Characteristics and differences in immune response capacity and gut microbiome between wild and captive Amur grayling (Thymallus grubii): New insights into endangered fish conservation

Introduction: Endangered species recovery hinges on evaluating captivity-induced shifts in the adaptive traits of candidates slated for reintroduction. Gut microbiota is one such trait and is particularly important for Amur grayling (Thymallus grubii).

Methods: The present study aimed to systematically investigate the differences in intestinal and liver health in Amur grayling from two water environments (wild and captive) by feeding habits, biochemical parameters and 16S ribosomal RNA gene sequencing.

Results: Compared with captive fish, the wild Amur grayling in the liver and gut had higher lysozyme activity (P < 0.05), and alkaline phosphatase, catalase activity and glutathione content in gut was significantly higher (P < 0.05). In addition, the cultured fish showed lower relative expression levels of hepatic IgM, il-6, il-10, il-lβ, myd88, NF-kB, and Tnf-α mRNA expressions than those of wild fish (P < 0.05). In the intestine tissue, the mRNA level of C3, il-6, il-10, il-lβ, tlr1, tlr3, Tnf-α, and LYZ increased in the wild fish while the expression of IgM was significantly elevated (P < 0.05). For gut microbiota, the cultured group displayed higher percentages of Pseudomonadota phylum and lower percentages of Bacillota phylum than the wild group (P < 0.05) .

Discussion: Overall, wild Amur grayling had higher immune capacity and intestinal barrier functions than cultured Amur grayling. This study displayed that responses and adaptations to diverse aquatic environments were shown by liver-gut-microbiota axis in Amur grayling. Our findings could provide a promising direction for the improve its adaptability of wild population in reintroduction project and propose the conservation strategy for biodiversity recovery.

1 Introduction

Amur grayling (Thymallus grubii) is a cold-water freshwater fish species of high nutritional value in China, but it currently faces numerous threats caused by anthropogenic activities, including environmental pollution and overfishing (1). The species has been classified as protected and listed in the “China Red Data Book of Endangered Animals” (2). Consequently, captive breeding in artificially controlled environments is widely used to conserve the limited Amur grayling population in China. However, many attempts to reintroduce the endangered species into its natural habitat have not been successful. One potential reason is the loss of adaptive traits (3), such as alterations in host-associated microbiome composition.

Gut microbiota can be regarded as a signaling hub that integrates environmental inputs with host immune capacity (4, 5). In aquatic animals, wild and captive environments differ significantly in diet, social structure, and sources of stress, which may affect the gut microbial community (6). Differences in gut microbiota composition between wild and hatchery-reared juveniles suggest that the physiological status of juveniles may be influenced by their microbiota (7), potentially conferring a disadvantage after release into the wild. Currently, animal microbiome research has been applied as a perspective for population conservation practices (8). Thus, studies on the gut microbiota in wild and captive animals may provide insights into the adaptation mechanisms of Amur grayling in the wild, which could help increase survival rates during the reintroduction period.

It has been demonstrated that the fish gut microbiome can have significant impacts on host metabolism, immunity, and responses to infection (9, 10). The intestinal microbiota can regulate systemic immunity via signals transmitted through immune cells in the intestine (11). Notably, the liver is anatomically connected to the gut through the portal venous circulation, commonly referred to as the “gut–liver axis”, thereby establishing a close physiological relationship between gut and liver tissues (12). Several studies have shown that the gut microbiota, by coevolving with the host in a mutualism system, coordinates the host’s immunity, metabolism, barrier protection, and structural functions (13, 14). In turn, the host immune system contributes to tolerating beneficial bacteria taxa while inhibiting the growth of harmful bacteria (15). Some studies have reported relationships between microbes and host immune function to compare the health of animals living in farmed and wild environments, such as ricefield eel (Monopterus albus) (16, 17) and pike perch (Sander Lucioperca) (18). However, no prior research has compared the effects of captivity and wild conditions on the physiological functions, metabolism, and immune capacities of Amur grayling in an integrated manner. Such information is essential for improving conditions for captive individuals, thereby aiding in Amur grayling population restoration.

