Abstract

   High temperatures in summer often trigger disease outbreaks in shrimp,
   resulting in significant economic losses. To investigate the heat
   tolerance mechanisms of Penaeus monodon, juvenile tiger shrimp were
   subjected to a high-temperature stress of 38 °C for 144 h. The
   cumulative survival rate of shrimp sharply decreased to 5.29% in the
   later 144 h. The heat-sensitive shrimps (S group) were collected in the
   first 24 h, while those that survived beyond 120 h were collected as
   the heat-tolerant group (T group). The hepatopancreas of two groups was
   subjected to transcriptomic and metabolomic analysis. The results
   revealed that, compared to the S group, the T group exhibited a total
   of 3527 DEGs, including 2199 upregulated and 1328 downregulated genes.
   Additionally, 353 DAMs were identified in the T group, with 75
   metabolites showing increased levels and 278 metabolites displaying
   decreased levels. The results revealed that the mechanisms of heat
   tolerance involve energy supply strategies, immune system regulation,
   amino acid metabolism, and glutathione metabolism. Energy supply
   strategies include the digestion and absorption of carbohydrates and
   proteins, glycolysis/gluconeogenesis, fructose and mannose metabolism,
   and pyruvate metabolism, all of which collectively meet energy demands
   in high-temperature environments. The immune system is regulated by
   C-type lectin receptor pathways and IL-17 signaling pathways, which
   together coordinate innate immunity to prevent pathogen invasion. In
   amino acid metabolism, various glycogenic amino acids, such as
   histidine, phenylalanine, valine, and serine, are metabolized for
   energy, while excess ammonia is converted to γ-glutamyl-glutamate and
   L-glutamate to mitigate ammonia accumulation. Combined transcriptomic
   and metabolomic analyses further indicate that glutathione metabolism
   plays a crucial role in the adaptation of P. monodon to
   high-temperature environments. This study explains the high-temperature
   tolerance mechanism of P. monodon from the aspects of gene expression
   regulation and material metabolism regulation and also provides a
   scientific basis and basic data for the selection and breeding of new
   varieties of P. monodon with a high-temperature tolerance.

1. Introduction

   Global climate warming is leading to rising sea temperatures,
   significantly threatening the survival and growth of marine animals,
   even resulting in the extinction of certain species, disrupting
   regional biodiversity and community structures, and affecting the
   distribution or structure of marine animal populations [[42]1,[43]2].

   Acute or long-term changes in environmental temperature will damage the
   physiological status of fish and inhibit their growth. As the
   environment changes, organisms also adapt passively. Studies have shown
   that different species and individuals respond variably to
   high-temperature conditions. High-temperature-sensitive and tolerant
   individuals were naturally occurring in cold-water fish like rainbow
   trout [[44]3]. Temperature acclimation (TA) can increase mitochondrial
   plasticity and improve the high-temperature tolerance of rainbow trout
   [[45]4]. Additionally, the ability to tolerate high temperatures was
   found to be inherited by offspring in zebrafish [[46]5]. Organisms
   adapt to high temperatures by altering the expression of relevant genes
   and metabolic levels, which influences aquatic animal behavior,
   physiology (such as heart rate), and biochemistry (including protein
   and lipid structure and expression) [[47]6,[48]7]. According to these
   studies, it is necessary to conduct genetic improvements in the later
   stages to enhance species’ heat adaptation based on research on heat
   adaptation.

   The high temperature of water impacts tissue structure, enzyme activity
   levels, transcriptional regulation, and metabolism. Cyclic
   high-temperature stress-induced damage to the gill tissues of
   Litopenaeus vannamei triggers an oxidative stress response. Various
   biomarkers of serum, including total antioxidant capacity (T-AOC),
   total superoxide dismutase (T-SOD), glutamate dehydrogenase (GDH),
   glutaminase (GLS), hexokinase (HK), and acid phosphatase (ACP), were
   significantly changed [[49]8,[50]9]. Furthermore, endoplasmic reticulum
   stress, cell apoptosis, and impaired osmoregulatory function were also
   observed [[51]10]. Research indicates that the metabolic demands of
   microorganisms such as bacteria and algae increase substantially in
   high-temperature environments, leading to the excessive consumption of
   oxygen in the water [[52]11]. Moreover, the accumulation of reactive
   oxygen species (ROS) and elevated levels of heat shock proteins (HSPs)
   trigger transcription factors such as heat shock transcription factor 1
   (HSF1), hypoxia-inducible factor 1α (HIF-1α), and tumor suppressor
   protein (p53), which affect energy supply, immune response, and
   metabolic processes in marine animals [[53]12,[54]13]. These processes
   deplete the innate and adaptive immune and antioxidant systems of fish
   and shrimp, increasing their susceptibility to pathogens [[55]14].

   With the rapid development of biological big data analysis methods, the
   joint analysis of multi-omics technologies, for example,
   transcriptomics and metabolomics, is increasingly applied in the study
   of the mechanisms of organisms. Transcriptomic analyses show that
   thermal stress suppresses protein synthesis in juvenile grass carp,
   reduces fatty acid synthesis, and weakens carbohydrate metabolism
   [[56]15]. Additionally, transcriptomic analyses reveal significant
   differences in energy allocation among the hepatopancreas, gills, and
   muscle of L. vannamei under thermal stress [[57]16]. miR-301b-5p and
   its target gene nfatc2ip were reported to regulate the inflammatory
   response in the liver of rainbow trout (Oncorhynchus mykiss) under
   high-temperature stress, facilitating the repair of microstructural
   liver damage induced by thermal stress [[58]3]. Transcriptomic analyses
   confirmed that immune pathways and metabolic pathways are essential
   mechanisms for Procambarus clarkii to cope with high and
   low-temperature stress [[59]17].

