Abstract

   Acute salinity stress critically impacts aquaculture efficiency by
   inducing physiological disruptions in fish. This study investigated the
   molecular adaptation mechanisms of Pseudobagrus ussuriensis exposed to
   10 ppt NaCl for 96 h, integrating transcriptomic and metabolomic
   analyses of gill and kidney tissues. In transcriptomics, 2,554 and
   1,066 differentially expressed genes (DEGs) were identified in gills
   and kidneys, respectively, with significant enrichment in pathways
   related to energy metabolism (glycolysis, oxidative phosphorylation),
   membrane dynamics (glycerophospholipid metabolism), and
   immune-osmoregulatory crosstalk (HIF-1, TNF, and Jak-STAT signaling).
   Metabolomics revealed 85 and 433 differential metabolites (DMs) in
   gills and kidneys, highlighting tyrosine metabolism, amino acid
   biosynthesis/degradation, and lipid remodeling (e.g.,
   glycerophospholipids, sphingolipids). Multi-organ coordination was
   observed: gills prioritized short-term osmotic adaptation via membrane
   lipid reorganization but suffered oxidative damage due to sustained
   downregulation of ALDH7 A1 and AOX/HADHA, triggering a “membrane
   injury–oxidative stress-ATP depletion” cycle. Conversely,
   kidneys-maintained energy homeostasis through purine/pyrimidine-TCA
   cycle reprogramming and autophagy-apoptosis balance. Critically,
   interorgan metabolic crosstalk-mediated by lipid mediators
   (prostaglandins, sphingolipids) and amino acid derivatives
   (branched-chain keto acids, glutamine)—orchestrated substrate shuttling
   (e.g., lactate for energy exchange) and systemic signaling, bridging
   local stress responses (gill ion regulation) with global metabolic
   adjustments (renal energy buffering). Notably, the levels of
   phosphatidylcholine (PC) and phosphatidylethanolamine (PE) in the
   kidney and phosphatidic acid (PA) and PC in the gills were
   significantly increased, while sphingomyelin (SM) decreased. Our
   findings demonstrate that acute salinity stress induces organ-specific
   metabolic reprogramming and interorgan crosstalk in P. ussuriensis,
   revealing a trade-off between osmotic adaptation and oxidative stress
   resilience mediated by lipid remodeling and energy metabolism
   dysregulation.

Supplementary Information

   The online version contains supplementary material available at
   10.1186/s12864-025-11773-w.

   Keywords: Pseudobagras ussuriensis, Salinity stress, Transcriptomics,
   Metabolomics, Oxidative enzyme activity

Introduction

   Salinity is closely related to the growth, development, and regulation
   of various physiological functions in fish. Changes in salinity force
   the fish to adapt to a series of physiological changes. Salinity is a
   key factor in artificial aquaculture conditions [[42]1]. Fluctuations
   in salinity affect aquaculture on multiple levels, including biological
   immune responses, physiological adaptation mechanisms, and ecosystem
   stability.

   Salinity stress disrupts immunological defenses and homeostatic
   regulation in commercially important aquatic species. For instance,
   Experimental evidence demonstrates that hypotonic stress (0–10‰
   salinity) significantly impairs the immune competence of Epinephelus
   coioides, manifesting as suppressed cytokine expression (IL-1β, IL-6,
   IL-10, TNF-α), attenuated immune cell proliferation, and diminished
   inflammatory responses [[43]2]. Similarly, acute salinity reduction
   below 10‰ critically compromises bivalve physiology, as evidenced in
   Mytilus galloprovincialis by complete cessation of byssal thread
   production, structural degeneration of pedal secretory glands, and
   ultimately fatal loss of adhesive capacity [[44]3]. Salinity effects on
   the survival and metabolism of aquatic animals. For example, Under
   salinity stress, the survival rate and digestive enzyme activities
   (e.g., amylase and lipase) of Perna viridis were regulated [[45]4]. The
   gill tissue of Crassostrea hongkongensis counteracts oxidative damage
   by modulating antioxidant enzyme activities and protein carbonylation
   levels [[46]5]. The gill tissue of Penaeus vannamei exhibits adaptive
   structural and functional adjustments, including thickening of
   epithelial cells and enrichment of mitochondria to support active ion
   transport [[47]6].

   At the ecosystem level, salinity fluctuations may undermine the
   stability of aquaculture systems by affecting biodiversity. Studies
   have found that the diversity of estuarine fish communities can buffer
   the impacts of salinity changes via a “portfolio effect” (akin to risk
   diversification in investment portfolios), where asynchronous responses
   among different fish species help maintain overall productivity [[48]1,
   [49]7, [50]8]. Additionally, nitrifying bacterial communities that have
   been pre-adapted to salinity stress (e.g., through pre-exposure to
   seawater) exhibit enhanced tolerance to subsequent salinity
   fluctuations, providing potential strategies for optimizing aquaculture
   wastewater treatment systems [[51]9].

   The regulation of salinity within fish primarily occurs in the gills
   and kidneys, where ion absorption is enhanced in the gills and diluted
   urine is produced in the kidneys to compensate for ion loss [[52]10,
   [53]11]. Salinity stress can cause structural changes in fish tissues,
   such as alterations in gill structure and necrosis in the liver and
   kidney tissues. The Qinghai Lake naked carp (Gymnocypris przewalskii),
   which inhabits the high-altitude saline-alkaline, hypoxic, and
   oligotrophic waters of Qinghai Lake, exhibits significant adaptive
   modifications in its gill arches and filaments: the number of gill
   rakers increases with a denser arrangement and elongation, while the
   gill filaments display a highly vascularized structure [[54]12]. The
   glomerular structure collapses, collecting tubules shrink, and the
   filtration rate of the nephron decreases significantly, leading to an
   obvious suppression of kidney function. Magnesium and calcium
   concentrations in the intestines are higher than those in the plasma,
   but no significant changes have been observed in the tissue structure
   [[55]13]. Studies on Oreochromis niloticus, under salinity stress, show
   an increase in mitochondria-rich cells in the gill tissue,
   vacuolization, degenerative changes, necrosis in the liver, and
   significant interstitial nephritis in the kidneys [[56]14].

   Salinity stress also alters the oxidative stress levels in fish cells.
   For example, salinity significantly affects the activities of
   superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase
   (GPX), and malondialdehyde (MDA). In Rachycentron canadum juveniles,
   the specific activities of SOD, CAT, and GPX increased with decreasing
   salinity [[57]15]. Both acute and chronic salinity stress lead to a
   gradual increase in the activities of SOD and CAT in the blood of
   Sebastes schlegeli as seawater salinity decreased [[58]16]. In Poecilia
   reticulata, antioxidant enzyme activity increases significantly under
   acute salinity stress at different salinity levels [[59]17].