This study aimed to compare immune enzyme activities, immune-related gene expression, and gut microbiota composition between wild and captive Amur grayling, and to identify potential probiotic taxa for conservation and aquaculture enhancement. It also explored the possible relationships among adaptations and immunoregulatory responses of Amur grayling under wild and captive environments from the perspective of gut microbiota–immune interaction.

2 Materials and methods

2.1 Animal ethics statement

All animal experimental procedures were conducted in accordance with the guidelines of the Laboratory Animal Ethics Committee of the Research Institute of Fisheries of the Heilongjiang River (No. 20240909-001), and the guidelines of EU Directive 2010/63/EU for animal experiments were followed throughout the study.

2.2 Fish sampling

Cultured Amur grayling (CAG; n = 15; body length : 19.63 cm ± 0.92 cm; body weight: 112.98 g ± 24.89 g) were obtained from the Bohai Cold Water Fish Experimental Station of the Heilongjiang Institute of Fisheries Research, China. Wild Amur grayling (WAG; n = 15; body length: 18.95 cm ± 2.06 cm; body weight: 108.64 g ± 15.75 g) were captured in the Huma River, part of the upper Amur River, in October 2024. CAG came from the same cohort fed with commercial pellets, and the feed nutrient contents are presented in Supplementary Table S1. Fish were anesthetized with 100 mg/L tricaine methanesulfonate (MS-222, Sigma, Michigan, USA), after which the stomach, intestine, liver, and intestinal contents were immediately collected and stored in RNase-free tubes for subsequent analysis of feeding habits, biochemical measurements, quantitative real-time PCR (qRT-PCR), and gut microbiome analysis. All samples were immediately frozen in liquid nitrogen for 2 h and then stored at − 80°C.

2.3 Observation of feeding habits

The feeding habits of the Amur grayling were assessed by dissecting the fish and removing its stomach. The stomach was then immediately opened, and its contents were extracted and placed on a Petri dish containing 5 mL of sterile physiological saline solution as a diluent. Stomach contents that could be observed directly were separated by type. The frequency of occurrence for each food type was recorded, and its volume was measured. Observation of the stomach contents was performed using a digital microscope (S6D, Leica, Weztlar, Germany) at a magnification of 40 × 10 to determine the types of food consumed by the fish. Contents that could not be identified based on external characteristics due to gastric digestion were verified by DNA extraction, amplification, and sequencing. Ultimately, the contents were identified by aligning the sequencing data against reference sequences in the GenBank database (Release 262.0, 15 August 2024).

2.4 Enzyme activity measurements

The activities of acid phosphatase (ACP, JL-T1094), alkaline phosphatase (AKP, JL-T0946), lysozyme (LYZ, JL-T1062), superoxide dismutase (SOD, JL-T0779), catalase (CAT, JL-T0900), glutathione (GSH, JL-T0906), as well as the content of malondialdehyde (MDA, JL-T0761) in the gut and liver, were measured using commercial test kits (Jianglai Co. Ltd., Shanghai, China) following the manufacturer’s instructions. Liver and gut samples were homogenized with cold extraction solution at a ratio of 1:9 (w:v, 1 g tissue per 9 mL ice-cold extraction buffer). Following centrifugation at 12,000 rpm for 10 min at 4 °C, the supernatant was collected (19). Optical density (OD) values were measured using the absorbance microplate reader (SpectraMax Plus 384, Molecular Devices, California, USA) at 405 nm (AKP), 405 nm (ACP), 530 nm (LZM), 560 nm (SOD), 510 nm (CAT), 412 nm (GSH), and 532/600 nm (MDA), respectively. Finally, the fresh weight of samples was used to calculate enzymatic activity according to the formula.

2.5 RNA extraction, cDNA synthesis, and real-time polymerase chain reaction

Primers were designed using the Primer Premier 6.0 software based on immune- and inflammatory-related gene sequences published in GenBank (Table 1). Primer amplification efficiency and linearity were rigorously assessed via the slope (m) and coefficient of determination (R²) of the standard curve; only primer sets exhibiting a slope between − 3.6 and − 3.1 (corresponding to 90%–110% efficiency) and an R² > 0.98 were advanced to subsequent analyses. Specificity was verified by a single, distinct melt-curve peak and the exclusive presence of a single, target-sized amplicon on agarose gel electrophoresis.

