Abstract

Introduction

   Cr(VI) is a heavy metal contaminant, can diffuse to ecosystems and harm
   aquatic animals. Gills, as a vital organ in direct contact with the
   aquatic environment, have become a key target tissue for assessing the
   toxicological effects of heavy metal pollution of water bodies due to
   their sensitivity to heavy metal exposure. However, 3the effects of
   Cr(VI) on the gill tissues in fish have been less studied. In this
   study, we revealed the multiple effects of chromium toxicity by
   assessing the oxidative damage, transcriptomic and metabolomic changes
   of Cr(VI) on gill tissues of Thymallus grubii.

Methods

   A total of 270 fishes were stratified into three experimental groups:
   control group, low-concentration exposure group (0.2 mg/L), and
   high-concentration exposure group (1 mg/L). In this study, we revealed
   the multiple effects of chromium toxicity by assessing the oxidative
   damage, transcriptomic and metabolomic changes of Cr(VI) on gill
   tissues of Thymallus grubii.

Results

   Cr(VI) stress can lead to gill damage with significant reduction in
   gill filament thickness, significant thinning of gill lamellae, and
   congestion of epithelial blood vessels. Cr(VI) stress significant
   increases in H[2]O[2] and MDA levels and significant decreases in
   antioxidant enzyme activity levels (SOD, GSH-Px, and T-AOC) and energy
   metabolism-related ATPase activity levels (Na^+K^+-ATPase,
   Ca^2+-ATPase, and Mg^2+-ATPase). Cr(VI) stress induced disturbances in
   gill arachidonic acid metabolism leading to the release of
   pro-inflammatory metabolites (e.g., thromboxane A2 and prostaglandin
   J2) accompanied by the accumulation of oxidised glutathione. However,
   the synthesis of metabolites with anti-inflammatory/antioxidant
   functions (e.g. GABA, quinidine and l-artitic acid) was reduced.
   Transcriptomics and metabolomic coanalyses revealed that Cr(VI) induced
   PPAR-γ inactivation to deregulate COX-2, which disrupted arachidonic
   acid metabolic pathways, leading to oxidative stress, apoptosis, and
   release of inflammatory factors. Disorders of arachidonic acid
   metabolism led to the release of proinflammatory metabolites (such as
   thromboxane A2 and prostaglandin J2), and decreased levels of reduced
   glutathione.

Discussion

   The effects of Cr(VI) exposure on gill gene expression and metabolism
   were analysed using RT-PCR, transcriptomic, and metabolomic approaches.
   In summary, we better understand the toxic effects of Cr(VI) on gill
   tissues of aquatic animals. Targeted activation of PPAR-γ and
   supplementation with anti-inflammatory metabolites such as GABA,
   quinidine and l- artitic acid may be potential intervention strategies
   to reverse Cr(VI) toxicity.

   Keywords: gill, metabolome, transcriptome, Cr(VI) stress, inflammatory
   responses

1. Introduction

   Global water resources are increasingly polluted by heavy metals due to
   rapid industrial development and agricultural activities, seriously
   threatening the aquatic animal health and disrupting the balance of
   ecosystems ([42]1). As a redox-active transition metal ubiquitous in
   industrial systems, chromium persists in natural ecosystems through
   multiple valence states, of which Cr^3+ and Cr(VI)(Cr^6+) are common
   ionic forms ([43]2). Cr^6+ has strong oxidative activity and chemical
   toxicity and can cause allergic dermatitis, neurotoxicity,
   genotoxicity, and cancers ([44]3). Cr^6+ enters cells in the chromate
   ionic state, crossing cell membranes through nonspecific phosphate or
   sulfate anion carriers, leading to mitochondrial damage and cellular
   DNA damage ([45]4). Owing to human activities, the Cr^6+ released from
   industrial production migrates to groundwater by entering surface water
   and soil ([46]5). Hexavalent chromium salts are more soluble than
   Cr^3+; thus, Cr^6+ is relatively more mobile. In aquatic environments,
   Cr^6+ is present for longer periods of time and is more harmful to
   biological systems; therefore, Cr^6+ is more toxic than Cr^3+, which is
   considered one of the most harmful heavy metals ([47]6). Fish is an
   important source of protein for humans, and enrichment of Cr^6+ in
   contaminated fish tissue can be transferred to the human body and poses
   health risks. Therefore, the study of the effects of Cr^6+ exposure on
   fish can provide a basis for the aquaculture industry to formulate
   aquatic product safety standards, and it is also an inevitable choice
   to safeguard human food safety and prevent and control environmental
   pollution.

   Studies have shown that chronic exposure of animals to Cr^6+ leads to
   oxidative stress and significantly increases the expression of
   apoptotic genes; moreover, Cr^6+ can affect the normal function of
   mitochondria, transmembrane potential, and antioxidant enzyme activity,
   resulting in mitochondrial damage, which triggers a cascade of caspase
   proteases leading to apoptotic cell death ([48]7–[49]9). In vitro
   cytotoxicity experiments have shown that Cr^6+ ions enter the cell
   through nonspecific ion channels in the cell membrane and generate
   large amounts of ROS during their reduction to the low-valent form of
   chromium and that the continuous accumulation of ROS in cells causes
   DNA and cellular damage ([50]10, [51]11). Cr^6+ exposure was found to
   cause neurotoxicity and induce oxidative damage in zebrafish ([52]12).
   Gills are important organs for gas exchange, osmoregulation and
   detoxification in fish ([53]13). Gills, characterized by substantial
   surface area and acute responsiveness to aquatic environmental
   fluctuations, serve as primary target sites for toxic metal
   accumulation in aquatic organisms ([54]14). Several studies have
   confirmed that heavy metal exposure leads to gill damage in fish, with
   altered morphology and pathology, energy and metabolic imbalances, and
   impaired antioxidant systems ([55]15–[56]17).