   Salinity stress also causes changes in fish energy metabolism, immune
   responses, signaling molecules, and related metabolic pathways.
   Transcriptomic analysis of Lateolabrax maculatus under salinity stress
   has revealed that salinity-regulated genes are related to ion transport
   proteins, energy metabolism, signal transduction, immune responses, and
   structural remodeling [[60]18]. In Cynoglossus semilaevis (half-smooth
   tongue sole), liver transcriptomic studies have shown that lipid
   metabolism is crucial for salinity adaptation [[61]19]. Transcriptomic
   analysis of Rachycentron canadum under different salinity conditions
   showed that the major enriched pathways included steroid biosynthesis,
   unsaturated fatty acid metabolism, glutathione metabolism, energy
   metabolism, osmoregulation, and immune responses, with salinity having
   the greatest effect on metabolism [[62]20]. Studies on Carassius
   auratus (goldfish) using transcriptomic and metabolomic analyses of
   gill tissues have found that saline-alkali stress disrupts the
   antioxidant system in the gills, disturbs lipid metabolism, and induces
   cell apoptosis and immune responses [[63]21].

   Pseudobagrus ussuriensis, also known as the Ussuri catfish, is highly
   valued for its tender flesh and high economic value [[64]22]. It is
   widely cultured in more than ten provinces in China. Research on P.
   ussuriensis breeding has mainly focused on artificial propagation,
   aquaculture mode improvements, sex determination [[65]23], genetic
   analysis [[66]24], and stress resistance breeding [[67]25]. However,
   Research on salinity-tolerant breeding holds significant scientific and
   practical value in aquaculture, ecological conservation, and addressing
   climate change. research on P. ussuriensis salt-tolerant breeding is
   limited. In this study, we investigated the physiological and
   biochemical changes in the gill and kidney tissues of P. ussuriensis
   under acute salinity stress for 0, 6, 12, 24, 48, 72, and 96 h. We
   performed multi-omics analyses, including transcriptomics and
   non-targeted metabolomics, on the gill and kidney tissues after 24 h of
   salinity stress, to understand the molecular-level impacts of acute
   salinity stress on these tissues. This study provides valuable data for
   understanding the molecular regulatory mechanisms in the gill and
   kidney tissues of P. ussuriensis under salinity and offers insights for
   salt and alkali resistance breeding in this species.

Materials and methods

Ethical statement

   This study was conducted in accordance with the principles of animal
   protection, livestock, and ethical standards, and was authorized by the
   Animal Ethics Committee of Shanxi Agricultural University (Approval
   No.SXAU-EAW-2022 F.YC.012017254).

Salinity design and experimental fish sampling

   Juvenile P. ussuriensis were obtained from the breeding base in Yongji
   City, Shanxi Province. The fish were transported alive in oxygen bags
   to the laboratory and housed in a static water pool for
   acclimatization. The juveniles P. ussuriensis (body length: 10.50
   ± 3.09 cm, body weight: 16.76 ± 6.38 g) were acclimatized and subjected
   to salinity treatments at the aquaculture laboratory of Shanxi
   Agricultural University. The fish were maintained in aerated tap water
   at a temperature of 20–25 °C for two weeks, under a natural light
   cycle, with dissolved oxygen levels maintained between 8.00 and 9.50
   mg/L. The fish were fed a commercial floating feed at approximately 1%
   of body weight twice daily at 08:00 and 16:00. Light/dark cycle of 14
   h: 10 h. After acclimatization, feeding was stopped for two days, and
   the fish were randomly distributed into six culture tanks (2.0 m × 1.0
   m × 1.0 m), with 100 fish per tank. The fish were randomly assigned
   into two groups: the treatment group and the control group, each with
   three replicates (three tanks per group). The treatment group was
   exposed to 10 ppt NaCl, a concentration determined from preliminary
   studies on the salt-alkali tolerance of P. ussuriensis. The control
   group was maintained in well-aerated tap water, under the same
   conditions as the acclimatization period, with no feeding during the
   experiment. The experimental period lasted 96 h, with sampling at time
   points of 6, 12, 24, 48, 72, and 96 h. For each time point, 9 fish from
   each replicate group were randomly selected, anesthetized with MS-22,
   and used for paraffin tissue sectioning and antioxidant enzyme activity
   analysis. At 24 h (In the salinity tolerance test, juveniles fish
   gradually exhibited stress responses within 30 min. Synchronous changes
   in gill physiological indicators were observed: gill filament
   hyperemia, increased amplitude of opercular movements, and a rapid rise
   in respiratory rate, indicating that the juveniles had activated an
   acute respiratory compensation mechanism. After 12 h of continuous
   salinity stress, the behavioral patterns of the juveniles underwent
   systematic changes—such as circular swimming along the tank walls,
   remaining suspended at the water surface, and an increased demand for
   dissolved oxygen—suggesting that the organisms had entered a
   compensatory adaptation stage involving energy metabolism and osmotic
   regulation. By 24 h, irreversible physiological failure was evident,
   characterized by tilting and rolling motions, increased mucus secretion
   on the body surface, startle reflexes triggered by external mechanical
   stimuli, and subsequent uncontrolled behaviors such as rapid swimming
   and rolling. Furthermore, a decrease in opercular movement frequency
   and a collapse of respiratory compensation, along with neuromuscular
   dysregulation, indicated that the organisms had exceeded their salinity
   tolerance threshold and entered a process of multisystem failure.
   Therefore, a 24-h time point was chosen for sampling.), 18 fish per
   group were randomly selected from each replicate for gill and kidney
   tissue sampling, which were rapidly frozen in liquid nitrogen and
   stored at −80 °C for subsequent RNA extraction, reverse transcription,
   sequencing, and metabolomics analysis. At the end of the experiment, 9
   fish from each control group replicate were randomly selected for
   tissue sampling (for paraffin sectioning and antioxidant enzyme
   activity), and 18 fish were used for transcriptomics and metabolomics
   sequencing.

Histopathological analysis and antioxidant enzyme activity assay

   Gill and kidney tissues fixed in 4% paraformaldehyde were dehydrated in
   ethanol, cleared in xylene, embedded in paraffin, sectioned, stained
   with hematoxylin and eosin, and mounted. The tissue structures were
   then observed using an optical microscope.

   Gill and kidney samples were homogenized in ice-cold physiological
   saline (1:9, w/v). The homogenates were then centrifuged at 2,500 g for
   10 min at 4 °C, and the supernatant was collected to prepare a 10%
   tissue homogenate for measuring the activities of SOD, CAT, and
   glutathione peroxidase (GSH-Px), as well as MDA levels.Biochemical
   assays for catalase (CAT, A007-1-1), malondialdehyde (MDA, A003-1)
   superoxide dismutase (SOD, A001-3), and glutathione peroxidase (GSH-PX,
   A005-1) were performed according to the specifications provided by
   Nanjing Jian cheng Bioengineering Institute (Nanjing, China).The
   activities of GSH-Px, CAT, and SOD, as well as MDA levels, were
   measured using colorimetric methods at wavelengths of 405 nm, 405 nm,
   450 nm, and 532 nm, respectively.