Table 1

Table 1. Primer sequences used for qRT-PCR.

Total RNA was extracted from the liver and gut samples using the TRIzol reagent (Thermo Fisher Scientific, Wilmington, DE, USA) according to the manufacturer’s protocol. RNA quality (purity and concentration) was assessed using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific). RNA degradation and contamination were evaluated by 1% agarose gel electrophoresis. First-strand complementary DNA (cDNA) was synthesized using the Prime Script™ RT reagent kit with DNA Eraser (TaKaRa, Kyoto, Japan). The messenger RNA (mRNA) expression levels of il-lβ, il-6, il-10, Tnf-α, tlr1, tlr3, myd88, NF-κB, foxo1, igM, lyz, c3, mpo, and saa1 were detected by qRT-PCR. The reaction mixture contained 0.4 μL of each forward and reverse primer, 5 μL of 2 × TB Green Premix Ex Taq II (Tli RNaseH Plus), 3 μL of sterile distilled H₂O (dH₂O), 0.2 μL of 50 × ROX Reference Dye II (Basel, Roche, Switzerland), and 1 μL of template cDNA. The cycling parameters were established at 95°C for 180 s, followed by 40 cycles of 95°C for 5 s, 60°C for 15 s, and 72°C for 30 s. qRT-PCR was performed using an ABI 7500 real-time PCR instrument (Thermo Fisher Scientific). The level of gene expression was determined using the 2^−ΔΔCT method. β-actin (F: 5′-GGACTTTGAGCAGGAGATGG-3′; R: 5′-ATGATGGAGTTGTAGGTGGTCT-3′) was used as an internal reference to measure the relative expression of the target genes. All samples were amplified in triplicate (20).

2.6 16S ribosomal DNA sequencing and gut microbiome analysis

Three gut content samples from CAG (n = 3) and gut content samples from WAG (n = 3) were collected from each experimental group. Subsequently, DNA was extracted using the E.Z.N.A. Soil DNA Kit (Omega Bio-tek Inc., Norcross, USA). The purity and integrity of nucleic acids were verified using a NanoDrop 2000 spectrophotometer (Thermo Scientific Inc., USA). The 16S rDNA was then amplified using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) on a thermocycler PCR system (GeneAmp 9700, ABI, California USA) (21). MiSeq library construction and sequencing were performed using the Illumina MiSeq PE300 platform (Illumina, San Diego, California, CA, USA) with a read length of 2 × 300 bp. Raw data underwent quality control and chimera filtering, and operational taxonomic units (OTUs) were obtained using the Uparse algorithm in Vsearch (v2.7.1) clustering. Representative OTU sequences were classified using a native Bayesian model, and species composition was analyzed at the phylum, family, and genus levels. A Venn diagram was used to identify unique and shared OTUs between the CAG and WAG groups. Alpha diversity analyses were performed using QIME software (v1.8.0) to calculate Chao1, Shannon, and Simpson indices. Based on OTUs and species abundance tables, the Bray–Curtis algorithm was used to evaluate the beta diversity of all samples, including unweighted Unifrac distance-based principal coordinate analysis (PCoA) and partial least squares discrimination analysis (PLS-DA). Functional prediction of OTUs and KEGG pathway analysis were performed using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) (v2.2.0). Biomarker features in each group were identified using linear discriminant analysis effect size (LefSe) software (v1.0.0). All bioinformatics data were analyzed using the Majorbio cloud platform (https://www.majorbio.com).

2.7 Statistical analysis

The biochemical data were calculated using Microsoft Excel and analyzed using the statistical software package IBM SPSS 22.0 (IBM Corporation, Armonk, NY, USA). All data are presented as the mean ± standard deviation (SD). Prior to statistical analysis, normality and homogeneity of variance were assessed using the Kolmogorov–Smirnov and Levene’s test, respectively. Independent t-tests were then utilized to determine the significance of differences, with p < 0.05 indicating a significant difference between the two groups. p-values from Spearman correlations were adjusted using the Benjamini–Hochberg false-discovery rate (FDR) method, and only correlations with FDR < 0.05 were considered significant.