   Amur grayling (Thymallus grubii) is an important albino fish in China
   with high nutritional and economic values. T. grubii has become highly
   valuable as an economic species for cold Water aquaculture, possessing
   tasty meat, rich in unsaturated fatty acids, low cholesterol and high
   protein levels. However, due to environmental pollution and other
   anthropogenic disturbances, the population of T. grubii has declined
   sharply ([57]18). In addition, understanding the response mechanism of
   T. grubii to heavy metal stress can help to provide scientific evidence
   for monitoring the ecological health of the watershed, and provide
   toxicological basis for the development of aquatic animal conservation
   strategies. In heavy metal exposure studies, transcriptomics analyses
   can comprehensively resolve the dynamics of gene expression in
   organisms under heavy metal stress. Metabolomics in heavy metal
   exposure studies can elucidate the details of metabolic processes that
   occur during environmental adaptation and provide a better
   understanding of these processes. However, the effects of Cr^6+ stress
   on tissue, gill metabolism, and gene expression in T. grubii have not
   been reported. In the present study, we assessed the effects of chronic
   Cr^6+ exposure on gill tissue structure, metabolism and gene expression
   in T. grubii. This study was to elucidate the effects of gill exposure
   to heavy metals on gene expression, transcriptomics and metabolomics to
   elucidate the contribution of Cr^6+ to T. grubii-induced gill toxicity
   and the possible underlying mechanisms.

2. Materials and methods

2.1. Animals and diet

   This study was approved by the Ethics Committee for Animal Experiments
   of the Heilongjiang Fisheries Research Institute, Chinese Academy of
   Fisheries Sciences (20241125–007). The Bohai Experimental Station of
   the Heilongjiang Provincial Fisheries Research Institute provided the
   fish for this experiment. Fish were temporarily reared in the aquarium
   for 30 days to acclimatize to the environment. A total of 270 fish of
   uniform size were selected and allocated to nine aquaria (three
   groups), with three biological replicates established in each group.
   Control fish tanks were filled with tap water. In the aquarium for the
   low-concentration exposure group (Lcr group: Cr^6+ of 0.2 mg/L). In the
   aquarium for the high-concentration treatment group (Hcr group: Cr^6+
   of 1 mg/L). Cr^6+ exposure levels refer to the results of previous
   studies and water resources ecosystem surveys ([58]19–[59]21). During
   the feeding experiment, the fish were handfed twice daily (at 8:30 a.m.
   and at 16:00 p.m.) to apparent satiation for 4 weeks. Experimental
   environment of fish: temperature, 10 ± 2°C; pH, 6.8 ± 0.44 dissolved
   oxygen, 5.57 ± 0.63 mg/L; ammonia concentration < 0.3 mg/L; nitrite
   concentration < 0.02 mg/L. Potassium dichromate solution was purchased
   from Merck, China (CAS: 7778-50-9, MDL: MFCD00011367, EC: 231-906-6).
   Each tank was replaced with 25% water daily.

2.2. Fish sampling

   After 24 h of starvation, the fish were anaesthetized with 20.0 mg/L
   tricaine methanesulfonate (MS-222) at weeks 2 and 4 of the experiment.
   Eighteen fish per group were randomly selected and prepared for
   sampling. Fish were euthanized and gills, muscles, livers, and
   intestines were collected. The collected tissues were frozen in liquid
   nitrogen and transferred to a −80°C refrigerator.

2.3. Chromium analysis

   Cr^6+ levels in gills, liver, muscle, and intestines were only examined
   by the methods published in previous studies ([60]22). First 0.1 g of
   sample, 5.0 mL of nitric acid was mixed in an ablative tube and 3.0 mL
   of ultrapure water was added. Mineralization of the samples was carried
   out in a MarXpress microwave ablation system (North Carolina, USA).
   Cooling 0.5 mL of internal standard was added and the sample was
   diluted to 50.0 mL with ddH[2]O and the experiment was repeated 3
   times. Cr^6+ levels in gills, liver, muscle, and intestines were
   quantified using an Agilent 7500cx ICP-MS (Agilent Technologies, Santa
   Clara, CA, USA). Cr^6+ levels in water tanks were determined by the
   same method ([61] Table 1 ).

Table 1.

   Cr^6+ levels in water (mg/L).
   Group Nominal concentration Actual Cr^6+ concentration at 14 days
   Actual Cr^6+ concentration at 28 days
   Control 0 0.004 ± 0.002 0.006 ± 0.001
   Lcr group 0.2 0.186 ± 0.074 0.201 ± 0.032
   Hcr group 1 0.996 ± 0.032 1.002 ± 0.044
   [62]Open in a new tab

2.4. Histopathological examination

   Gill samples were dehydrated in increasing concentrations of ethanol
   (50%, 70%, 80%, 90% and 100%), placed in xylene for 1 minute, dried,
   and embedded in paraffin. Gill tissue samples were cut into thin slices
   of 2-6 μm thickness using a rotary slicer (Leica RM2235). Use
   haematoxylin and eosin and stain according to the manufacturer’s
   instructions. Observations were made using an Olympus BX53
   research-grade biomicroscope (Olympus BX53, Japan), and gill sample
   changes were observed with cellSens software (cellSens 4.1) and
   photographed for preservation.

2.5. Histological enzyme activity

   Assays of hydrogen peroxide (H[2]O[2]), superoxide dismutase (SOD),
   glutathione peroxidase (GSH-PX), total antioxidant capacity (T-AOC),
   catalase (CAT), and malondialdehyde (MDA) levels in the gills were
   performed according to the manufacturer’s instructions. The activities
   of Na^+K^+-ATPase, Ca^2+-ATPase, and Mg^2+-ATPase were determined with
   an ATPase Assay Kit (Kit No. A016-2-2). All kits were purchased from
   Nanjing Jiancheng Bioengineering Institute of China (Nanjing, China).

2.6. Gill metabolome analysis

   The untargeted metabolomics assay was performed by LC-Bio (Hangzhou,
   China) with the following procedures: (a) homogenization of 18 fish
   gills in liquid nitrogen; (b) Metabolite enrichment was performed by
   methanol-buffer precipitation (50%, v/v). The extracted samples were
   subjected to random machine sequential testing, and QC samples were
   inserted before, during and after the samples as a repetitive
   assessment of the experimental technique. Detection of eluted
   metabolites in columns by high performance liquid chromatography
   (HPLC). The data were preprocessed using XCMS (XCMS-v4.7) software.
   Initial feature annotation via MetaX-driven database comparison
   (PlantCyc/KEGG/HMDB). Identification of metabolites in product
   secondary mass spectra using in-house libraries. MetaX software was
   used to perform univariate and multivariate analyses of the
   metabolomics data to identify metabolites that were enriched by
   differences between groups (dm). Differentially abundant features were
   identified when meeting all criteria: (a) Presence in ≥2 biological
   replicates or relative abundance ≤50%; (b) Significant inter-group
   divergence (BH-corrected q < 0.05) via Wilcoxon rank-sum test; (c)
   OPLS-DA variable importance projection (VIP) score ≥1.0. KEGG pathway
   enrichment profiling was conducted using a hypergeometric distribution
   model. Functionally annotated terms with corrected P < 0.05 were
   designated as significantly enriched clusters for differentially
   expressed proteins. Gene set enrichment analysis was performed using
   GSEA (v4.1.0) and MSigDB software programs to determine whether a group
   of genes were differentially enriched in a specific KEGG pathway.