   Metabolomics provides insights into the response mechanisms of
   organisms to thermal stress by analyzing low molecular weight
   metabolites in cells, tissues, or biological fluids [[60]18]. Levels of
   adenosine, inosine, xanthine, guanosine, and deoxyguanosine, which are
   critical for DNA/RNA synthesis, are markedly reduced, while the
   abundance of D-glucose 6-P significantly increases [[61]19].
   High-temperature stress significantly disrupts the metabolism of
   glycerophospholipids and fatty acids, leading to membrane damage and
   lipid metabolic disorders in the liver cells of rainbow trout [[62]20].
   Integrated metabolomic and transcriptomic analyses revealed that
   enhanced amino acid and carbohydrate metabolism, along with inhibited
   fatty acid metabolism, constitute a potential energy conservation
   strategy for sturgeon Acipenser dabryanus during high-temperature
   stress [[63]21]. The same integrated analysis demonstrated that gene
   expression and metabolite levels of lipid homeostasis were varied,
   thereby alleviating lipid metabolic disorders induced by thermal stress
   in turbot (Scophthalmus maximus) [[64]22]. All of this research showed
   that multi-omics technologies has been powerful in analyzing molecular
   mechanisms.

   Penaeus monodon, commonly known as the black tiger shrimp, is one of
   the major cultivated shrimp species worldwide, with advantages in rapid
   growth, high-quality meat, strong disease resistance, and low
   production costs. It is widely farmed in tropical and subtropical
   regions such as China, Southeast Asia, and Africa, and has a broad
   temperature tolerance, ranging from 15 to 35 °C, with an optimal
   temperature of 25 to 30 °C [[65]23]. However, extremely high
   temperatures in summer still challenge the farming of P. monodon, which
   suffers greater losses during disease outbreaks, such as White Spot
   Syndrome (WSS), Early Mortality Syndrome (EMS), Acute Hepatopancreatic
   Necrosis Disease (AHPND), Enterocytozoon Hepatopenaei (EHP), and so on
   [[66]24,[67]25,[68]26,[69]27]. Moreover, extremely high temperatures
   deteriorate the water quality, causing eutrophication and imbalances in
   ammonia nitrogen, often leading to disruptions in the microbial
   communities of the farming ponds, which significantly impact
   physiological and biochemical parameters and growth performance, and
   increase mortality [[70]28]. Uncovering the molecular mechanisms upon
   high-temperature stress, and further promoting genetic improvements to
   cope with extreme summer environments, have become urgent tasks in
   black tiger shrimp aquaculture.

   Based on the preliminary experimental results, the number of shrimp
   surviving under 38 °C stress was sufficient to ensure an adequate
   sample size for subsequent tests. In this paper, we characterized
   temperature-sensitive and heat-tolerant individuals of the P. monodon
   under 38 °C high-temperature stress for 144 h. We compared the
   differences in gene expression and metabolism levels and then
   identified key genes and metabolic markers associated with
   high-temperature tolerance by integrated transcriptomic and metabolomic
   analyses. The results provide useful data for the strategies for
   dealing with high-temperature threats in the shrimp industry, as well
   as benefits the selective breeding of high-temperature-tolerant species
   of tiger shrimp.

2. Materials and Methods

2.1. Shrimp and Rearing Conditions

   Healthy juvenile P. monodon (average weight 4.97 ± 1.95 g) were sourced
   from the Shenzhen Experimental Base of the South China Sea Fisheries
   Research Institute in Shenzhen city, Guangdong Province in China. They
   were acclimated in a concrete pond for 7 days under continuous
   aeration, with a maintained temperature of 30 ± 2 °C and salinity at 30
   ppt, and fed commercial feed three times daily. This study was approved
   by the Animal Care and Use Committee of the South China Sea Fisheries
   Research Institute, Chinese Academy of Fishery Sciences (Approval No.
   nhdf2025-10). All sampling procedures and experimental protocols were
   conducted in strict accordance with the committee’s established
   guidelines and regulations.

2.2. High-Temperature Stress and Sample Collection

   Following the acclimatization period, a total of 700 juvenile P.
   monodon were introduced into experimental tanks (length 5.5 m, width
   2.85 m, water depth 1 m). Water temperature was gradient heated with a
   speed of 2 °C per day, starting from an initial temperature of 30 °C,
   until the target temperature of 38 °C was reached. During the
   experiment, the tanks were monitored every 20 min to remove moribund
   shrimp (exhibiting signs of lateral recumbency and minimal response to
   touch), which were recorded. The experiment lasted for 144 h. The
   shrimp that were moribund during the first 24 h were considered the
   heat-sensitive group (S group), and those that survived beyond 120 h
   were classified as the heat-tolerant group (T group).

   Currently, there is no established anesthesia method for Penaeus
   monodon. To avoid compromising the experimental results, live sampling
   was employed in this study. The hepatopancreas of each shrimp was
   dissected into two parts. One half was placed in RNAlater solution
   (Ambion, Austin, TX, USA) for transcriptomic analysis. The other half
   was rapidly frozen in liquid nitrogen for metabolomic analysis. In the
   transcriptomic analysis, twelve shrimp were included per group, with
   hepatopancreas tissues from every four individuals pooled to form one
   test sample. For the metabolomic analysis, 20 shrimp were included per
   group, and similarly, hepatopancreas tissues from every 4 individuals
   were combined to constitute a single test sample.

2.3. -Transcriptomic Analysis

2.3.1. RNA Extraction and Library Construction

   Total RNA was extracted from the hepatopancreas using TRIzol reagent
   according to the manufacturer’s instructions. RNA purity and
   quantification were assessed using a NanoDrop 2000 spectrophotometer
   (ThermoScientific, Wilmington, DE, USA), while RNA integrity was
   evaluated using an Agilent 2100 Bioanalyzer (Agilent Technologies,
   Santa Clara, CA, USA). The transcriptomic library was constructed using
   the VAHTS Universal V5 RNA-seq Library Prep Kit following the
   manufacturer’s protocol. Sequencing of the library was performed on the
   Illumina Novaseq 6000 platform, generating 150 bp paired-end reads.