Metabolomics analysis

   A 20 mg sample was weighed into a 1.5 mL EP tube, to which two small
   steel beads were added. Then, 300 µL of methanol-water (V: V = 4:1,
   containing mixed internal standards, 4 µg/mL) was added. After
   pre-cooling at −40 °C for 2 min, the sample was ground using a grinder
   (60 Hz, 2 min). The sample was then extracted by sonication in an
   ice-water bath for 10 min and left to rest overnight at −40 °C. The
   sample was centrifuged at 12,000 rpm for 10 min at 4 °C, and 150 µL of
   the supernatant was collected. The supernatant was filtered using a
   0.22 μm organic phase filter and transferred to an LC vial for
   analysis. Samples were stored at −80 °C until LC-MS analysis. Quality
   control (QC) samples were prepared by mixing equal volumes of the
   extraction solution from all samples. All extraction reagents were
   pre-cooled at −20 °C before use.

   The analysis was performed using a Waters ACQUITY UPLC I-Class
   plus/Thermo QE ultra-performance liquid chromatography coupled with
   high-resolution tandem mass spectrometry (LC-MS) system.

Transcriptome analysis

RNA extraction and library construction

   Total RNA was extracted using TRIzol (Cat.No. B511311, Sangon Biotech,
   Shanghai, China) reagent according to the manufacturer’s instructions.
   RNA purity and concentration were assessed using a NanoDrop 2000
   spectrophotometer (Thermo Scientific, USA), and RNA integrity was
   evaluated using an Agilent 2100 Bioanalyzer (Agilent Technologies,
   Santa Clara, CA, USA). Transcriptome libraries were constructed using
   the VAHTS Universal V6 RNA-seq Library Prep Kit following the
   manufacturer’s instructions. The library quality was verified using the
   Agilent 2100 Bioanalyzer, and sequencing was performed on the Illumina
   Novaseq 6000 platform to generate 150 bp paired-end reads.
   Transcriptome sequencing and analysis were conducted by Shanghai OE
   Biotech Co., Ltd. (Shanghai, China).

De novo transcriptome sequencing analysis and differential gene analysis

   Raw reads in fastq format were processed using Trimmomatic to remove
   reads containing poly-N and low-quality reads, obtaining clean reads
   [[68]26]. After removing adapters and low-quality sequences, clean
   reads were assembled into expressed sequence tags (contigs), and de
   novo transcript assembly was performed using Trinity [[69]27]. The
   longest contig for each gene was selected as the unigene for further
   analysis.

   Unigenes were annotated by alignment with databases including NCBI
   non-redundant (NR), Swiss-Prot, and Gene Ontology (GO), using Diamond
   software with an e-value threshold of < 1e-5 [[70]28]. EggNOG and KOG
   annotations were also performed. Functional annotation of the unigenes
   was done based on sequence similarity to known proteins. These unigenes
   were mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG)
   database for pathway annotation, and GO classification was performed
   through mapping to Swiss-Prot and GO terms [[71]29].

   After unigene annotation, Bowtie2 was used to calculate the number of
   reads mapped to each unigene in each sample [[72]30]. The expression
   levels of unigenes were calculated using eXpress [[73]31] software and
   reported as fragments per kilobase of transcript per million mapped
   reads (FPKM). Differential expression was analyzed using DESeq2
   [[74]32], with negative binomial distribution (NB) for significance
   testing. The default criteria for differential expression were set at
   q-value < 0.05. Hierarchical clustering of differentially expressed
   genes (DEGs) was performed using R (v 3.2.0) to display gene expression
   patterns across different groups and samples. GO and KEGG pathway
   enrichment analysis of DEGs were performed using R, with visualization
   of enriched functional terms in bar charts or enrichment circle plots.

Real-time quantitative PCR validation

   Primers for differentially expressed genes were designed using Primer
   Premier 5 software, and synthesized by Sangon Biotech (Shanghai) Co.,
   Ltd. (see table [75]1). β-actin was used as the internal reference
   gene. qRT-PCR was performed on 12 differentially expressed genes from
   the gill and kidney tissues. The primers and RT-qPCR conditions are
   detailed in Table [76]1. qRT-PCR was carried out using the TB Green^®.
   Premix Ex Taq™ II (Tli RNaseH Plus) kit (Cat.No. RR820 A TaKaRa, Japan)
   following the manufacturer’s instructions on a real-time PCR system
   (Roche, Switzerland). Relative expression levels of DEGs were
   calculated using the 2^–ΔΔCt method [[77]33].

Table 1.

   Sequences of primer pairs used in the qRT-PCR
   Tissue Gene name Primer sequence(5’→3’) Product length (bp) Tm(℃)
   Efffciency values(%)
   gill MAFA F: GGACTGTGGCTGTAGGAGTTTGTG 106 67.8 98
   R: GGAACACCGACTGAAATCCAGACC 70.5
   MMP9 F: TGGAAGAGACTGGTGAGCTGGAC 89 69.0 104
   R: TGTTTGGTAGTTGCGGATGTCTGG 70.7
   KCNQ1 F: AGAGGGAGAGTGATGTGAGCAGTG 132 68.0 95
   R: AGCTGTCCTCAAGGGCAGATGG 70.7
   CXCL11 F: GGACAACCAAGGACCAATGTGAGG 85 71.3 96
   R: CGATCTTGTCAATGCGTTGTGTCC 71.4
   KRT1 F: GATTCAAACTGCCGTGACCGAAAC 103 71.2 103
   R: TTCCTCTTCCATTGCTTGCGTCTC 71.2
   LGMN F: AGCGTGTCGTTCTGGATCAATGC 83 71.3 93
   R: TGAGTTCGTCAGGCTTGCATGAAG 71.4
   kidney SOCS3 F: TCCAGTCACCCACCACCTTCTTC 92 70.4 95
   R: CTGGCTTGGTTGTTGTGCTGTTG 70.7
   HMOX1 F: GCAGCCCAAATCTCCTCGTAGC 127 69.9 105
   R: GAGAAGAATGCCACACCCTCCTTG 70.7
   ATP1 A F: CATGAAGCGGCAACCCAGAAATG 108 73.0 99
   R: AAGAACCCTGCTGCTGCTTGC 69.8
   HMGB1 F: AGGACATTGCAGCATATCGGAAGG 110 70.6 97
   R: GTCGTCGTCGTCATCATCGTCATC 71.9
   IRF1 F: AACCATGCCTGTGTCCAGAATGC 86 71.1 93
   R: CTACCCAGACAAGTCCAGCGATTG 69.6
   DDX58 F: GCAGGCTCGGGTATGACTTTGAC 97 69.7 94
   R: CAGCAACGGAGGTGGCGATAAG 71.5
   β-actin F: CCTCCGTCTGGATTTGGCTG 141 69.0
   R: TCAAGGGCGACGTAGCAGAG 67.7
   [78]Open in a new tab

Integrated analysis of metabolomics and transcriptomics

   Differential metabolites (DMs, P-value < 0.05,|VIP| > 1) and DEGs
   (q-value < 0.05, FC > 2.0 or FC < 0.5) were integrated for comparative
   analysis between control and stressed groups. Pearson correlation was
   calculated using the R package (stats package) to analyze the
   relationship between metabolomics and transcriptomics data. A heatmap
   was used to visualize the associations between DMs and DEGs.