2.7. Transcriptome analysis

   Gill tissue samples from three biological replicates per group were
   subjected to transcriptome sequencing through Hangzhou Lianchuan
   Biotechnology Company, Ltd (Hangzhou, China). Total RNA was extracted
   using TRIzol reagent (TaKaRa, Dalian, China), with RNA integrity
   verified by Bioanalyzer 2100 Bioanalyzer (RIN > 8.0). First-strand cDNA
   synthesis was performed using 6-base random hexamer primers with mRNA
   as template. Second-strand cDNA was generated by adding reaction
   buffer, RNase H, dNTPs, and DNA polymerase. The products were purified
   with QIAquick PCR Purification Kit (Qiagen) and eluted in EB buffer.
   AMPure XP beads (Beckman Coulter) and USER enzyme (NEB) were employed
   for size selection and degradation of uracil-containing second-strand
   cDNA, ensuring strand-specificity of the final library. PCR
   amplification was conducted using Phusion High-Fidelity DNA Polymerase
   (Thermo Scientific) with indexed primers. Sequencing was performed by
   LC-Bio Co., Ltd (Hangzhou, China) on Illumina NovaSeq 6000 platform.
   Then sequence quality was verified using FastQC
   ([63]http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ,
   0.11.9). Genes differential expression analysis was performed by DESeq2
   software between two different groups (and by dgeR between two
   samples). Differentially expressed genes (DEGs) were screened based on
   DESeq2, with significance thresholds set at |log[2](fold change)| ≥ 1
   and corrected p value < 0.05. Volcano plots were generated to
   demonstrate the differential expression distributions by Gplot2, and a
   hierarchical clustering heatmap was visualized using the pheatmap to
   visualize hierarchically clustered heatmaps of DEGs. The genes with the
   parameter of false discovery rate (FDR) below 0.05 and absolute old
   change ≥ 2 were considered differentially expressed genes. The
   differentially expressed genes were then analyzed for GO function and
   KEGG pathway enrichment.

2.8. Gene ontology and enrichment exploration

   GO enrichment analysis of DEGs was performed using Wallenius
   non-central hypergeometric distribution. Pathway enrichment analysis
   was performed using the KEGG database to further assess significantly
   enriched metabolic or signaling pathways, with p value < 0.05 being
   significantly enriched for DGE.

2.9. qRT-PCR validation

   Total RNA was isolated from frozen gills using the TRIzol Reagent Kit
   according to the instructions of the manufacturer and assessed for
   quality. Samples with A260/A280 RNA ≥ 1.8 were selected for cDNA
   synthesis according to the manufacturer’s instructions (Beijing
   Tiangen). The primers used are listed in [64]Supplementary Table S1 .
   Referring to the previous study by Lu et al. ([65]23), specific primers
   were designed using the online tool Primer 3 plus
   ([66]https://www.primer3plus.com/) based on the Amur grayling
   transcriptome sequence (PRJNA907151). qRT-PCR analysis was performed
   using the SYBR Premix Ex Taq II kit (Tli RNaseH Plus, Takara Bio,
   Japan) following the manufacturer’s thermal cycling parameters. The β
   actin served as an internal control to normalize the data. 2^-ΔΔCT
   method was used to calculate the relative expression of target genes
   ([67]24).

2.10. Statistical analysis

   All data are expressed as mean ± standard deviation (SD). One-way
   statistical analysis of variance (ANOVA) was performed using SPSS 20.0
   (SPSS, Chicago, IL, USA). All data were normally distributed and passed
   the equal variance test. Tukey’s multiple post hoc test, and for the
   same sampling intervals, different letters indicate that the
   differences are significant (p < 0.05). Graphical representation of the
   experimental data was performed using GraphPad Prism 9.0 (GraphPad
   Software, USA).

3. Results

3.1. Accumulation of Cr in tissues

   As shown in [68]Figure 1 , Cr^6+ accumulated in the gills, liver and
   intestines of the fish at Days 14 and 28. The level of Cr^6+
   accumulation in fish increased in a concentration-dependent manner (P <
   0.05). The accumulation level of Cr^6+ in each tissue was in the order
   of intestine>liver>gill>muscle. Compared with those in the control
   group, the Cr^6+ accumulation levels in the gill, liver, intestine and
   muscle in the Hcr group were significantly increased (P < 0.05),
   whereas Cr^6+ accumulation in the muscle did not significantly differ
   between the Lcr and control groups (P > 0.05).

Figure 1.

   [69]Charts labeled A to D display Cr accumulation (mg/g) in gill,
   liver, muscle, and gut over 14 and 28 days across control, Lcr, and Hcr
   groups. Higher accumulation is observed in Hcr, particularly at 28
   days. Images E to G show histological sections with labels GF, GL, and
   MRC, indicating different tissue structures.
   [70]Open in a new tab

   After 14 and 28 days, different levels of Cr^6+ accumulated in gills,
   liver, muscle and intestine of the T. grubii (A-D). The data are
   expressed as the means ± S.D (n = 6). Bars with different letters are
   significantly different (P < 0.05) according to Tukey’s test for the
   same sampling interval. Gill tissue changes in T. grubii after 28 days
   of Cr^6+ exposure (E-G). (E) H&E staining in the control group; scale
   bars = 100 µm. (F) H&E staining in the Lcr group; scale bars = 100 µm.
   (G) H&E staining in the Hcr group; scale bars = 50 µm 100 µm. GF (gill
   filaments), GL (gill lamellae), MRC (mitochondria-rich cell).