3 Results

3.1 Authentication of feeding habits

The results showed that wild Amur grayling was dominated by zoobenthos (97.206%), identified based on morphological characteristics and genetic analysis. Among them, the most dominant diet was Perlidae (37.692%), followed by Ephemera (28.200%), Nothopsyche (14.002%), and Eubasilissa (5.652%). Therefore, the Amur grayling is a carnivorous fish that primarily feeds on zoobenthos. We hypothesize that this diet reflects a match between the fish’s trophic spectrum and locally available prey, thereby minimizing foraging costs. In addition, the abundance of zoobenthos precisely aligns with the realized nutritional niche of Amur grayling.

3.2 Analysis of immune enzyme activities

Changes in ACP, AKP, and LYZ levels in liver and gut tissue are summarized in Figure 1. The activities of ACP in the liver and gut showed no significant differences (p > 0.05) between the WAG and CAG groups. AKP activity in the gut was significantly higher in the WAG group than in the CAG group (p < 0.05), while AKP activity in the liver showed no significant difference between the two groups (p > 0.05). Similarly, LYZ activity in the liver and gut tissues of Amur grayling was significantly higher in the WAG group than in the CAG group (p < 0.05), demonstrating that the wild environment can enhance immunity in Amur grayling.

Figure 1

Figure 1. Intestinal and haptic immune-related enzymes of wild (WAG) and cultured (CAG) Amur grayling. Results are shown as mean ± SD (n = 5). Values marked with asterisks are significantly different (^*p < 0.05).

3.3 Analysis of antioxidant parameters

As shown in Figure 2, CAT activity in the liver was 9% higher in the captive group than in the wild group (p < 0.01). The gut antioxidant parameters of wild and cultured Amur grayling showed highly significant differences (p < 0.01). Specifically, CAT activity and GSH content were 64% and 66% higher in the wild group than in the cultured group, respectively, while MDA levels were lower in the wild group.

Figure 2

Figure 2. Intestinal and haptic antioxidant-related parameters of wild (WAG) and cultured (CAG) Amur grayling. Results are shown as mean ± SD (n = 5). Values marked with asterisks are significantly different (^**p < 0.01).

3.4 Expression of immune- and inflammatory-related genes in the liver and gut

In the present study, the mRNA expression levels of immune/inflammatory-related genes in the liver and intestines were measured by qRT-PCR. In the liver, the mRNA expression of C3, IgM, il-6, il-10, il-lβ, lyz, mpo, myd88, NF-κB, ssa1, tlr1, tlr3, and Tnf-α was upregulated in the WAG group, while foxo1 was significantly downregulated (p < 0.05) (Figure 3). In intestinal tissue, the mRNA levels of C3, foxo1, il-6, il-10, il-lβ, tlr1, tlr3, Tnf-α, lyz, mpo, and NF-кB increased significantly in the WAG group, whereas the expression of IgM, myd88, and ssa1 decreased significantly (p < 0.05) (Figure 4).

Figure 3

Figure 3. The mRNA expression levels of immune- and inflammatory-related genes in the liver tissue of wild (WAG) and cultured (CAG) Amur grayling. Results are shown as mean ± SD (n = 5). Values marked with asterisks are significantly different (^*p < 0.05; ^**p < 0.01).

Figure 4

Figure 4. The mRNA expression levels of immune- and inflammatory-related genes in the intestinal tissue of wild (WAG) and cultured (CAG) Amur grayling. Results are shown as mean ± SD (n = 5). Values marked with asterisks are significantly different (^*p < 0.05; ^**p < 0.01).

3.5 Overview of 16S rRNA gene sequencing and gut microbiota structure

Using high-throughput 16S rRNA gene sequencing, we analyzed the farm group (CAG; n = 3) and WAG (n = 3), yielding a total of 404,602 raw reads. The Venn diagram analysis identified 992 OTUs, with 304 OTUs unique to the CAG group and 530 OTUs unique to the WAG group (Figure 5a). Good’s coverage confirmed that the sequencing captured up to 99% of the gut microbiota in both captive and wild Amur grayling (Figure 5b). The Chao1 index indicated that wild Amur grayling had higher species richness than captive individuals (Figure 5c). Additionally, Shannon and Simpson indices showed that the gut microbiota of wild Amur grayling was more diverse, with higher Shannon and lower Simpson values compared with captive Amur grayling (Figures 5d, e). These results indicate that fish living in a natural environment exhibit higher species richness and greater species diversity. However, analyses using principal component analysis (PCA), PCoA, and nonmetric multidimensional scaling (NMDS) revealed no statistically significant differences between the gut microbiota of farmed and wild fish (Figure 6).