Data analysis

   In this experiment, All data were expressed as mean ± SD. Statistical
   analysis was carried out with IBM SPSS Statistics 24.0, employing
   one-way analysis of variance (ANOVA) and the least significant
   difference (LSD) method to evaluate the significance of differences.
   Statistical significance was defined as P < 0.05 and is denoted by
   different lowercase letters. Graphs and charts were generated using the
   GraphPad Prism 8.3.0 software. All software and database lists used in
   this study are included in the Supplementary Material 1: Tables 1 and
   2.

Results

Acute salinity stress on the tissue structure of P. ussuriensis juveniles

Changes in gill tissue structure

   The HE staining results are shown in Fig. [79]1. In the control group,
   the gill filaments, gill arches, and gill lamellae exhibited normal
   extension, with the tips of the gill filaments maintaining their
   typical morphology. At 6 and 12 h of salinity stress, no significant
   wrinkling was observed in the gill arches or filaments, though mild
   contraction of the gill lamellae was detected. After 24 h of acute
   salinity stress, while no notable wrinkling occurred in the gill arches
   or filaments, a distinct contraction and thinning of the gill lamellae
   became apparent. Additionally, the mucus cells along the margins of the
   gill filaments showed enlarged sizes. At 48, 72, and 96 h, both the
   gill filaments and lamellae displayed pronounced wrinkling and
   thinning.

Fig. 1.

   [80]Fig. 1
   [81]Open in a new tab

   HE Staining Results of P. ussuriensis Gill Tissues Following Acute
   Salinity Stress Treatment at 6 h, 12 h, 24 h, 48 h, 72 h, and 96 h, and
   the Control Group. a Control group (0 h); b 6 h; c 12 h; d 24 h; e 48
   h; f 72 h; g 96 h. Scale bar: 200 μm

Changes in kidney tissue structure

   As shown in the Fig. [82]2, in the control group, the glomeruli,
   proximal tubules, and distal tubules maintained normal cellular
   morphology. Under acute salinity stress, at 6, 12, 24, 48, 72, and 96
   h, the glomeruli exhibited some degree of contraction, and the lumen
   appeared enlarged. Both the proximal and distal tubules showed a
   reduction in tubular diameter, with an increased number of cells
   observed within a single field of view.

Fig. 2.

   [83]Fig. 2
   [84]Open in a new tab

   H&E Staining Results of P. ussuriensis Kidney Tissue Following Acute
   Salinity Stress Treatment at 6 h, 12 h, 24 h, 48 h, 72 h, and 96 h, and
   the Control Group. a Control group; b 6 h; c 12 h; d 24 h; e 48 h; f 72
   h; g 96 h. PCT: Proximal convoluted tubule; DCT: Distal convoluted
   tubule; GL: Glomerulus; 1: Increased number of cells per field of view.
   Scale bar: 50 μm

Changes in antioxidant enzyme activity of P. ussuriensis juveniles under
acute salinity stress

   As shown in Fig. [85]3, the activities of antioxidant enzymes,
   including SOD, CAT, and GSH-Px, in the gill and kidney tissues of P.
   ussuriensis juveniles displayed temporal fluctuations in response to
   acute salinity stress. In both gill and kidney tissues, SOD activity
   initially decreased and then increased with the extension of the stress
   period. Specifically, kidney tissue showed significantly lower SOD
   activity at 6 h and 24 h compared to the control group. In gill tissue,
   SOD activity was significantly lower at 24 h and 72 h relative to the
   control group.

Fig. 3.

   [86]Fig. 3
   [87]Open in a new tab

   Changes in SOD, CAT, GSH-PX, MDA enzyme activities in gill (G) and
   kidney (K) of P. ussuriensis under acute salt stress at 0 h, 6 h, 12 h,
   24 h, 48 h, 72 h, and 96 h. 0 h represents the control group. Different
   letters indicate significant differences (P < 0.05)

   In both gill and kidney tissues, GSH-Px activity exhibited a
   fluctuating trend: it initially decreased, then increased, followed by
   another decline, and finally rose again under prolonged stress.
   Compared with the control group, GSH-Px activity in the gill tissues
   was significantly reduced at 6, 24, and 96 h. In the kidney tissues,
   GSH-Px activity was significantly higher than that in the control group
   at 12 h, but significantly decreased at the other time points. while
   gill tissue showed significantly higher enzyme activity at 48 h and 72
   h compared to 24 h. MDA levels in gill tissue showed an initial
   decrease followed by an increase with longer stress exposure, while in
   kidney tissue, MDA levels initially increased and then decreased. MDA
   levels in gill tissue were much higher than in kidney tissue.
   Specifically, MDA levels in gill tissue were significantly lower than
   in the control group at 6 h, 12 h, and 72 h. In kidney tissue, MDA
   levels were significantly higher than the control group at 6 h, 24 h,
   and 48 h, with the highest MDA level observed at 48 h.

   These results suggest that acute salinity stress leads to complex and
   time-dependent changes in antioxidant enzyme activities and oxidative
   stress markers in the gill and kidney tissues of P. ussuriensis. The
   differential response of these tissues indicates the varying capacities
   of the organs to cope with oxidative damage induced by salinity stress.

Metabolomics analysis under salinity stress at 24 h

Multivariate statistical analysis of metabolites in gill and kidney tissues

   OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) is a
   supervised model that differs from PCA (Principal Component Analysis)
   in that it reduces systematic noise and extracts variability-related
   information, making it a better model for classification. In the
   OPLS-DA score plots, the control and salinity-stressed groups were
   clearly separated, indicating that 24 h of salinity stress
   significantly disturbed the metabolite profiles in the gill tissue
   (Fig. [88]4A and B). The R^2Y and Q^2 values of the OPLS-DA model for
   gill tissue were 0.876 and − 0.456, respectively, while for kidney
   tissue, the values were 0.994 and − 0.104, demonstrating the high
   predictability and suitability of the OPLS-DA model for subsequent data
   analysis.

Fig. 4.

   [89]Fig. 4
   [90]Open in a new tab

   Quality analysis of metabolomics data. A OPLS-DA score plot of gill
   tissues. B OPLS-DA score plot of kidney tissues. C Permutation test
   plot of OPLS-DA for gill tissues. D Permutation test plot of OPLS-DA
   for kidney tissues

   A permutation test with 200 iterations was performed on the OPLS-DA
   model to verify overfitting (Fig. [91]4C and D). The results showed
   that the R^2 and Q^2 values from the random permutations were higher
   than those from the original OPLS-DA model, confirming that the OPLS-DA
   model is reliable and effective, with no overfitting.