3.2. Histological analysis of gill tissues using H&E-stained sections

   After 28 days, the gill filaments of the control group remained intact,
   the gill lamellae were neatly arranged, and complete physiological
   structures were observed ([71] Figure 1E ). Gill filament
   mitochondria-rich cells (MRCs) were partially vacuolated and gill
   filament thickness was significantly reduced in the Lcr group compared
   to the control group ([72] Figure 1F ). Compared with those of the
   control group, the Hcr group gill filaments of MRCs were heavily
   vacuolated, the gill filament thickness was significantly reduced, gill
   lamellae were significantly thinner, and epithelium vascular congestion
   was observed ([73] Figure 1G ).

3.3. Exposure to Cr induces changes in enzyme activity

   To investigate whether exposure to Cr^6+ causes gill damage, we
   examined the levels of MDA and H[2]O[2] in gill tissue ([74]
   Figures 2A, B ). Compared with the control group, H[2]O[2] levels were
   significantly greater in both the Lcr and Hcr groups (P < 0.05).
   Compared with those in the control group, the MDA levels were
   significantly greater in the Hcr group (P < 0.05). However, there was
   no significant difference in the MDA levels between the control and Lcr
   groups (P > 0.05).

Figure 2.

   [75]Bar charts labeled A to I compare three treatments: Control
   (orange), Lcr (blue), and Hcr (red) across two time points (14 and 28
   days). The parameters include H2O2, MDA, Na+K+-ATPase, Ca2+-ATPase,
   Mg2+-ATPase, SOD, CAT, GSH-PX, and T-AOC, showing variations in values
   with statistical significance indicated by letters above bars.
   [76]Open in a new tab

   Changes in the gill enzyme activity indices of T. grubii after 14 and
   28 days of treatment with different concentrations (0.2 and 1 mg/L) of
   Cr^6+ stress. (A) H[2]O[2]; (B) MDA; (C) Na^+K^+-ATPase; (D)
   Ca^2+-ATPase; (E) Mg^2+-ATPase; (F) SOD; (G) CAT; (H) GSH-Px; (I):
   T-AOC. The data are expressed as the means ± SDs (n=6). Bars with
   different letters are significantly different (P < 0.05) according to
   Tukey’s test for the same sampling interval.

   We further measured changes in gill enzyme activity indicators using
   assay kits ([77] Figures 2C-E ). Compared with those in the control
   group, the Na^+K^+-ATPase, Ca^2+-ATPase, and Mg^2+-ATPase activities
   decreased with increasing Cr^6+ levels (P < 0.05). Compared with those
   in the control group ([78] Figures 2F-I ), the SOD, GSH-PX, and T-AOC
   activities increased but then decreased with increasing Cr^6+
   concentration (P < 0.05). However, the CAT activity did not
   significantly differ between the groups (P > 0.05).

3.4. Metabolomics analysis of the effects of Cr^6+ exposure on gill
metabolism

   Metabolomics was used to further clarify the negative effects of
   chronic exposure to Cr^6+ on T. grubii gill tissue. The OPLS-DA results
   revealed significant separation between each Cr^6+ treatment group and
   the control group, suggesting that Cr^6+ significantly interfered with
   the metabolic profile of gill tissues ([79] Figures 3A-C ). A
   permutation test chart was constructed to indicate the degree of model
   fit. The Q2 values were all <R2 values, and the intercepts of the Q2
   values on the y-axis were all <0 ([80] Figures 3D-F ), indicating that
   the OPLS-DA model was not overfitted. Bar charts were constructed to
   display the number of differentially abundant metabolites ([81]
   Figure 3G ). [82]Supplementary Figure S1 . shows heat maps of the top
   30 metabolites with the highest differential abundance in the Lcr and C
   groups. [83]Supplementary Figure S2 . shows heatmaps of the top 30
   differentially abundant metabolites in the Hcr and C groups.
   [84]Supplementary Figure S3 . shows heat maps of the top 30 metabolites
   with the highest differential abundance in the Hcr, Lcr, and C groups.

Figure 3.

   [85]Charts and graphs display data analysis results. Panels A, B, and C
   show PCA scatter plots with different class groups differentiated by
   color. Panels D, E, and F present correlation plots with intercept
   values. Panel G is a bar chart comparing the number of metabolites
   upregulated or downregulated across different comparisons. Panels H, I,
   and J are KEGG enrichment scatter plots displaying metabolic pathways,
   with metabolite numbers represented by circle size and p-values
   indicated by color gradient.
   [86]Open in a new tab

   Quality analysis of metabolomics data and KEGG enrichment analysis
   (n=6). OPLS-DA score plots for metabolites in the C, Lcr and Hcr groups
   (A–C). OPLS-DA permutation test for the positive and negative ion modes
   (D) C vs. Lcr; (E) C vs. Hcr; (F) Lcr vs. Hcr). Changes in the total
   amount of differential metabolites between the two groups (G) KEGG
   enrichment analysis between the two groups (H) C vs. Lcr; (I) C vs.
   Hcr; (J) Lcr vs. Hcr).

   Enrichment analyses of the KEGG pathway were performed on the
   differential metabolites ([87] Figures 3H-J ). Linoleic acid
   metabolism, biosynthesis of plant hormones, alpha-linolenic acid
   metabolism, biosynthesis of plant secondary metabolites, and the sulfur
   relay system were the five pathways most significantly enriched in the
   C Vs. Lcr group ([88] Figure 3H ). The serotonergic synapse,
   neuroactive ligand–receptor interaction, biosynthesis of alkaloids
   derived from the shikimate pathway, asthma, and arachidonic acid
   metabolism pathways were the five pathways most significantly enriched
   in the C Vs. Hcr group ([89] Figure 3I ). The biosynthesis of alkaloids
   derived from the shikimate pathway, glycerophospholipid metabolism,
   ether lipid metabolism, phenylalanine, tyrosine and tryptophan
   biosynthesis, and choline metabolism in cancer were the five pathways
   most significantly enriched in the Hcr Vs. Lcr group ([90] Figure 3J ).

3.5. Transcriptomic analysis of the effect of Cr^6+ exposure on gene
expression in fish gills

   The levels of DEGs between the different treatment groups are shown in
   [91]Figure 4 , with 107 genes up-regulated and 95 genes down-regulated
   between the Lcr and C groups after Cr^6+ exposure, and 379 genes were
   up-regulated and 638 genes were down-regulated between the Hcr and C
   groups. There were 85 genes upregulated and 302 genes downregulated
   between the Lcr and Hcr groups. [92]Figures 4B-D show volcano plot and
   heatmap.

Figure 4.

