, W.; Jing, T.X.; Wang, J.J.; Wei, D.D. Antioxidant Enzymes and Heat Shock Protein Genes from Liposcelis bostrychophila Are Involved in Stress Defense upon Heat Shock. Insects 2020, 11, 839. [Google Scholar] [CrossRef]
  45. Heath, R.J.; Rock, C.O. A Conserved Histidine Is Essential for Glycerolipid Acyltransferase Catalysis. J. Bacteriol. 1998, 180, 1425–1430. [Google Scholar] [CrossRef]
  46. Abate, W.; Alrammah, H.; Kiernan, M.; Tonks, A.J.; Jackson, S.K. Lysophosphatidylcholine Acyltransferase 2 (LPCAT2) Co-Localises with TLR4 and Regulates Macrophage Inflammatory Gene Expression in Response to LPS. Sci. Rep. 2020, 10, 10355. [Google Scholar] [CrossRef]
  47. Gervais, O.; Renault, T.; Arzul, I. Molecular and Cellular Characterization of Apoptosis in Flat Oyster a Key Mechanisms at the Heart of Host-Parasite Interactions. Sci. Rep. 2018, 8, 12494. [Google Scholar] [CrossRef]
  48. Nagata, S.; Tanaka, M. Programmed Cell Death and the Immune System. Nat. Rev. Immunol. 2017, 17, 333–340. [Google Scholar] [CrossRef]
  49. Jaree, P.; Somboonwiwat, K. DnaJC16, the Molecular Chaperone, Is Implicated in Hemocyte Apoptosis and Facilitates of WSSV Infection in Shrimp. Fish Shellfish Immunol. 2023, 137, 108770. [Google Scholar] [CrossRef] [PubMed]
  50. Chi, C.; Giri, S.S.; Yu, X.W.; Liu, Y.; Chen, K.K.; Liu, W.B.; Zhang, D.D.; Jiang, G.Z.; Li, X.F.; Gao, X.; et al. Lipid Metabolism, Immune and Apoptosis Transcriptomic Responses of the Hepatopancreas of Chinese Mitten Crab to the Exposure to Microcystin-LR. Ecotoxicol. Environ. Saf. 2022, 236, 113439. [Google Scholar] [CrossRef]
  51. Kalpage, H.A.; Wan, J.; Morse, P.T.; Zurek, M.P.; Turner, A.A.; Khobeir, A.; Yazdi, N.; Hakim, L.; Liu, J.; Vaishnav, A.; et al. Cytochrome c Phosphorylation: Control of Mitochondrial Electron Transport Chain Flux and Apoptosis. Int. J. Biochem. Cell Biol. 2020, 121, 105704. [Google Scholar] [CrossRef] [PubMed]
  52. Orrenius, S.; Zhivotovsky, B. Cardiolipin Oxidation Sets Cytochrome c Free. Nat. Chem. Biol. 2005, 1, 188–189. [Google Scholar] [CrossRef]
  53. Green, D.R.; Kroemer, G. The Pathophysiology of Mitochondrial Cell Death. Science 2004, 305, 626–629. [Google Scholar] [CrossRef] [PubMed]
  54. Wartmann, T.; Mayerle, J.; Kähne, T.; Sahin–Tóth, M.; Ruthenbürger, M.; Matthias, R.; Kruse, A.; Reinheckel, T.; Peters, C.; Weiss, F.U.; et al. Cathepsin L Inactivates Human Trypsinogen, Whereas Cathepsin L-Deletion Reduces the Severity of Pancreatitis in Mice. Gastroenterology 2010, 138, 726–737. [Google Scholar] [CrossRef] [PubMed]
Fishes 10 00628 g001
Figure 1. Flow chart of artificial injection infection in E. carinicauda.
Figure 1. Flow chart of artificial injection infection in E. carinicauda.
Fishes 10 00628 g001
Fishes 10 00628 g002
Figure 2. Length distribution of unigenes.
Figure 2. Length distribution of unigenes.
Fishes 10 00628 g002
Fishes 10 00628 g003
Figure 3. Venn diagram of unigenes annotated in KOG, KEGG, NR, and Swiss-Prot. The numbers indicate the number of unigenes annotated in each database and in their overlaps.
Figure 3. Venn diagram of unigenes annotated in KOG, KEGG, NR, and Swiss-Prot. The numbers indicate the number of unigenes annotated in each database and in their overlaps.
Fishes 10 00628 g003
Fishes 10 00628 g004
Figure 4. Several species with high contribution values in the NR database.
Figure 4. Several species with high contribution values in the NR database.
Fishes 10 00628 g004
Fishes 10 00628 g005
Figure 5. GO annotation analysis of all unigenes.
Figure 5. GO annotation analysis of all unigenes.
Fishes 10 00628 g005
Fishes 10 00628 g006
Figure 6. KEGG annotation analysis of all unigenes.
Figure 6. KEGG annotation analysis of all unigenes.
Fishes 10 00628 g006
Fishes 10 00628 g007
Figure 7. Overview of differently expressed genes between M. bicuspidata infected and non-infected in E. carinicauda. (A) Volcano plot showing upregulated genes (red), downregulated genes (blue), and non-significant genes (black) (the horizontal dotted line represents FDR < 0.05 and the vertical dotted lines represent an absolute fold change ≥ 2) (B) Heatmap of DEGs, where each column represents a sample and each row a gene; red indicates higher expression levels, blue indicates lower expression.