2.3.2. Bioinformatics Analysis of the Transcriptome

   Raw reads in fastq format were processed using fastp 0.20.1 software to
   remove low-quality reads, resulting in clean reads. Subsequently, clean
   reads were aligned and annotated against the P. monodon genome using
   HISAT2 2.1.0 software, and gene expression levels were calculated as
   FPKM (fragments per kilobase of transcript per million mapped reads).
   Read counts for each gene were obtained using HTSeq-count. PCA analyses
   were performed using R (v 3.2.0) to evaluate the biological duplication
   of samples. Differential expression analysis was performed with DESeq2
   software, identifying differentially expressed genes (DEGs) based on
   the criteria of q-value < 0.05 and fold change > 2 or fold change <
   0.5. A hierarchical cluster analysis of DEGs was performed using R (v
   3.2.0) to demonstrate the expression pattern of genes in different
   groups and samples. GO and KEGG pathway enrichment analyses for DEGs
   were conducted using hypergeometric tests based on the Gene Ontology
   (GO) database and the Kyoto Encyclopedia of Genes and Genomes (KEGG)
   database. The transcriptional characteristics of immune- and oxidative
   stress-related DEGs were further analyzed.

2.3.3. qRT-PCR Verification

   Total RNA extracted from the hepatopancreas of each group was used as a
   template for cDNA synthesis by the Evo M-MLV Plus cDNA kit (AG,
   Changsha, China). We randomly selected 12 differentially expressed
   genes for validation through qRT-PCR to verify the transcriptomic
   sequencing results, using the EF-1α gene (GenBank [71]MG775229.1) as an
   internal reference. The qPCR was conducted using the LightCycler^® 480
   II (Roche, Mannheim, Germany), following the method by R. Fan et al.
   [[72]29]. Each sample and reference gene was analyzed in triplicate,
   and data were calculated using the 2^−ΔΔCt method.

2.4. Metabolomics Analysis

2.4.1. Metabolite Extraction and LC-MS Analysis

   A total of 30 mg of hepatopancreas was mixed with 400 μL of
   methanol–water (v:v = 4:1, containing mixed internal standards at 4
   μg/mL). After pre-cooling at −40 °C for 2 min, the mixture was
   homogenized for 2 min. Ultrasonic extraction was performed in an
   ice-water bath for 10 min, followed by centrifugation at 12,000 rpm for
   10 min at 4 °C. The supernatant (300 μL) was collected and evaporated
   to dryness in a sample vial for LC-MS analysis. Prior to the analysis,
   the residue was reconstituted with 300 μL methanol–water (v:v = 1:4),
   sonicated for 3 min in an ice-water bath, and then left to stand at −40
   °C for 2 h. The sample was centrifuged again at 12,000 rpm for 10 min
   at 4 °C.

   The LC-MS analysis was conducted using a Waters ACQUITY UPLC I-Class
   Plus coupled with a Thermo QE ultra-high-performance liquid
   chromatography–tandem mass spectrometry system. Liquid chromatographic
   separation was performed on an ACQUITY UPLC HSS T3 column (100 mm × 2.1
   mm, 1.8 μm) at a column temperature of 45 °C, using mobile phase A
   (water with 0.1% formic acid) and B (acetonitrile) at a flow rate of
   0.35 mL/min with an injection volume of 3 μL. Mass spectrometry
   utilized an ESI ion source with separate scanning for positive and
   negative ions, employing a data-dependent acquisition (DDA) mode.

2.4.2. Bioinformatics Analysis of the Metabolome

   The raw data were processed using the metabolomics software Progenesis
   QI v3.0 (Nonlinear Dynamics, Newcastle, UK) for baseline filtering,
   peak identification, integration, retention time correction, peak
   alignment, and normalization. Metabolites were identified and annotated
   using the Human Metabolome Database (HMDB), Lipidmaps (v2.3), the
   METLIN database, and the LuMet-Animal 3.0 local database. Orthogonal
   Partial Least Squares Discriminant Analysis (OPLS-DA) was applied to
   differentiate the overall metabolic profiles between groups.
   Differential metabolites were selected based on the combination of
   multivariate and univariate analyses (VIP > 1 and p-value < 0.05). The
   volcano plot was employed to visualize the p-values, VIP (Variable
   Importance in Projection) scores, and FC (fold change) values.
   Hierarchical clustering was subsequently performed to analyze the
   expression levels of selected significantly differential metabolites. A
   KEGG pathway enrichment analysis for the differential metabolites was
   conducted using hypergeometric testing based on the KEGG PATHWAY and
   KEGG ORTHOLOGY databases. The metabolite biomarkers were further
   identified.

2.5. Combined Analysis of Hepatopancreatic Transcriptome and Metabolome

   After filtering the data for differentially abundant metabolites (DAMs)
   and differentially expressed genes (DEGs), a correlation analysis was
   performed using the Spearman algorithm to construct a correlation
   heatmap for DEGs and differentially expressed metabolites (DEMs). A
   joint analysis was conducted on the KEGG enrichment results from both
   transcriptomics and metabolomics, focusing on pathways that were
   significantly enriched (p-value < 0.05) in each dataset. Commonly
   enriched KEGG pathways were extracted, and the results were visualized
   using a bubble plot.