   To identify significantly different metabolites between groups, a
   combination of multivariate and univariate analyses was employed. In
   OPLS-DA and PLS-DA analyses, the variable importance in projection
   (VIP) values were used to assess the impact and explanatory power of
   each metabolite in distinguishing between groups. Differential
   metabolites with biological significance were identified and validated
   using a t-test to confirm their significance.

   With a VIP > 1.0 and a p-value < 0.05, a total of 85 differential
   metabolites (DMs) were identified in the gill tissue, with 49
   upregulated and 36 downregulated, compared to the control group. In
   kidney tissue, 433 DMs were identified, with 252 upregulated and 181
   downregulated. To visualize the relationships between the samples and
   the expression differences of metabolites across groups, Stratified
   cluster analysis was performed for the top 50 most significant
   metabolites based on all significant metabolite VIP scores (Fig. [92]5A
   and B). The results showed clear color changes between the groups,
   indicating that salinity stress significantly impacted the metabolite
   profiles of both gill and kidney tissues. Notably, lipid metabolism was
   most significantly affected.

Fig. 5.

   [93]Fig. 5
   [94]Open in a new tab

   Hierarchical clustering analysis of DMs and metabolomics view of
   significant metabolic pathways. A Heatmap of top 50 metabolite
   clustering analysis for gill tissues. B Heatmap of top 50 metabolite
   clustering analysis for kidney tissues. C Total KEGG analysis bubble
   plot for gill tissues. D Total KEGG analysis bubble plot for kidney
   tissues. Relative metabolite levels are depicted according to the color
   scale, with red indicating up regulation and blue indicating down
   regulation. The size of the bubbles is proportional to the impact of
   each pathway, and the color of the bubbles indicates the degree of
   significance, ranging from highest (red) to lowest (white). DG0:
   Control group gill tissues; DG3: Experimental group gill tissues, 24 h
   salt stress; DK0: Control group kidney tissues; DK3: Experimental group
   kidney tissues, 24 h salt stress

   To explore the potential metabolic pathways influenced by 24 h of
   salinity stress, pathway analysis was conducted using the KEGG database
   (website: [95]https://www.genome.jp/kegg/), based on all differential
   metabolites (Total), upregulated differential metabolites (Up), and
   downregulated differential metabolites (Down). The results indicated
   that salinity stress for 24 h affected multiple metabolic pathways in
   both gill and kidney tissues. As shown in (Fig. [96]5C and D), the most
   significantly impacted metabolic pathways in gill tissue were
   glycerophospholipid metabolism, followed by glycine, serine, and
   threonine metabolism, D-amino acid metabolism, and the biosynthesis of
   valine, leucine, isoleucine, and arginine. In kidney tissue, the
   significantly affected pathway was glycosylphosphatidylinositol
   (GPI)-anchor biosynthesis, followed by linoleic acid metabolism,
   glycerophospholipid metabolism, and the biosynthesis of unsaturated
   fatty acids.

Transcriptomic analysis of P. ussuriensis under 24-hour salinity stress

Overview of transcriptome sequencing results

   A total of 12 samples were used for transcriptome sequencing in this
   analysis, generating 77.17 GB of clean data. The effective data for
   each sample ranged from 5.73 to 7.03 GB, with a Q30 base distribution
   between 94.84% and 95.46%, and an average GC content of 45.45%. A total
   of 84,887 unigenes were assembled, with a total length of 105,767,614
   bp and an average length of 1,245.98 bp. The unigene annotation results
   were as follows: 38,479 (45.33%) unigenes annotated to the NR database,
   29,227 (34.43%) annotated to the Swiss-Prot database, 14,046 (16.55%)
   annotated to the KEGG database, 22,444 (26.44%) annotated to the KOG
   database, 32,829 (38.67%) annotated to the eggNOG database, 26,268
   (30.94%) annotated to the GO database, and 23,908 (28.16%) annotated to
   the Pfam database. The reads were aligned to the unigenes with a
   mapping rate ranging from 87.15 to 89.6%. Two comparison groups were
   established, and 2,554 and 1,066 DEGs were detected in the gill and
   kidney tissues, respectively. A total of 64,371 SSRs (simple sequence
   repeats) were predicted, with 14,770 unigenes containing more than one
   SSR. Additionally, 46,565 CDS sequences were predicted, of which 38,691
   were predicted by the database alignment method, and 7,874 were
   predicted by ESTS can. The clean data set is available in the NCBI
   Sequence Read Archive (SRA), accession number to be provided.

DEG analysis

   A total of 2,554 DEGs were identified in gill tissue and 1,066 in
   kidney tissue (with q < 0.05 and fold change > 2). Compared to the
   control group, 826 genes were upregulated, and 1,728 genes were
   downregulated in the gill tissue after 24 h of salinity stress. In
   kidney tissue, 508 genes were upregulated, and 558 genes were
   downregulated. Volcano plots were created to show the overall
   distribution of DEGs in both tissues (Fig. [97]6A and B). Hierarchical
   clustering analysis was performed on the DEGs, which revealed
   significant expression differences between the groups, with the results
   shown as heatmaps (Fig. [98]6C and D). The results indicate significant
   differences in gene expression between the control and
   salinity-stressed groups.

Fig. 6.

   [99]Fig. 6
   [100]Open in a new tab

   Volcano plots and clustering heatmaps of the distribution trends of
   DEGs in the stress and control groups of gill and kidney tissues. A and
   B Volcano plots showing the distribution trends of DEGs in gill and
   kidney tissues between the stress group and the control group. Red dots
   represent up regulated genes, blue dots represent down regulated genes,
   and gray dots represent genes with no differential expression. The
   X-axis displays log2 FoldChange, and the Y-axis displays -log10pValue.
   C and D Heatmap of clustering analysis for DEGs in gill and kidney
   tissues between the stress group and the control group. ZG0: Control
   group gill tissues; ZG3: Experimental group gill tissues, 24 h salt
   stress; ZK0: Control group kidney tissues; ZK3: Experimental group
   kidney tissues, 24 h salt stress

DEG pathway enrichment

   To better understand the biological significance of the DEGs, we used
   the GO database for comparison and annotation, as shown in
   (Fig. [101]7A and B). n the ZG3 vs. ZG0 group, biological process (BP)
   terms were significantly enriched in immune response, protein
   translation and folding, and leukocyte chemotaxis. Cellular component
   (CC) terms were primarily associated with the ribosome, cytosolic large
   ribosomal subunit, and proteasome complex. Molecular function (MF)
   analysis indicated significant enrichment in structural constituents of
   the ribosome and muscle. In contrast, in the ZK3 vs. ZK0 group, BP
   analysis highlighted immune-related functions such as defense response
   to viruses and innate immune response, as well as phosphate ion
   homeostasis. MF terms were predominantly associated with glucose
   transmembrane transporter activity, lipopolysaccharide binding, and
   other metabolic and immune regulatory functions.

Fig. 7.