   [93]Panel A shows a bar graph depicting the number of upregulated and
   downregulated genes across three comparisons: Lcr vs. C, Hcr vs. C, and
   Lcr vs. Hcr. Panel B presents a volcano plot for the C vs. Lcr
   comparison, illustrating gene expression changes with up and
   downregulated genes highlighted. Panel C is a similar volcano plot for
   the C vs. Hcr comparison. Panel D features a heatmap showing
   hierarchical clustering of gene expression levels across different
   samples, with high expression in red and low expression in blue.
   [94]Open in a new tab

   The results of mRNA sequencing. Differentially expressed genes (A),
   volcano plots (B, C) and heatmaps (D) of the DEGs (P < 0.05). n = 3.

3.6. GO analysis and KEGG pathway enrichment based on DEGs

   The results obtained from GO analysis showed that positive regulation
   of oxidative stress-induced neuron intrinsic apoptotic signaling
   pathway, Parkin-FBXW7-Cul1 ubiquitin ligase complex, positive
   regulation of epidermal growth factor-activated receptor activity,
   regulation of autophagy of mitochondrion, and positive regulation of
   ERK1 and ERK2 cascade were the five most significantly enriched terms
   in the C and Lcr groups ([95] Figure 5A ). The sterol biosynthetic
   process, parkin-cholesterol biosynthetic process, steroid metabolic
   process, tRNA aminoacylation for protein translation, and endoplasmic
   reticulum were the five most significantly enriched terms in the C and
   Hcr groups ([96] Figure 5B ). The regulation of dendrite development,
   dendrite cytoplasm, positive regulation of axon extension,
   cyclin-dependent protein serine/threonine kinase activity, and solute:
   proton antiporter activity were the five most significantly enriched
   terms in the Lcr and Hcr groups ([97] Figure 5C ). [98]Supplementary
   Figure S4 . shows the clusters to which each enriched terms in the
   comparison group belongs.

Figure 5.

   [99]Six bubble charts display GO and pathway enrichment statistics
   across different comparisons: C vs. Lcr, C vs. Hcr, and Lcr vs. Hcr.
   Each chart shows various GO terms or pathways on the y-axis and the
   Rich Factor on the x-axis, with bubble size representing gene numbers
   and color indicating p-values. Panels A, B, and C focus on GO
   enrichment, while D, E, and F show pathway enrichment. Charts reveal
   significant enriched terms and pathways in each comparison.
   [100]Open in a new tab

   GO enrichment analysis of transcriptomic genes in gills. (A) C vs. Lcr;
   (B) C vs. Hcr; (C) Lcr vs. Hcr). KEGG enrichment analysis of
   transcriptomic genes in gills. (D) C vs. Lcr; (E) C vs. Hcr; (F) Lcr
   vs. Hcr).

   This study used the KEGG database to annotate the enrichment pathway of
   DEGs ([101] Figures 5D-F ). The galactose metabolism, steroid
   biosynthesis, terpenoid backbone biosynthesis, selenocompound
   metabolism, and biosynthesis of unsaturated fatty acids were the five
   most significantly enriched signal pathway in the C and Lcr groups. The
   steroid biosynthesis, aminoacyl-tRNA biosynthesis, fatty acid
   biosynthesis, proteasome, and pyruvate metabolism were the five most
   significantly enriched signal pathway in the C and Hcr groups. In
   addition, signaling pathways such as selenocompound metabolism,
   aflatoxin biosynthesis, glutathione metabolism, and protein processing
   in endoplasmic reticulum were similarly significantly enriched. The
   aminoacyl-tRNA biosynthesis, arginine and proline metabolism, glycine,
   serine and threonine metabolism, diterpenoid biosynthesis, and
   glycerophospholipid metabolism were the five most significantly
   enriched signal pathway in the Lcr and Hcr groups.

3.7. Cr^6+ induces changes in the expression of key genes in gills

   To further explore the effects of Cr^6+-induced oxidative stress on the
   expression regulation of genes in gill tissues, we validated the key
   genes by qRT–PCR ([102] Figure 6 ). Compared with those in the control
   group, the expression levels of IL-10 and GPx4 were significantly
   lower, and those of NF-κB, IL-8, and Caspase-9 were significantly
   greater in the Lcr group (P < 0.05). Compared with those in the control
   group, the expression levels of PPAR-γ, IL-10, TGF-β and GPx4 were
   significantly lower, and those of COX-2, NF-κB, IL-8, HSP70, Caspase-3,
   and Caspase-9 were significantly greater in the Hcr group (P < 0.05).

Figure 6.

   [103]Bar graph showing relative mRNA expression levels for PPAR-γ,
   COX-2, IL-10, TGF-β, NF-κB, IL-8, HSP70, Caspase-3, Caspase-9, and
   GPx4. Three groups are compared: Control (blue), Lcr (purple), and Hcr
   (teal), with error bars and significance denoted by letters a, b, and c
   above the bars.
   [104]Open in a new tab

   Cr^6+ induces changes in the expression of key genes in gills. The data
   are expressed as the means ± S.Ds. (n = 3). The levels of peroxisome
   proliferator activated receptor (PPAR)-γ, Cyclooxygenase-2 (COX-2),
   interleukin 10 (IL-10), transforming growth factor-β (TGF-β), Nuclear
   factor κB (NF-κB), interleukin 8 (IL-8), 70-kDa heat shock protein
   (Hsp70), cysteinyl aspartate specific proteinase 3 (Caspase-3),
   cysteinyl aspartate specific proteinase 9 (Caspase-9), and Glutathione
   peroxidase 4 (GPx4) were detected. Bars with different letters are
   significantly different (P < 0.05) according to Tukey’s test for the
   same sampling interval.

   As shown in [105]Figure 7 , we selected 10 genes for gill qRT-PCR to
   verified the reliability and reproducibility of RNA-Seq. The results
   showed that the upregulation and downregulation trends of the genes in
   the qRT-PCR results were consistent with the RNA-Seq results,
   suggesting that the transcriptome sequencing data were reliable.

Figure 7.

   [106]Two bar graphs labeled A and B compare the log2 fold change of
   genes using RNA-Seq and qRT-PCR methods. Each graph presents data for
   genes like Hsp70, Caspase-3, Caspase-9, NF-κB, and various TRINITY
   sequences. Bars indicate gene expression differences, with orange for
   RNA-Seq and blue for qRT-PCR, showing differences in gene expression
   levels.
   [107]Open in a new tab

   RT–PCR was used to validate transcriptomic gene expression. Comparison
   of genes for RNA-Seq and qRT–PCR (A) C vs. Lcr; (B) C vs. Hcr).