3. Results

3.1. The Cumulative Survival Rate of P. Monodon

   Typical signs of stressed shrimp, such as reduction in food consumption
   and red coloration, were observed, and the dead shrimps were recorded
   throughout the whole experimental stage. High-temperature stress
   threatened the survival of shrimp, and the cumulative survival within
   24 h was 95.57%, and then sharply decreased to 5.29% in the later 144
   h, accompanied with a rise in the temperature. The peak mortality
   period occurred between 72 and 120 h ([73]Figure 1). Consequently,
   shrimp that succumbed within 24 h were classified as heat-sensitive (S
   group), whereas those that survived beyond 120 h were classified as
   heat-tolerant (T group).

Figure 1.

   [74]Figure 1
   [75]Open in a new tab

   Cumulative survival rate of P. monodon under high-temperature stress.

3.2. Hepatopancreas Transcriptomic Analysis

3.2.1. Identification and Functional Annotation of the DEGs

   The PCA analysis in this study revealed a distinct clustering trend
   between the T group and S group ([76]Figure 2a). Compared to the S
   group, a total of 3,527 DEGs were identified in the T group, including
   2199 upregulated and 1328 downregulated genes ([77]Figure 2b,c).

Figure 2.

   [78]Figure 2
   [79]Open in a new tab

   Differential genes in the hepatopancreas of P. monodon under
   high-temperature stress. (a) PCA diagram; (b) histogram of
   differentially expressed gene statistics; and (c) volcano map of
   transcriptome genes.

   The further analysis of the DEGs through GO and KEGG enrichment
   revealed that 448 GO terms were significantly enriched between the two
   groups, comprising 273 in biological processes, 67 in cellular
   components, and 108 in molecular functions. The functional enrichment
   of the DEGs included categories such as oxidoreductase activity, the
   negative regulation of MAP kinase activity, integrins, and
   mitochondrial functions ([80]Figure 3a). The KEGG enrichment analysis
   indicated that there were 60 significantly differentially enriched KEGG
   pathways between the T and S groups, including pathways related to
   glutathione metabolism, lysosome, carbohydrate digestion and
   absorption, protein digestion and absorption,
   glycolysis/gluconeogenesis, fructose and mannose metabolism, pyruvate
   metabolism, glycine, serine, and threonine metabolism, the C-type
   lectin receptor signaling pathway, and the IL-17 signaling pathway
   ([81]Figure 3b).

Figure 3.

   [82]Figure 3
   [83]Open in a new tab

   The pathway enrichment in the hepatopancreas of P. monodon under
   high-temperature stress. (a) GO enrichment terms; (b) KEGG enrichment
   terms.

   In the glutathione metabolism pathway, the expression of genes such as
   GLCL and Ggct was upregulated, while genes like GST1, ICDH, and Rrm1
   were downregulated. Within the lysosome pathway, genes including MLA1
   and CTSC were upregulated, whereas NPC1, CTSD, and GLB1 showed
   downregulation. In the glycolysis/gluconeogenesis pathway, genes such
   as CG10160 and TEgg056i02.1 were upregulated, while G6pt, ALDH3, and
   Aldhx were downregulated. For the glycine, serine, and threonine
   metabolism pathway, Tdh and LPIPOX exhibited upregulation, while bhmt,
   DAO, and AGT1 were downregulated. In the C-type lectin receptor
   signaling pathway, COX2, CG12559, and FYN were upregulated, while
   DDB_G0277917 and MLT were downregulated. Lastly, in the IL-17 signaling
   pathway, CG11992 (Relish), mapk15, Traf6, and CG5680 (JNK) showed
   upregulation, whereas the expression of the T05E11.3 (Hsp90b1) gene was
   downregulated ([84]Table 1).

Table 1.

   List of the genes with a few significant changed KEGG pathways.
   Pathway/Gene Symbol Gene All Name log2FoldChange p-Value Up/Down
   Glutathione metabolism
   GLCL glutamate-cysteine ligase catalytic subunit-like 1.264 0.00276 UP
   Ggct gamma-glutamylcyclotransferase-like 2.413 0.00943 UP
   GST1 glutathione S-transferase 1-like −5.980 1.63 × 10^−8 DOWN
   ICDH Isocitrate dehydrogenase (NADP) −1.652 0.00183 DOWN
   Rrm1 ribonucleoside-diphosphate reductase large subunit-like −7.808
   3.03 × 10^−16 DOWN
   Lysosome
   MLA1 CD63 antigen-like 4.658 1.98 × 10^−11 UP
   CTSC cathepsin C 4.561 3.72 × 10^−5 UP
   NPC1 NPC intracellular cholesterol transporter 1-like −4.530 0.00011
   DOWN
   CTSD lysosomal aspartic protease-like −4.764 6.26 × 10^−10 DOWN
   GLB1 beta-galactosidase-like −4.198 1.22 × 10^−13 DOWN
   Glycolysis/Gluconeogenesis
   CG10160 L-lactate dehydrogenase-like isoform X1 3.236 9.52 × 10^−6 UP
   TEgg056i02.1 aldoketoreductase-like protein 5.122 0.00208 UP
   G6pt glucose-6-phosphatase-like −6.920 1.24 × 10^−15 DOWN
   ALDH3 aldehyde dehydrogenase, dimeric NADP-preferring-like −1.712
   0.00442 DOWN
   Aldhx aldehyde dehydrogenase X, mitochondrial-like isoform X2 −4.764
   3.61 × 10^−10 DOWN
   Glycine, serine, and threonine metabolism
   Tdh L-threonine 3-dehydrogenase, mitochondrial-like 5.340 0.00113 UP
   LPIPOX peroxisomal sarcosine oxidase-like 2.781 0.00026 UP
   bhmt betaine--homocysteine S-methyltransferase 1-like −6.325 2.47 ×
   10^−10 DOWN
   DAO D-amino-acid oxidase-like −2.561 3.36 × 10^−8 DOWN
   AGT1 serine--pyruvate aminotransferase-like isoform X1 −2.175 7.15 ×
   10^−6 DOWN
   C-type lectin receptor signaling pathway
   COX2 cyclooxygenase 5.416 3.55 × 10^−8 UP
   CG12559 ERK 4.871 0.01191 UP
   FYN tyrosine-protein kinase SRK3-like 5.898 0.00017 UP
   DDB_G0277917 putative calmodulin-like −1.112 0.00971 DOWN
   MLT putative mucosa-associated lymphoid tissue lymphoma translocation
   protein 1-like −1.346 0.01094 DOWN
   IL-17 signaling pathway
   CG11992 NF-κB transcription factor Relish 1.748 0.00083 UP
   mapk15 putative mitogen-activated protein kinase 15-like 6.033 0.00114
   UP
   Traf6 tumor necrosis factor receptor-associated factor 6 2.107 0.00236
   UP
   CG5680 c-jun N-terminal kinase (JNK) 2.065 0.00745 UP
   T05E11.3 Endoplasmin (Hsp90b1) −1.408 0.00224 DOWN
   [85]Open in a new tab