   [102]Fig. 7
   [103]Open in a new tab

   Bubble plots of GO and KEGG analysis of gill and kidney tissues. A and
   B GO analysis bubble plots of gill (G) and kidney (K) tissues. C and D
   KEGG analysis bubble plots of gill (G) and kidney (K) tissues

   Additionally, to further explore the relationship between DEGs and
   metabolic pathways, all DEGs were mapped to KEGG pathways, and the top
   20 significant pathways were selected. KEGG enrichment analysis
   revealed that 24 h salinity stress significantly affected various
   metabolic and immune pathways in both gill and kidney tissues. In gill
   tissue, the significantly affected pathways included tyrosine
   metabolism, alanine, aspartate, and glutamate metabolism, oxidative
   phosphorylation, glycolysis, and gluconeogenesis. In kidney tissue,
   pyrimidine metabolism was the significantly affected pathway. Moreover,
   gill tissue was enriched in pathways related to cell necrosis, ribosome
   function, and antigen processing and presentation, while kidney tissue
   was enriched in pathways such as mineral absorption,
   aldosterone-regulated sodium reabsorption, prolactin and thyroid
   hormone signaling, Jak-STAT signaling, HIF-1 signaling, and TNF
   signaling pathways (Fig. [104]7C and D).

qRT-PCR validation

   To further validate the reliability of the transcriptomic analysis
   results, we performed qRT-PCR on 12 randomly selected DEGs from both
   the control and salinity stress groups. The specific genes selected for
   validation are listed in the Table [105]1. The results showed that the
   expression levels of the genes detected by qRT-PCR exhibited a similar
   trend to the RNA-Seq results (Supplementary Material 2). This
   consistency between qRT-PCR and RNA-Seq data confirms the reliability
   of our RNA-Seq findings. In gill tissue, the relative expression of
   MAFA, MMP9, and KCNQ1 was upregulated, but the relative expression of
   CXCL11, KRT1, and LGMN showed a decreasing trend. In kidney tissue, the
   relative expression of SOCS3 and HMOX1 showed an increasing trend,
   while the relative expression of genes ATP1 A, HMGB1, IRF1, and DDX58
   was downregulated.

Integrated analysis of metabolomics and transcriptomics

   Correlation analysis using the Spearman correlation algorithm was
   conducted to explore the relationships between transcriptomics and
   metabolomics data. The top 30 significantly different entries (based on
   p-value ranking) from both the transcriptomic and metabolomic datasets
   were selected. For datasets with fewer than 30 significant entries, all
   significant results were used for correlation analysis. The correlation
   between these datasets was calculated, and the results are presented in
   heatmaps (Fig. [106]8A for gills and Fig. [107]8B for kidneys). The
   main contents are shown in the attached table pathwayG0-G3
   (Supplementary Material 3) and pathwayK0-K3 (Supplementary Material 4).

Fig. 8.

   [108]Fig. 8
   [109]Open in a new tab

   A and B Correlation heatmaps of the top differential metabolites in
   gill (G) and kidney (K) tissues. C and D KEGG pathway bar plots of gill
   (G) and kidney (K) tissues. E and F KGML network diagrams of gill (G)
   and kidney (K) tissues. Circular nodes represent differentially
   expressed genes/proteins, square nodes represent differential
   metabolites, and triangular nodes represent associated pathways. Node
   colors indicate regulatory patterns: orange for upregulated, blue for
   downregulated, and light blue for nodes with conflicting up- and
   down-regulation associations. Node size corresponds to the degree of
   connectivity

   Furthermore, a bar chart was created to display the common top 30
   pathways from both omics, with significant threshold lines indicated
   (Fig. [110]8C and D). To further elucidate the network relationships
   between genes, metabolites, and pathways, a KGML (Kyoto Gene and
   Genomic Markup Language) network analysis was performed (Fig. [111]8E
   and F). The letters correspond to the relationships between metabolites
   and genes, as detailed in Supplementary Material 1: Table 3 − 1 and
   Table 3 − 2.

   The integrated transcriptomic and metabolomic analysis revealed that
   metabolic activities in the gill tissue were significantly enriched in
   pathways related to glycerophospholipid metabolism, glycine, serine,
   and threonine metabolism, amino sugar and nucleotide sugar metabolism,
   aminoacyl-tRNA biosynthesis, arginine and folate biosynthesis, as well
   as the degradation of taurine, ether lipids, and branched-chain amino
   acids (valine, leucine, and isoleucine). Additionally, pathways such as
   pyrimidine metabolism, steroid hormone biosynthesis, and arachidonic
   acid metabolism were also involved.

   In contrast, the kidney tissue exhibited a more extensive regulatory
   network. Besides sharing pathways with the gill, such as pyrimidine
   metabolism, glycerophospholipid metabolism, and steroid hormone
   biosynthesis, it was also enriched in neuroactive ligand-receptor
   interactions, programmed necrosis, autophagy, the mTOR signaling
   pathway, oxidative phosphorylation, the TCA cycle, and fatty acid
   degradation-key pathways associated with energy metabolism and cellular
   homeostasis. Furthermore, the kidney exhibited significant enrichment
   in the metabolism of multiple amino acids (e.g., alanine, aspartate,
   glutamate, cysteine, methionine, and tyrosine) and pathways related to
   transmembrane transport and cofactor synthesis, including ABC
   transporters and pantothenate/coenzyme A biosynthesis.

Discussion

   Salinity is a crucial factor in aquaculture, influencing fish stress
   responses, survival, and productivity. Research on acute salinity
   stress aids in optimizing salinity levels and breeding species suited
   for specific environments. This study integrates metabolomics,
   transcriptomics, and physiological-biochemical analyses to investigate
   the effects of acute salinity stress on tissue structure, energy
   metabolism, and immune pathways in P. ussuriensis, offering new
   insights into oxidative stress and regulatory mechanisms in the gill
   and kidney.

Oxidative stress

   SOD, CAT, GSH-Px, and MDA are key indicators of antioxidant stress,
   reflecting the cellular oxidative stress status and function of the
   antioxidant defense system [[112]34]. MDA is a lipid peroxidation
   product generated via ROS-mediated degradation of membrane lipids,
   serves as a key biomarker for oxidative stress and membrane integrity
   disruption, reflecting cellular damage under pathological or
   environmental stress conditions [[113]35]. After 24 h of salinity
   stress, kidney SOD and GSH-Px activities decreased significantly, while
   MDA levels increased. GSH-Px activity also declined in the gill,
   consistent with findings in Cyprinus carpio under similar conditions
   [[114]36]. Similarly, in Oreochromis niloticus, MDA levels
   significantly increased after 5 and 10 days of 15 ppt salinity stress;
   whereas in Carassius auratus, SOD, CAT activity, and MDA levels
   significantly increased under 30-day alkalinity stress, and GSH-Px
   activity also increased significantly [[115]21]. Differences in enzyme
   activities under oxidative stress may be linked to tissue function,
   antioxidant system activity, and metabolic stress. The gill, in direct
   contact with the environment, may have stronger antioxidant defenses,
   while the kidney, involved in excretion and detoxification, faces
   greater oxidative stress. Although CAT activity remained unchanged,
   this may be a temporary compensatory response, potentially increasing
   with intensified stress. HMOX1 is a key oxidative stress-responsive
   gene [[116]37]. It was significantly upregulated in this study,
   indicating a severe oxidative stress response under acute salinity
   stress, with insufficient antioxidant enzymes to fully counter the
   stress.