Figure 7. Overview of differently expressed genes between M. bicuspidata infected and non-infected in E. carinicauda. (A) Volcano plot showing upregulated genes (red), downregulated genes (blue), and non-significant genes (black) (the horizontal dotted line represents FDR < 0.05 and the vertical dotted lines represent an absolute fold change ≥ 2) (B) Heatmap of DEGs, where each column represents a sample and each row a gene; red indicates higher expression levels, blue indicates lower expression.
Fishes 10 00628 g007
Fishes 10 00628 g008
Figure 8. GO enrichment analysis of most DEGs after M. bicuspidata infection.
Figure 8. GO enrichment analysis of most DEGs after M. bicuspidata infection.
Fishes 10 00628 g008
Fishes 10 00628 g009
Figure 9. KEGG pathway enrichment analysis of DEGs after M. bicuspidata infection.
Figure 9. KEGG pathway enrichment analysis of DEGs after M. bicuspidata infection.
Fishes 10 00628 g009
Fishes 10 00628 g010
Figure 10. Validation of DEGs with qRT-PCR.
Figure 10. Validation of DEGs with qRT-PCR.
Fishes 10 00628 g010
Table 1. Primer sequences of genes verified by qRT-PCR.
Table 1. Primer sequences of genes verified by qRT-PCR.
GeneDescriptionPrimer Sequence (5′ to 3′)
ARSBArylsulfatase B-likeF-CGTCAGGTCCAACATCATCC
R-CTTCGTTCGCCAGTTCTTCC
CTSBCathepsin BF-TAATACTGGGTGTGGTGTGTG
R-TACTTTGAGTCGGGATGAACG
CTLC-type lectinF-CAATACGACAGTCTGGGCTTC
R-CGCACCTCCATCAACATCAG
fth1-aFerritinF-GAGACGATGTTGCTCTTCCTG
R-TCCACCACGGCTGTTCTG
CTSLCathepsin LF-CGACTGCTAACGAAAGATGGG
R-CGGTAGTTGAAGGTTCTGGAAG
GSTGlutathione S-transferaseF-ATACTTAGCCAACCAGCAACAG
R-ACGAGGCAAACTTCTTGATAGC
PlgTrypsinF-AGGCACAGAACAGCGTATAAC
R-TCCAGCAACTTCACACATTCC
SorbSorbitol dehydrogenase-likeF-TGCTTTCATTCGGCTGCTG
R-ACCTTCCTCTTGGCTGACG
EC18S18S ribosomalF-ACCTATCCTGAGTGCCTAAGC
R-CTTCGTCCTTCCATCTTCTGC
Table 2. Summary of RNA-seq data quality metrics across all samples.
Table 2. Summary of RNA-seq data quality metrics across all samples.
SampleRaw ReadsClean ReadsClean BasesQ20 (%)Q30 (%)GC (%)
C-173,264,63872,853,97810,875,846,06097.4693.1143.69
C-269,762,45669,449,58410,367,317,03397.7693.6343.91
C-372,742,58672,387,82410,804,261,76397.9093.9043.42
T-169,891,13069,590,13010,380,228,57497.8193.7543.70
T-265,801,93665,524,9789,779,274,27897.7293.5743.93
T-368,803,89468,501,78010,219,018,61097.6193.3443.90
Table 3. Transcriptome assembly, annotation overview and BUSCO assessment.
Table 3. Transcriptome assembly, annotation overview and BUSCO assessment.
CategoryNumber
Transcriptome statistics
Number of genes67,811
Total size of transcripts (bp)61,403,893
GC percentage (%)39.1699
N50 number7792
N50 length1977
Max length35,367
Min length201
Average length905
BUSCO Completeness
Complete BUSCOs94.68%
single86.61%
Duplicated8.07%
Fragmented2.15%
Missing3.17%
Table 4. Representative DEGs at 60 h after M. bicuspidata infection.
Table 4. Representative DEGs at 60 h after M. bicuspidata infection.
GeneDescriptionFlod Change
pattern recognition receptors
CTLC-type lectin8.19
SR-BScavenger receptor class B4.09
Lysosome
CTSBCathepsin B3.88
CTSACathepsin A14.19
LIPALysosomal acid lipase4.55
ARSBArylsulfatase B2.39
Antioxidant system
GSTGlutathione S-transferase−2.09
Glycerophospholipid metabolism
MBOAT1lysophospholipid acyltransferase−2.67
AGPAT1lysophosphatidiate acyltransferase−4.58
Apoptosis
CASP2Caspase 22.44
CASP7Caspase 72.74
CYTCCytochrome c3.35
CTSLCathepsin L−4.03
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhao, R.; Li, H.; Wang, L.; Shi, W.; Wan, X. Transcriptome Analysis Reveals the Mechanisms of Organismal Response in Exopalaemon carinicauda Infected by Metschnikowia bicuspidata. Fishes 2025, 10, 628. https://doi.org/10.3390/fishes10120628

AMA Style

Zhao R, Li H, Wang L, Shi W, Wan X. Transcriptome Analysis Reveals the Mechanisms of Organismal Response in Exopalaemon carinicauda Infected by Metschnikowia bicuspidata. Fishes. 2025; 10(12):628. https://doi.org/10.3390/fishes10120628

Chicago/Turabian Style

Zhao, Ran, Hui Li, Libao Wang, Wenjun Shi, and Xihe Wan. 2025. "Transcriptome Analysis Reveals the Mechanisms of Organismal Response in Exopalaemon carinicauda Infected by Metschnikowia bicuspidata" Fishes 10, no. 12: 628. https://doi.org/10.3390/fishes10120628

APA Style

Zhao, R., Li, H., Wang, L., Shi, W., & Wan, X. (2025). Transcriptome Analysis Reveals the Mechanisms of Organismal Response in Exopalaemon carinicauda Infected by Metschnikowia bicuspidata. Fishes, 10(12), 628. https://doi.org/10.3390/fishes10120628

Article Metrics

Back to TopTop