3.2.2. Analysis of Specific Genes for Immunity and Oxidative Stress

   In addition, some genes related to immunity and oxidative stress were
   further analyzed. Immune-related genes, including
   anti-lipopolysaccharide factor isoform 6 (ALF), serine proteinase
   inhibitor 6 (Serpinb1a), beta-integrin (ZK1058.2), and sushi, von
   Willebrand factor type A, EGF, and pentraxin domain-containing protein
   1-like (Svep1), were found to be upregulated, while i-type
   lysozyme-like protein 1 (lysoz), Kazal-type serine proteinase inhibitor
   1 (Agrin), gamma-interferon-inducible lysosomal thiol reductase
   (ifi30), and chitotriosidase-1-like (Chia) were downregulated.

   For oxidative stress and antioxidant-related genes, lactoylglutathione
   lyase (Glo1), prophenoloxidase-activating enzyme 2a (PPAF1), and
   cyclooxygenase (COX2) were upregulated, whereas short-chain
   dehydrogenase/reductase family 16C member 6-like (Sdr16c6) and
   glutathione S-transferase (Gstm1) were downregulated ([86]Figure 4a).
   The qRT-PCR validation of the transcriptomic sequencing results
   indicated that the expression patterns of the genes tested by qRT-PCR
   were consistent with those obtained from RNA-Seq, confirming the
   reliability and accuracy of the RNASeq analysis ([87]Figure 4b).

Figure 4.

   [88]Figure 4
   [89]Open in a new tab

   The transcription characteristics of gene markers and differential gene
   validation of P. monodon under high-temperature stress. (a) Heatmap of
   differential genes; (b) qRT-PCR differential gene validation.

3.3. Hepatopancreas Metabolomics Analysis

3.3.1. Identification and Functional Analysis of Differential Metabolites

   The OPLS-DA analysis demonstrated significant differences between the T
   group and S group, indicating substantial alterations in the
   metabolites of heat-tolerant P. monodon under high-temperature stress
   ([90]Figure 5a). Compared to the S group, a total of 353 differentially
   abundant metabolites were identified in the T group, with 75
   metabolites showing increased expression and 278 metabolites showing
   decreased expression ([91]Figure 5b,c).

Figure 5.

   [92]Figure 5
   [93]Open in a new tab

   Metabolic pattern variation in the hepatopancreas of P. monodon under
   high-temperature stress. (a) OPLS–DA scatter diagram; (b) histogram of
   differential metabolites; and (c) volcanic map of differential
   metabolites.

   The further enrichment analysis of these DAMs revealed that the primary
   pathways enriched between the T and S groups included amino acid
   metabolism (arginine, proline, glycine, serine, threonine, alanine,
   aspartate, and glutamate), pyrimidine and purine metabolism,
   glycerophospholipid metabolism, ABC transporters, autophagy,
   glutathione metabolism, and the FoxO signaling pathway ([94]Figure 6a).

Figure 6.

   [95]Figure 6
   [96]Open in a new tab

   The pathway enrichment and the identification of metabolite markers in
   the hepatopancreas of P. monodon under high-temperature stress. (a)
   KEGG enrichment terms; (b) heatmap of differential metabolites.

3.3.2. Recognition of Metabolite Markers

   Additionally, some stress-related marker metabolites were further
   analyzed, including downregulated metabolites associated with amino
   acid metabolism, such as L-theanine, N-ribosylhistidine, and
   L-tryptophan, and upregulated metabolites such as L-glutamic acid and
   5-amino-pentanoic acid. In glycerophospholipid metabolism, PE (22:6
   (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)/6 keto-PGF1alpha) and PGP (16:0/18:1
   (12Z)-2OH (9, 10)) were found to be upregulated. Nucleotide metabolism
   revealed the upregulation of Fad, guanine, deoxyinosine, thymine, and
   deoxyguanosine, while uridine 5′-monophosphate and 5-thymidylic acid
   were downregulated. For immune-related metabolites, pentigetide,
   trideca-3,6,9-trienoylcarnitine, and dodeca-3,6,9-trienoylcarnitine
   were downregulated, whereas 4,5-dihydroorotic acid, nicotinic acid, and
   4,5-dihydroorotic acid were upregulated ([97]Figure 6b).