   Oxidative stress also affects metabolism. Lipid peroxidation caused by
   oxidative stress not only damages cell membranes but also activates
   enzymes such as phospholipases, exacerbating inflammation and cellular
   damage [[117]38]. Changes in glycerophospholipid metabolism also affect
   the antioxidant capacity of cells and their response to oxidative
   stress [[118]39]. Metabolomics data showed that glycerophospholipid
   metabolism was most affected in the gill, while the GPI anchor
   biosynthesis pathway changed most in the kidney. Salinity-induced
   oxidative stress in P. ussuriensis leads to lipid peroxidation,
   membrane disruption, and oxidative damage to proteins and DNA, thereby
   impacting cell signaling and energy metabolism.

Energy metabolism

   Several studies have shown that salt and alkali exposure disturb lipid
   metabolism in aquatic organisms [[119]21, [120]40]. For example,
   salinity stress in Ictalurus punctatus altered fatty acid, oxygen, and
   amino acid metabolism [[121]41]. while in Scophthalmus maximus,
   pathways such as fat digestion and absorption, cholesterol metabolism,
   insulin resistance, and PPAR signaling were significantly affected
   under low-salinity exposure [[122]42]. Additionally, low-salinity
   stress in Seriola dumerili led to marked changes in DEGs related to
   lipid and vitamin metabolism, ion transport, and signal transduction
   [[123]43]. In this study, 24 h of salinity stress significantly
   impacted multiple metabolic pathways in both gill and kidney tissues.
   In the gill, the most significantly altered pathway was
   glycerophospholipid metabolism, followed by glycine, serine, and
   threonine metabolism; d-amino acid metabolism; and the biosynthesis of
   valine, leucine, isoleucine, and arginine. In the kidney, GPI anchor
   biosynthesis was the most affected pathway, followed by linoleic acid
   metabolism, glycerophospholipid metabolism, and the biosynthesis of
   unsaturated fatty acids. Through the integrated analysis of metabolome
   and transcriptome, we found that salinity changes may regulate
   metabolic changes by regulating PC, PA, PE, and SM, as well as changes
   in some key signaling pathways.

   Metabolomic analysis provided a comprehensive profile of metabolic
   changes in the gill and kidney tissues of P. ussuriensis juveniles
   under acute salinity stress. Compared to the control, the salinity
   stress group exhibited significantly increased levels of
   phosphatidylcholine (PC) and phosphatidylethanolamine (PE) in the
   kidney, and elevated phosphatidic acid (PA) and PC in the gill. In
   contrast, sphingomyelin (SM) levels were markedly reduced. Notably, PC
   in the kidney showed two distinct trends, indicating differential
   metabolic responses. As the major components of cellular membranes, PC,
   PA, PE, and SM play crucial roles in activating signaling pathways,
   regulating enzyme activity, and maintaining lipid transport and
   metabolic balance [[124]44]. Phosphatidic acid (PA) serves as a
   precursor for several phospholipids, such as PC and
   phosphatidylinositol, and is involved in fatty acid synthesis and
   storage. Phosphatidylethanolamine (PE) is a key precursor for multiple
   phospholipids, including PC, thereby influencing the dynamic balance of
   intracellular lipids and facilitating membrane fusion with internal
   structures [[125]45]. Sphingomyelin (SM), predominantly located in
   nerve cell membranes and myelin, is tightly regulated by its metabolic
   enzymes. Specifically, sphingomyelinase (SMase) hydrolyzes SM into
   ceramide (Cer), a bioactive molecule that modulates cell proliferation,
   growth, and apoptosis, while SM synthase (SMS) and related enzymes
   maintain the balance between SM and Cer to ensure cellular homeostasis
   [[126]46].

   Transcriptomic analysis supported these findings, with gill tissue
   enriched in pathways including tyrosine metabolism; alanine, aspartate,
   and glutamate metabolism; oxidative phosphorylation; glycolysis; and
   gluconeogenesis, and kidney tissue showing enrichment in pyrimidine
   metabolism pathways. In addition, the insulin signaling
   pathway—critical for blood glucose regulation and energy balance
   [[127]47]. was significantly enriched in both gill and kidney tissues.
   In the gill, the HIF-1 signaling pathway and insulin-regulating
   transcription factor MAFA were upregulated, while PPP1R3, a key
   regulator of glucose and lipid metabolism, was downregulated. In the
   kidney, SLC34 A, which influences ATP synthesis and cellular energy
   status through phosphate regulation [[128]48], was downregulated,
   whereas EGLN, involved in hypoxia-inducible factor degradation
   [[129]49], was upregulated. These findings indicate that acute salinity
   stress markedly disrupts energy metabolism and blood glucose regulation
   in P. ussuriensis.

   These findings suggest that acute salinity stress triggers lipid
   metabolic dysregulation and adaptive membrane remodeling, with gill
   tissues exhibiting heightened vulnerability compared to kidneys. This
   disparity likely stems from the gill’s direct environmental exposure
   and dual roles in osmoregulation/detoxification, rendering it prone to
   oxidative and metabolic injury under abrupt salinity shifts.

Immune response

   Prior studies indicate salinity stress differentially impacts immune
   responses in fish gills and kidneys under acute exposure [[130]21].
   Here, transcriptomic analysis revealed gill-specific enrichment of
   pathways linked to cell necrosis, ribosomal activity, and antigen
   processing/presentation. Notably, HMGB1 is a nuclear DAMP
   (danger-associated molecular pattern) activating inflammation via
   TLR/NF-κB pathways—was downregulated, potentially attenuating
   inflammatory responses by suppressing TLR/RAGE-NF-κB signaling.
   Concurrently, MMP9 (extracellular matrix remodeling [[131]50]. CXCL11
   (immune cell recruitment [[132]51]) and LGMN (antigen processing
   [[133]52]) were upregulated, collectively driving tissue homeostasis
   remodeling while dampening immune activation. These shifts were
   associated with TGF-β/Smad/NF-κB pathway enrichment in gills under 24 h
   10 ppt salinity, suggesting a coordinated mechanism balancing tissue
   repair and inflammation resolution.