   [108]Figure 8 shows a heatmap for gene and metabolite correlation
   analysis. Correlation analysis in a clustered heatmap revealed that
   PPAR-γ, IL-10, TGF-β and GPx4 were negatively correlated with the key
   metabolites cinchonidine, quinidine, quinine, 5-hydroxy-L-tryptophan,
   thromboxane A2 and prostaglandin J2 and positively correlated with
   5,6-DHET, 14R,15S-EpETrE, γ-aminobutyric acid, leukotriene D4,
   L-aspartic acid, GABA, L- valine, L-tyrosine, and vanillin, whereas
   COX-2, NF-κB, IL-8, HSP70, Caspase-3, and Caspase-9 were inversely
   correlated with the above metabolites.

Figure 8.

   [109]Correlation heatmap displaying the relationships between various
   genes and metabolites, with a color gradient from blue for negative
   correlations to red for positive correlations. Metabolites listed
   include Cinchonidine, Prostaglandin J2, and others, while genes include
   Caspase-3, COX2, and more.
   [110]Open in a new tab

   Heatmap for gene and metabolite correlation analysis.

4. Discussion

   Aquatic ecosystems are at risk of multiple heavy metal exposures due to
   increased industrial wastewater discharges and agricultural pollution,
   of which Cr^6+ is a representative persistent pollutant with
   significant toxic effects on aquatic animals through water column
   enrichment ([111]1). As a key organ for respiration and ion exchange in
   fish, the gill is a primary target organ for heavy metal
   bioaccumulation ([112]25). Therefore, a systematic analysis of the
   metabolic network remodeling of gill tissues under heavy metal exposure
   is highly valuable for revealing species-specific detoxification
   mechanisms and constructing ecological risk threshold models.
   Hexavalent chromium (CrVI), as a redox-active transition metal, induces
   ROS-mediated oxidative stress cascades through Fenton-like reactions,
   specifically depleting reduced glutathione (GSH) while elevating
   oxidized glutathione (GSSG) ratios ([113]26). In this study, Cr^6+
   accumulated significantly in all tissues and organs with increasing
   exposure time. In the present study, Cr^6+ accumulated significantly in
   all tissues and organs with increasing exposure time. Gills were in
   direct contact with water and were the primary target organ for Cr^6+
   enrichment. Intestine and liver had high metabolic activities so the
   Cr^6+ accumulation was higher ([114]19, [115]27). The main reasons for
   the significantly higher accumulation of Cr^6+ in the intestine than in
   other organs may be twofold: firstly, the relatively limited absorption
   efficiency of Cr^6+ in the intestine leads to the prolonged retention
   of Cr^6+ in the intestinal lumen; secondly, cadmium is able to be
   transported and redistributed through the trans-organ interactions
   network (liver-intestinal axis, muscle-intestinal axis,
   brain-intestinal axis, etc.), which has the intestinal as its core, and
   ultimately, it forms a high-concentration accumulation in the
   intestinal tract ([116]17, [117]28, [118]29). Two levels of Cr^6+
   caused damage to the gills of the fish, with the Hcr group being the
   most severely damaged. We found that Cr^6+ can cause gill tissue damage
   mainly through vacuolization of MRC cells, congestion of epithelial
   vessels and a significant reduction in gill filament thickness.
   Previous studies have shown that Cr^6+ exposure can lead to oxidative
   stress in fish through the liver-intestinal axis, resulting in liver
   damage and gut flora disruption ([119]17). MDA and H[2]O[2] are key
   indicators used to measure whether tissues are suffering from oxidative
   damage ([120]30). The present experimental data revealed that Cr^6+
   exposure induced gill damage, and the concentrations of MDA and
   H[2]O[2]in gill tissues were significantly and positively correlated
   with the dose of Cr^6+ exposure. Although Cr^6+ exposure led to a
   significant increase in H[2]O[2] levels, CAT activity did not change
   significantly, probably because the organism had entered an
   irreversible stage of damage due to chronic Cr^6+ stress, which is
   similar to the results of previous studies ([121]20, [122]31). SOD,
   GSH-Px, and T-AOC levels tended to increase but then decreased with
   increasing Cr^6+ content, possibly because T. grubii can adapt to low
   concentrations of Cr^6+ by regulating its metabolism. However, when the
   Cr^6+ concentration exceeded the tolerance threshold, the fish could
   not adapt to Cr^6+ stress through their own metabolism, and the
   antioxidant defense system was imbalanced, which was similar to the
   findings of our previous study ([123]17).