3.4. Combined Transcriptome and Metabolome Analysis

   The further joint analysis revealed that the pathways commonly enriched
   in both transcriptomics and metabolomics included glutathione
   metabolism, glycine, serine, and threonine metabolism, arginine and
   proline metabolism, biosynthesis of phenylalanine, tyrosine, and
   tryptophan, as well as histidine metabolism ([98]Figure 7a). In the T
   group, genes such as gamma-glutamyl cyclo transferase-like (GGCT),
   glucose-6-phosphate 1-dehydrogenase (G6PD), and gamma-glutamyl
   transpeptidase (GGT) in the glutathione metabolism pathway were
   upregulated, while glutathione reductase (GSR), glutathione
   dehydrogenase/transferase (DHAR), leucyl aminopeptidase (PepA), and
   trypanothione-disulfide reductase (TryR) were downregulated.
   Additionally, levels of L-glutamic acid increased, while
   L-gamma-glutamyl-L-amino acid levels decreased ([99]Figure 7c). The
   correlation analysis between metabolites and genes demonstrated strong
   associations between Chia, PPAF1, ZK1058.2, and Svep1, and metabolites
   such as Thapsigargin, Tricetin 7, 3′-Diglucuronide,
   Gamma-Glutamylalanine, and 4-Formyl Indole. PPAF1 was also strongly
   correlated with guanine, deoxyguanosine, 4,5-dihydroorotic acid,
   leonoside A, petunidin 3-galactoside, and thymine. Furthermore, Agrin,
   Gstm1, Lysoz, ALF, Glo1, COX2, and Serpinb1a exhibited strong
   correlations with Beta-D-Glucosaminyl-(1→4)-Beta-D-Glucosamine
   ([100]Figure 7b).

Figure 7.

   [101]Figure 7
   [102]Open in a new tab

   Transcriptome and metabolome correlation analysis. (a) KEGG pathway
   bubble diagram; (b) heatmap of differential gene–metabolite
   correlation, * indicates p < 0.05, ** indicates p < 0.01, and ***
   indicates p < 0.001; (c) The DAMs and related DEGs involved in
   glutathione metabolism.

4. Discussion

   Temperature is a key environmental factor for organisms that need the
   physiological and biochemical processes to be carried out at a certain
   temperature. Although shrimp belong to ectothermic animals, studies
   have shown that the immune and physiological activities of shrimp are
   significantly affected when the water temperature suddenly changes
   within 6~9 °C, which can even kill them. Uncovering the effector for
   the change in temperature and the adaptability of extreme temperature
   of shrimp will provide useful data for the healthy aquaculture of
   shrimp, as well as the breeding of new strains that resist high
   temperatures [[103]23,[104]30]. This study confirms that extreme high
   temperatures have lethal effects on P. monodon. This was accomplished
   by dividing the sensitive and tolerant groups and then obtaining the
   regulatory mechanisms of shrimp adapting to high temperatures by a
   joint analysis of the transcriptional regulation and metabolic levels.

   In this study, the transcriptomic analysis revealed significant
   enrichment in glycolysis/glycogen synthesis, fructose and mannose
   metabolism, the IL-17 signaling pathway, the C-type lectin receptor
   signaling pathway, amino acid metabolism, and glutathione metabolism
   under high-temperature stress conditions. Therefore, it is hypothesized
   that the regulation of resistance and defense genes, along with the
   expression of oxidative and antioxidative genes, represents a
   comprehensive strategy for high-temperature stress resistance in P.
   monodon. The further untargeted metabolomics analysis indicated that
   the differentially expressed metabolites in the heat-resistant group
   included amino acids, peptides and their analogs, carbohydrates and
   their conjugates, fatty acids and conjugates, and amino acid-derived
   groups and their derivatives (such as aminoquinolines and related
   compounds). Based on the integrative analysis of transcriptomics and
   metabolomics, it is suggested that P. monodon primarily adapts to
   high-temperature stress by regulating immune responses, energy
   metabolism, various amino acid metabolic pathways, and glutathione
   metabolism. This study will discuss these four aspects in detail.

4.1. Energy Metabolism Regulation Is Necessary for the Black Tiger Shrimp to
Adapt to High-Temperature Stress

   Rising temperatures increase the energy demand of cellular tissues,
   particularly in ectothermic animals, where elevated environmental
   temperatures stimulate metabolic levels to rise exponentially, leading
   to a sharp increase in energy requirements. Increasing evidence
   suggests that the selective storage of energy substrates and the
   adjustment of energy supply mechanisms are critical strategies for
   organisms to cope with acute high-temperature stress
   [[105]31,[106]32,[107]33]. Our research identified several energy
   supply-related pathways significantly enriched in heat-tolerant shrimp,
   including carbohydrate digestion and absorption, protein digestion and
   absorption, glycolysis/gluconeogenesis, fructose and mannose
   metabolism, and pyruvate metabolism. Carbohydrates serve as the primary
   energy source essential for the growth and development of animals
   [[108]34]. They are digested in the intestine into monosaccharides,
   primarily glucose, galactose, and fructose, which are then absorbed
   into the bloodstream through the small intestine. In this study, we
   observed that the MGA gene (maltase-glucoamylase) was upregulated in
   the carbohydrate digestion and absorption pathway of heat-tolerant
   shrimp, while the SI (sucrase-isomaltase) and G6pt
   (glucose-6-phosphatase) genes were downregulated, indicating the
   crucial role of these enzymes in energy supply for coping with
   high-temperature stress [[109]35].