   In kidney tissues, enrichment was found in the JAK-STAT and TNF
   signaling pathways. The JAK-STAT pathway, activated by cytokines such
   as interferons and interleukins, regulates immune cell differentiation
   and the balance between pro- and anti-inflammatory factors [[134]53].
   TNF-α signaling, mediated via NF-κB, triggers inflammation and cell
   survival, and influences cell proliferation and apoptosis through p38,
   ERK, and JNK pathways [[135]54]. SOCS3, a cytokine signaling inhibitor,
   suppresses JAK-STAT signaling by binding to JAK kinases and preventing
   STAT translocation, while IRF1 regulates the expression of
   immune-related genes, including IFN-stimulated genes [[136]55,
   [137]56]. Transcriptomic data from this study revealed that under 24 h
   of 10 ppt salinity stress, kidney tissues exhibited activation of the
   JAK-STAT and TNF pathways, with SOCS3 upregulated and IRF1
   downregulated. These changes likely help to prevent excessive immune
   activation and apoptosis while maintaining controlled inflammation.

   Transcriptomic data revealed that 24 h salinity stress triggered
   inflammatory immune responses in both gill and kidney tissues of P.
   ussuriensis, transitioning from acute to chronic inflammation, with
   kidneys exhibiting delayed activation compared to gills. This aligns
   with prior findings: in Carassius auratus, saline-alkali stress
   activated IL-17/NF-κB signaling in gills [[138]21], while high salinity
   suppressed inflammation in Seriola dumerili, impairing pathogen
   clearance [[139]43]. Integrated omics analyses identified
   downregulation of key detoxification/energy metabolism genes in gills.
   ALDH and ALDH7 A1 are primarily involved in aldehyde metabolism and
   oxidative stress response; AOX plays a key role in the oxidation of
   aldehydes and heterocyclic compounds, important for the metabolism of
   drugs and endogenous molecules [[140]57]; HADHA is crucial for the
   β-oxidation of long-chain fatty acids, mainly involved in energy
   production in the mitochondria [[141]58]. ALDH enzymes help detoxify
   reactive aldehydes during oxidative stress [[142]59]. However, chronic
   oxidative stress may downregulate the expression of ALDH and ALDH7 A1,
   thereby reducing metabolism and exacerbating chronic inflammation. I
   Chronic oxidative stress may suppress ALDH/ALDH7 A1 expression,
   exacerbating inflammation by accumulating reactive aldehydes.
   Pro-inflammatory cytokines (e.g., TNF-α, IL-6) could further inhibit
   ALDH activity to sustain immune signaling via aldehyde-mediated DAMP
   pathways [[143]60]. Collectively, these dysregulations impair
   detoxification, lipid catabolism, and energy homeostasis in gills,
   highlighting tissue-specific vulnerability under salinity stress.

   In kidney tissue, ENPP1/3, lglutamine (downregulated), and succinic
   acid (upregulated) showed notable changes. ENPP1 and ENPP3, part of the
   ectonucleotide pyrophosphatase/phosphodiesterase family, regulate
   extracellular adenosine levels and inflammation, linking intercellular
   signaling with immune regulation [[144]61]. Glutamine plays a key role
   in carbon skeleton synthesis, amino acid metabolism, nitrogen balance,
   the TCA cycle, and antioxidant production (e.g., glutathione), and is
   especially important for rapidly proliferating cells [[145]62].
   Succinic acid, a central TCA cycle intermediate, is produced during
   aerobic metabolism and modulates inflammatory responses by inhibiting
   protein decarboxylase activity [[146]63]. The findings suggest that
   under acute salinity stress, kidney cells experience reduced
   antioxidant defense and metabolic adaptability, potentially entering a
   state of inflammation or oxidative stress with a shift toward anaerobic
   or inflammatory metabolic pathways.

Conclusion

   This study employed LC-MS/MS metabolomics, transcriptomics, and
   physiological-biochemical assays to delineate the molecular and
   systemic impacts of 24 h acute salinity stress (10 ppt NaCl) on P.
   ussuriensis juveniles. Both gill and kidney tissues exhibited severe
   oxidative damage, lipid-energy metabolic dysregulation, and
   immune-inflammatory activation, with gills showing earlier and more
   pronounced responses due to direct environmental exposure. Notably,
   tissue-specific adaptive strategies emerged: gills prioritized membrane
   lipid remodeling and acute-phase inflammation resolution (e.g.,
   TGF-β/Smad/NF-κB pathway modulation), while kidneys delayed
   inflammatory transitions through autophagy-apoptosis balancing and TCA
   cycle reprogramming. Multi-omics integration revealed a
   “stress-to-chronicity” shift characterized by sustained downregulation
   of detoxification enzymes (ALDH7 A1, AOX, HADHA) and pro-inflammatory
   mediator accumulation (HMGB1, MMP9), exacerbating metabolic-immune
   crosstalk. These findings uncover a dynamic tolerance mechanism
   balancing osmotic adaptation and redox homeostasis, providing
   actionable targets for salt-resistant breeding programs. The study
   underscores the necessity of combining omics-driven molecular insights
   with physiological validation to decode aquatic stress adaptation
   comprehensively.

Supplementary Information

   [147]Supplementary Material 1.^ (37.4KB, docx)
   [148]Supplementary Material 2.^ (152KB, docx)
   [149]Supplementary Material 3.^ (14.8KB, xlsx)
   [150]Supplementary Material 4.^ (19.6KB, xlsx)

Authors’ contributions

   Conceptualization, YL and LBG; methodology, YLand LBG; validation, YL
   and JZ; formal analysis, KW and MZL; Investigation, RYH and YC;
   resources, WWW; data curation, RYH and YC; writing original draft
   preparation, LBG; writing review and editing, YL; visualization, Weiwei
   Wang; supervision, QL; project administration, QL. All authors have
   read and agreed to the published version of the manuscript.

Funding

   This research was funded by grants from the Biological Breeding Project
   of Shanxi Agricultural University (YZGC133), Fund for introducing
   talents and doctoral research of Shanxi Agricultural University
   (2023BQ08). The Fundamental Research Program of Shanxi Province
   (202303021222081). The Earmarked Fund for Modern Agro-industry
   Technology Research System of Shanxi Province (2024QT155), and
   International Science and Technology Cooperation Program of the
   Ministry of Science and Technology of China (SQ2023YFE0102235). The
   Shanxi Agricultural University Local Cooperation Project
   (XDHZYQFXY-07). This research was also supported by the Shanxi Key
   Laboratory of Animal Genetic Resources Utilization and Breeding.

Data availability

   The raw sequencing reads from the RNA-seq described in this study have
   been deposited in the NCBI Sequence Read Archive under accession number
   [PRJNA1242274]
   ([151]https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1242274).

Declarations

Ethics approval and consent to participate

   This study was approved by the Animal Protection and Ethics Committee
   of Shanxi Agricultural University, approval number IACUC No.
   SXAU-EAW-2025Pu.ZZ.001018260. Throughout the experiment, all fish were
   anesthetized with MS-222 (1: 10,000) to minimize suffering as much as
   possible.

Consent for publication

   Not applicable.

Competing interests

   The authors declare no competing interests.

Footnotes

   Publisher’s Note

   Springer Nature remains neutral with regard to jurisdictional claims in
   published maps and institutional affiliations.

   Yu Liu and Libo Gu contributed equally to this work.

References