   Owing to industrial pollution and emissions from agricultural
   activities, Cr^6+ enters water bodies through soil infiltration,
   seriously threatening the survival of aquatic organisms. Cr^6+ can
   accumulate in aquatic animals to produce toxic effects. In this study,
   we used a nontargeted metabolomics system to analyze the effects of
   Cr^6+ on the metabolic regulatory network of gill tissues in T. grubii,
   aiming to elucidate the molecular toxicological mechanisms involved in
   the induction of oxidative stress, imbalance of lipid metabolism, and
   cellular inflammatory responses and to provide a theoretical basis for
   the risk assessment of Cr^6+ contamination in aquatic ecosystems. In
   our study, Cr^6+ exposure significantly elevated the metabolites
   thromboxane A2 and prostaglandin J2. The arachidonic acid metabolic
   pathway, serotonergic synapses, and neuroactive ligand–receptor
   interactions are central hubs for the regulation of inflammation,
   neurotransmitter systems, and cellular homeostasis. Studies have
   reported that heavy metal exposure can produce an inflammatory response
   through the metabolism of arachidonic acid to produce excess
   thromboxane A2 ([124]32, [125]33). Maria is similar to our results in
   that activated microglia produce large amounts of PGs after neuronal
   injury. whereas Prostaglandin J2, the most toxic component of the PGs
   family, may contribute to many neurodegenerative disorders, PPARγ
   activation is associated with anti-inflammatory and neuroprotective
   signaling ([126]34). In addition, cadmium exposure can also lead to
   significant downregulation of 5,6-DHET and 14R,15S-EpETrE metabolites
   in rats ([127]35), which is similar to our findings that Cr^6+ exposure
   leads to significant downregulation of these two metabolites. Heavy
   metals interfere with serotonergic synapses and GAD, reduce
   γ-aminobutyric acid (GABA) synthesis, lead to neuroexcitotoxicity, and
   can interact with arachidonic acid metabolism ([128]36, [129]37).
   Leukotriene D4 alleviates inflammatory responses by activating the
   phospholipase C/Ca^2+/protein kinase C pathway ([130]38). L-Aspartic
   acid is another important amino acid that serves as an intermediate in
   the tricarboxylic acid (TCA) and urea cycles, attenuating external
   oxidative stress-induced tissue damage and inflammatory responses
   ([131]39). Gamma-aminobutyric acid (GABA) is also an important amino
   acid with antioxidant properties that regulates lipid metabolism
   ([132]40). In our study, chronic Cr^6+ exposure resulted in significant
   increases in the levels of 5-hydroxy-L-tryptophan, thromboxane A2, and
   prostaglandin J2 and significant decreases in the levels of 5,6-DHET,
   14R,15S-EpETrE, GABA, leukotriene D4, L-aspartic acid, and GABA. This
   suggests that Cr^6+ exposure leads to arachidonic acid metabolism
   disruption and toxic action, whereas elevated levels of 5,6-DHET may be
   adaptive responses produced by the organism. In our study, the
   biosynthesis of alkaloids derived from the shikimate pathway was
   significantly altered, and 5-hydroxy-L-tryptophan, cinchonidine,
   quinidine, and quinine were significantly elevated, whereas L-alanine,
   L-tyrosine, and vanillin levels were significantly reduced.
   Cinchonidine protects against cisplatin-induced oxidative stress by
   activating the PI3K/AKT pathway ([133]41). In contrast, some drugs,
   such as quinine and quinidine, have indirect antioxidant effects,
   thereby mitigating oxidative damage ([134]42, [135]43). L-Valine
   promotes fish growth, improves antioxidant capacity and alleviates
   endoplasmic reticulum stress ([136]44). Thus, the present study
   demonstrated that chronic Cr^6+ exposure leads to disturbances in
   arachidonic acid metabolism and amino acid metabolism, induces
   oxidative damage to gill tissues, and regulates redox levels through
   metabolic reprogramming.

   Fish gill tissue is an important osmoregulatory organ ([137]45). When
   gill tissue is damaged, its osmoregulatory capacity is disrupted,
   directly affecting ATPase activity and leading to electrolyte imbalance
   ([138]46). In the present study, we found that Cr^6+ exposure resulted
   that steroid biosynthesis, fatty acid biosynthesis, biosynthesis of
   unsaturated fatty acids, aflatoxin biosynthesis, and lutathione
   metabolism signaling pathways were significantly altered. In addition,
   elevated expression of HSP70, which functions as oxidative stress
   biomarker, indicated that the cells were in a state of oxidative
   damage. Studies have shown that heavy metals and physiological stress
   can induce significant expression of stress proteins such as HSP70 and
   promote apoptosis by catalyzing Caspase-3 and caspase-9 ([139]47,
   [140]48). The experimental data revealed that chronic Cr^6+ exposure
   significantly upregulated the expression of HSP70, activated the
   apoptotic factors Caspase-3 and Caspase-9 in gill tissues, and
   inhibited the expression of the key antioxidant regulator GPx4,
   suggesting that Cr^6+ exposure mediates structural damage in gill
   tissues. The peroxisome proliferator-activated receptor (PPAR) family,
   classified within the ligand-activated nuclear receptor superfamily,
   comprises three functionally distinct isoforms designated as α, β/δ,
   and γ subtypes ([141]49).These nuclear receptors play important roles
   in metabolism, cell differentiation and inflammatory processes. PPARγ
   has been shown to be a key factor in the regulation of lipid metabolism
   and adipocyte differentiation, and increasing evidence suggests that
   PPARγ exerts anti-inflammatory and neuroprotective functions by
   regulating the transcription of inflammatory genes ([142]50, [143]51).
   In addition, previous studies have found that Cr^6+ can cause severe
   oxidative damage to tissues and organs throughout the body via the
   blood circulation ([144]52). Alwaili et al. found that Cr^6+ exposure
   inhibits PPARγ expression levels and mediates inflammatory responses in
   the mouse heart ([145]53). Jin et al. found that Cr^6+ exposure
   inhibited PPARγ expression levels and mediated apoptosis in chicken
   pancreas ([146]54). Notably, Cr^6+ exposure can lead to blood-brain
   barrier damage and brain-hepatic axis neurotoxicity in zebrafish and
   snakehead fish ([147]28). The results of the present study showed that
   chronic Cr^6+ exposure resulted in significant inhibition of PPARγ,
   accompanied by decreases in the expression levels of its downstream
   anti-inflammatory mediators TGF-β and IL-10. Moreover, Cr^6+ promotes
   the expression of COX-2 and induces the release of the proinflammatory
   cytokine IL-8 via the NF-κB pathway, which ultimately triggers a
   cascading inflammatory response. Low PPAR-γ expression deregulates
   COX-2 inhibition and activates the NF-κB signaling pathway to promote
   inflammatory progression ([148]55). COX-2 synthesizes and promotes the
   formation of thromboxane A2 and prostaglandin E2, leading to disorders
   of arachidonic acid metabolism and causing inflammation and nerve
   damage ([149]56, [150]57). Cinchonine inhibits PPARγ expression,
   downregulates fatty acid synthesis, and modulates inflammatory
   responses ([151]58). IL-10 and TGF-β1 achieve anti-inflammatory effects
   through transcriptional silencing of pro-inflammatory cytokines and
   constitutive inhibition of NF-κB nuclear translocation, thereby
   attenuating inflammation-driven tissue damage ([152]59, [153]60). IL-8
   can be activated by the NF-κB pathway to promote inflammation
   ([154]61). These findings are similar to those in our study, where
   correlation analyses revealed that PPAR-γ was negatively correlated
   with cinchonidine, quinidine, quinidine, 5-hydroxy-1-tryptophan,
   thromboxane A2, and prostaglandin J2, whereas the anti-inflammatory
   factors IL-10, TGF-β, and GPx4 were downregulated, and proinflammatory
   factors were upregulated. However, COX-2 showed the opposite trends of
   correlation with the above metabolites. GABA exerts anxiolytic effects
   as a neurotransmitter while inhibiting the release of proinflammatory
   factors and regulating lipid metabolism by enhancing PPAR-γ ([155]6,
   [156]62). In the present study, we analyzed the adverse effects of
   Cr^6+ exposure on gill tissues by integrating transcriptomics and
   metabolomics. We found that Cr^6+ exposure significantly led to
   increased glutathione depletion, resulting in decreased GPX4 expression
   levels. In addition, Cr^6+ exposure significantly inhibited the
   expression level of PPAR-γ, a key factor in lipid metabolism, and
   induced lipid metabolism disorders, which further activated the NF-κB
   pro-inflammatory signaling pathway to aggravate the release of
   inflammatory factors and triggered the Caspase-3 cascade reaction to
   trigger apoptosis. In this study, we confirmed the mechanism of action
   of Cr^6+ exposure in inducing gill toxicity in Thymallus grubii. Cr^6+
   accumulated in tissues such as intestine, liver and gill, and these
   results highlight the multi organ distribution pattern of Cr^6+. Based
   on these results, we will systematically investigate the cross-organ
   interaction network of Cr^6+ to elucidate the mechanism of Cr^6+
   induced oxidative stress cascade in aquatic animals.