   In addition to carbohydrates, dietary proteins are absorbed as amino
   acids, serving as an energy reserve. Under high-temperature stress,
   energy demands rise sharply, and these amino acids can quickly provide
   energy [[110]36]. In terms of energy supply,
   glycolysis/gluconeogenesis, fructose and mannose metabolism, and
   pyruvate metabolism are key pathways for energy metabolism and direct
   energy acquisition. We found that in the glycolysis/gluconeogenesis
   pathway of heat-tolerant shrimp, CG7070 (pyruvate kinase-like isoform
   X2), CG6058 (fructose-bisphosphate aldolase-like isoform X1), and
   CG10160 (L-lactate dehydrogenase-like isoform X1) were upregulated,
   while Aldh2 (aldehyde dehydrogenase, mitochondrial-like), Aldh9a1
   (4-trimethylaminobutyraldehyde dehydrogenase-like), and CG17725
   (phosphoenolpyruvate carboxykinase) were downregulated. The activation
   of pyruvate kinase and L-lactate dehydrogenase reflects increased
   glycolytic/glycolytic activity, which facilitates the breakdown of
   glycogen in the liver into glucose and its transport to osmoregulatory
   tissues such as the gills and kidneys to provide energy for
   thermoregulation [[111]37,[112]38]. In fructose and mannose metabolism,
   QccE-15018 (mannose-6-phosphate isomerase-like), CG32849 (hexokinase
   type 2 isoform X1), and PFKFB2
   (fructose-2,6-bisphosphate/fructose-2,6-bisphosphate kinase-like
   isoform X1) were upregulated, while Sdh1 (sorbitol dehydrogenase-like),
   Fuk (putative L-fucose kinase-like), and SORD (sorbitol
   dehydrogenase-like) were downregulated. In summary, our findings
   indicate that P. monodon adjusts its entire energy supply chain to
   adapt to high-temperature environments, from the digestion and
   absorption of energy substrates to the activation of multiple metabolic
   pathways, ultimately meeting energy demands in elevated temperature
   conditions.

4.2. The Regulation of Innate Immune System Is Necessary for the Black Tiger
Shrimp to Adapt to High-Temperature Stress

   In this study, the C-type lectin receptor and IL-17 signaling pathway
   were significantly enriched in high-temperature stress conditions.
   C-type lectin receptors (CLRs) serve as pattern recognition receptors
   (PRRs) for pathogen-derived ligands in dendritic cells, macrophages,
   and neutrophils. Upon ligand binding, CLRs initiate intracellular
   signaling cascades that induce the production of inflammatory cytokines
   and chemokines, thereby triggering both innate and adaptive immune
   responses against pathogens [[113]39,[114]40,[115]41]. The C-lectin of
   P. monodon has been confirmed to combine with bacterial polysaccharides
   and agglutinate multiple marine pathogenic bacteria, such as Vibrio
   harveyi, V. anguillarum, V. alginolyticus, and so on, to defend against
   bacterial infection [[116]24]. The high expression of the C-lectin
   pathway in heat-tolerant shrimp could protect it from bacterial
   disease. IL-17 is a proinflammatory cytokine produced by activated
   T-cells and certain cell types of the innate immune system and induces
   the production of proinflammatory proteins, including cytokines,
   chemokines, and matrix metalloproteases, to amplify inflammation
   [[117]42,[118]43]. The IL family is widely present in vertebrates.
   There are few studies in invertebrate shrimp. The first IL-like gene
   reported in L. vannamei affects antiviral and antibacterial immune
   responses. The lectin MjCC-CL of kuruma shrimp (M. japonicus) contains
   an IL-like domain, which can recognize bacterial surface molecules and
   induce antimicrobial peptides to inhibit bacterial infection [[119]44].

   The KEGG pathway analysis focusing on two specific pathways suggests a
   strong association between them. Based on previous studies, in this
   research, C-lectin may function similarly to IL-17, activating the
   expression of related factors through an IL-17 pathway analogous to
   that in mammals. The transcriptomic analysis revealed a significant
   enrichment of IL-17, with significant upregulation of Relish, MAPK15,
   Traf6, and JNK, indicating that high-temperature stress in the
   hepatopancreas induces IL-17A/C-lectin signaling through receptor
   binding. Concurrently, Hsp90 maintains the integrity of Act1 at the
   protein level, and Act1, through interaction with TRAF6, activates
   NF-κB/Relish and MAPK/JNK signaling pathways. These pathways then
   transcriptionally regulate cytokines, such as Cox2, or antimicrobial
   peptides, thereby resisting the invasion of exogenous microorganisms.
   This result suggests that the body increases susceptibility to
   bacterial infections such as Vibrio under heat stress and then
   activates the innate immune system to produce antimicrobial peptides,
   which protect the shrimp and adapt to high-temperature changes. This
   finding is consistent with previous research results [[120]40,[121]45].

4.3. Amino Acid Metabolism Is Necessary for the Black Tiger Shrimp to Adapt
to High-Temperature Stress

   As previously discussed, under high-temperature stress, protein
   degradation into amino acids can serve as an energy source,
   particularly glycogenic amino acids such as histidine, threonine,
   glutamine, phenylalanine, arginine, serine, tyrosine, methionine, and
   isoleucine, which can function as direct energy sources or precursors
   for gluconeogenesis or ketogenesis [[122]46]. In this study, we
   observed a significant reduction in the levels of various amino acids,
   including histidine, phenylalanine, valine, and serine, in P. monodon
   under thermal stress. However, the accumulation of ammonia in the body
   increases due to transamination or deamination processes that promote
   gluconeogenesis, posing a serious threat to fish health [[123]47]. To
   counteract ammonia accumulation, the organism must undergo adaptive
   metabolic adjustments. Notably, we also found a significant increase in
   γ-glutamyl glutamate and L-glutamate, suggesting the organism’s efforts
   to mitigate ammonia buildup. Furthermore, Yang Liu et al. have
   confirmed that the sustained increase in glutamate and glutamine levels
   under high-temperature stress may be a critical pathway for reducing
   ammonia accumulation and alleviating its toxicity in Brachymystax lenok
   during thermal stress [[124]48].

4.4. Antioxidant Response and Detoxification Is Necessary for the Black Tiger
Shrimp to Adapt to High-Temperature Stress

   GSH is a soluble thiol antioxidant abundantly present in cells, playing
   a critical role in maintaining redox homeostasis and protecting cells
   and tissues from oxidative stress and various forms of stress. It is
   closely involved in the regulation of redox signaling pathways and
   detoxification responses [[125]49,[126]50]. The redox balance in
   organisms is maintained by components such as peroxidases and mGSH,
   with GSSG being the oxidized form of GSH. In the process catalyzed by
   glutathione peroxidase (GSH-PX), GSH is oxidized to GSSG while reducing
   H[2]O[2] to H[2]O; subsequently, glutathione reductase uses NADPH to
   regenerate GSH from GSSG [[127]51]. A research report indicates that
   glutathione metabolism plays a crucial role in the response of aquatic
   animals to environmental stress. For example, an enhanced hepatic
   glutathione metabolic response was found in fish under heavy metal
   exposure [[128]52]. During high-temperature stress, the activities of
   GST, GSH, and various antioxidant enzymes undergo significant changes,
   and supplementation with GSH effectively mitigates the impact of
   high-temperature stress on fish metabolic mechanisms
   [[129]53,[130]54,[131]55].

   This study further reveals significant changes in the expression of
   glutathione metabolism-related genes in heat-tolerant shrimp, including
   GSR, TryR, DHAR, GGCT, G6PD, and GGT. The downregulation of genes such
   as GSR and DHAR limits the interconversion between GSH and GSSG, while
   the upregulation of GGCT and GGT promotes the conversion of GSH to
   L-glutamate and L-amino acids. These findings suggest that glutathione
   in heat-tolerant shrimp operates in a low-sensitivity mode, further
   supporting the idea that the activity of the glutathione metabolic
   pathway can serve as an indicator of the heat tolerance level in P.
   monodon. Additionally, the levels of metabolic products such as
   L-glutamate and L-γ-glutamyl-L-amino acids are also regulated, which
   may be critical for the thermal adaptation of P. monodon.

5. Conclusions

   In this study, through a comprehensive analysis of transcriptomics and
   metabolomics, we have gained a detailed understanding of the gene
   expression regulation and metabolic changes associated with thermal
   tolerance in P. monodon. The mechanisms underlying the high-temperature
   adaptability of this species are complex and involve multiple
   processes, including energy supply strategies, immune system
   modulation, amino acid metabolism, and glutathione metabolism
   ([132]Figure 8). Within the energy supply strategies, pathways related
   to carbohydrate digestion and absorption, protein digestion and
   absorption, glycolysis/gluconeogenesis, fructose and mannose
   metabolism, and pyruvate metabolism collectively regulate energy
   demands under high-temperature conditions. The immune system’s
   regulation involves the C-type lectin receptor pathway and the IL-17
   signaling pathway, which work together to enhance both innate and
   adaptive immunity, thereby preventing pathogen invasion. Additionally,
   various glycogenic amino acids such as histidine, phenylalanine,
   valine, and serine are metabolized to supply energy, while excess
   ammonia is converted into γ-glutamyl-glutamate and L-glutamate to
   mitigate ammonia accumulation. Furthermore, our combined transcriptomic
   and metabolomic analyses reveals that glutathione metabolism plays a
   significant role in the adaptation of P. monodon to high-temperature
   thermal stress environments. In summary, this study elucidates the
   high-temperature tolerance mechanisms in P. monodon through
   investigations of gene expression regulation and metabolic modulation.
   We have identified key pathways, genes, and metabolites closely
   associated with thermotolerance traits. While most of these pathways
   have been reported in thermal stress responses of other aquatic
   species, the specific expression patterns of genes and metabolites
   within these pathways exhibit distinct characteristics in P. monodon.
   Collectively, our findings provide both scientific rationale and
   fundamental data for breeding novel heat-tolerant P. monodon varieties.
   Concurrently, it should be noted that the adaptive mechanisms currently
   identified necessitate additional experimental verification through
   well-designed studies. Meanwhile, we are systematically conducting
   targeted experiments to identify and optimize a set of mechanisms
   particularly adapted for high-temperature breeding applications.

Figure 8.

   [133]Figure 8
   [134]Open in a new tab

   Response pattern of P. monodon to high temperature stress.

Author Contributions

   L.L.: writing—review and editing, writing—original draft,
   visualization, validation, methodology, formal analysis, data curation,
   and conceptualization. P.Z.: validation, methodology, data curation,
   and conceptualization. L.Y.: writing—review and editing,
   writing—original draft, and formal analysis. Y.L.: formal analysis and
   conceptualization. Z.H.: formal analysis and conceptualization. Q.Y.:
   formal analysis and conceptualization. Y.Y.: formal analysis and
   conceptualization. J.S.: formal analysis and conceptualization. Y.C.:
   formal analysis and conceptualization. J.H.: writing—review and
   editing, writing—original draft, visualization, validation,
   methodology, formal analysis, data curation, and conceptualization. All
   authors have read and agreed to the published version of the
   manuscript.

Institutional Review Board Statement

   This study was approved by the Animal Care and Use Committee of the
   South China Sea Fisheries Research Institute, Chinese Academy of
   Fishery.

Data Availability Statement

   The authors will provide the raw data supporting the conclusions of
   this paper without reservation.

Conflicts of Interest

   No potential conflict of interests were reported by the authors.

Funding Statement

   This research was funded by the Rural Revitalization Strategy Special
   Fund Seed Industry Revitalization Project of Guangdong Province
   (2022SPY02001, 2024SPY02001), the National Key R & D Program of China
   (2022YFD2400104), Central Public-interest Scientific Institution Basal
   Research Fund, CAFS (No. 2023TD34), China Agriculture Research
   System-48 (CARS-48), and Guangdong Provincial Special Fund for Modern
   Agriculture Industry Technology Innovation Teams (No. 2019KJ149),
   Guangdong Basic and Applied Basic Research Foundation
   (2023A1515012410), Hainan Provincial Natural Science Foundation of
   China (320QN359; 323MS127; 324MS130).

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References