5. Conclusion

   In conclusion, this study elucidates for the first time the mechanism
   of gill tissue damage caused by Cr^6+ in aquatic organisms. The data
   suggest that Cr^6+ exposure disrupts the arachidonic acid metabolic
   pathway by inactivating PPAR-γ to deregulate COX-2, leading to
   oxidative stress and inflammatory responses. Disturbances in
   arachidonic acid metabolism led to the release of proinflammatory
   mediators such as thromboxane A2 and prostaglandin J2, which are
   accompanied by the accumulation of oxidized glutathione. PPAR-γ
   activity inhibition leads to blocked synthesis of metabolites with
   anti-inflammatory/antioxidant functions, such as GABA, quinidine, and
   L-aspartic acid. Therefore, targeted activation of PPAR-γ combined with
   COX-2 inhibitors could be a potential intervention strategy to reverse
   Cr^6+ toxicity ([157] Figure 9 ).

Figure 9.

   [158]Flowchart depicting metabolomics and transcriptome analysis. On
   the left, metabolomics analysis shows pathways including PPARγ, COX-2,
   and arachidonate, leading to arachidonic acid, mangiferic acid pathway
   disorders. Middle section highlights oxidative stress, linking it to
   transcriptome and metabolome combination analyses, leading to gill
   damage and HSP70 increase. Right section depicts transcriptome analysis
   pathways involving PPAR-γ, COX-2, and caspase-3, leading to
   inflammation and apoptosis, showing interactions between NF-κB, TGF-β,
   IL-10, and IL-8. Red arrows indicate changes in levels.
   [159]Open in a new tab

   Mechanism of Cr^6+ causing gill metabolic disorders.

Funding Statement

   The author(s) declare that financial support was received for the
   research and/or publication of this article. The work was supported by
   the Central Public-interest Scientific Institution Basal Research Fund,
   HRFRI, (No. HSY202513Q); Agricultural Finance Special Project of the
   Ministry of Agriculture and Rural Affairs, “Normalization Monitoring of
   Fisheries Resources and Environment in Key Waters of Northeast China”;
   The Central Public-interest Scientific Institution Basal Research Fund,
   HRFRI (NO. HSY202414Q); The New Era Longjiang Outstanding Master’s and
   Doctoral Thesis Project Grant (LJYXL2022-085); Identification and
   evaluation of characteristic Aquatic Animal Germplasm Resources and
   creation of improved varieties in Heilongjiang Province; The Central
   Public-interest Scientific Institution Basal Research Fund, CAFS
   (2023TD59); Technology Collaborative Innovation and Extension System
   for the Freshwater Fish Industry of Heilongjiang Province.

Data availability statement

   The datasets presented in this study can be found in
   online repositories. The names of the repository/repositories
   and accession number(s) can be found in the article/[160] Supplementary
   Material .

Ethics statement

   The animal study was approved by This study was approved by the Ethics
   Committee for Animal Experiments of the Heilongjiang Fisheries Research
   Institute, Chinese Academy of Fisheries Sciences (20241125–007). The
   study was conducted in accordance with the local legislation and
   institutional requirements.

Author contributions

   XS: Conceptualization, Data curation, Funding acquisition,
   Investigation, Resources, Software, Visualization, Writing – original
   draft, Writing – review & editing. XC: Conceptualization, Data
   curation, Investigation, Methodology, Software, Supervision, Writing –
   original draft, Writing – review & editing. KM: Conceptualization,
   Investigation, Software, Writing – review & editing. BM: Data curation,
   Methodology, Validation, Writing – original draft. HS:
   Conceptualization, Formal analysis, Project administration, Writing –
   review & editing. WW: Data curation, Formal analysis, Project
   administration, Writing – review & editing. HH: Methodology, Project
   administration, Supervision, Writing – review & editing. MX: Formal
   analysis, Project administration, Visualization, Writing – original
   draft. WX: Data curation, Project administration, Validation, Writing –
   original draft. YZ: Conceptualization, Data curation, Formal analysis,
   Funding acquisition, Investigation, Resources, Software, Visualization,
   Writing – original draft, Writing – review & editing.

Conflict of interest

   The authors declare that the research was conducted in the absence of
   any commercial or financial relationships that could be construed as a
   potential conflict of interest.

Correction note

   A correction has been made to this article. Details can be found at:
   [161]10.3389/fimmu.2025.1692659.

Generative AI statement

   The author(s) declare that no Generative AI was used in the creation of
   this manuscript.

Publisher’s note

   All claims expressed in this article are solely those of the authors
   and do not necessarily represent those of their affiliated
   organizations, or those of the publisher, the editors and the
   reviewers. Any product that may be evaluated in this article, or claim
   that may be made by its manufacturer, is not guaranteed or endorsed by
   the publisher.

Supplementary material

   The Supplementary Material for this article can be found online at:
   [162]https://www.frontiersin.org/articles/10.3389/fimmu.2025.1633174/fu
   ll#supplementary-material
   [163]Image1.tiff^ (1MB, tiff)
   [164]Image2.tiff^ (1.1MB, tiff)
   [165]Image3.tiff^ (1.5MB, tiff)
   [166]Image4.tif^ (2.2MB, tif)
   [167]Table1.docx^ (21.5KB, docx)

References