Figure 5

Figure 5. Venn diagram of operating taxonomic units (a) and α-diversity analysis (b–e) of the intestinal microbiota of wild and cultured Amur grayling. The number of OTUs shared between the wild (WAG) and captive (CAG) groups was 158, with 530 unique OTUs in the wild group and 304 unique OTUs in the captive group.

Figure 6

Figure 6. Comparisons of β-diversity in the gut microbiota between wild (WAG) and captive (CAG) Amur grayling. (a) Principal component analysis (PCA). (b) Principal coordinate analysis (PCoA) (c) Nonmetric multidimensional scaling (NMDS).

To assess gut microbiota differences between wild and aquaculture Amur grayling, samples from Amur Lake were compared with those from an aquaculture facility. At the phylum level, the gut microbiota of farmed Amur grayling was dominated by Pseudomonadota, followed by Fusobacteriota, Bacillota, and Actinomycetota, which together accounted for 97.3% of the community. In contrast, the wild cohort was dominated by Bacillota, followed by Pseudomonadota, Cyanobacteriota, and Actinomycetota, representing 88.7% of the community (Figure 7a). Bacillota was significantly more abundant in wild fish than in the farmed group, whereas Pseudomonadota was significantly less abundant in the wild group (p < 0.05) (Figure 7b). As shown in Figure 7c, at the family level, the farmed group was dominated by Comamonadaceae (6.10%), followed by Xanthobacteraceae (5.88%). In the wild group, Mycoplasmataceae was the most abundant, accounting for 4.2%. Compared with the farmed group, the wild group showed a significant increase in the relative abundance of Carnobacteriaceae and Mycobacteriaceae, whereas the relative abundances of Devosiaceae, Beijerinckiaceae, Xanthobacteraceae, Sphingomonadaceae, Comamonadaceae, Moraxellaceae, Burkholderiaceae, Lysobacteraceae, Pleomorphomonadaceae, Caulobacteraceae, and Rhizobiaceae were significantly decreased (p < 0.05) (Figure 7d). The most abundant genus in the gut microbiota of wild Amur grayling was Candidatus_Bacilloplasma (16.6%), followed by norank_o_Chloroplast (11.4%), Roseateles (8.2%), and Prevotella (5.9%) (Figure 7e). In captive Amur grayling, Roseateles (19.8%) was the dominant genus, followed by Bradyrhizobium (13.3%), Sphingomonas (13.1%), and Pseudomonas (11.1%). Compared with the captive group, the wild group showed a significant increase in the relative abundance of Culicoidibacter, whereas the relative abundances of Methylobacterium, Delftia, Aquabacterium, Bradyrhizobium, Sphingomonas, Brevundimonas, and Stenotrophomonas were significantly decreased (p < 0.05) (Figure 7f).

Figure 7

Figure 7. Differences in the relative abundance of intestinal bacterial flora between wild (WAG) and farmed (CAG) Amur grayling. (a) Relative abundance of intestinal bacteria at the phylum level. (b) Significant bacterial community abundance at the phylum level. Values marked with asterisks are significantly different (^*p < 0.05). (c) Relative abundance of intestinal bacteria at the family level. (d) Significant bacterial community abundance at the family level. Values marked with asterisks are significantly different (^*p < 0.05; ^**p < 0.01). (e) Relative abundance of intestinal bacteria at the genus level. (f) Significant bacterial community abundance at the genus level. Values marked with asterisks are significantly different (^*p < 0.05; ^**p < 0.01).

The changes in the presumptive functions of the intestinal microbiota of Amur grayling were examined by predicting the metagenomes using PICRUSt (Figure 8). Four functional pathways were more highly abundant in wild Amur grayling, including glycan biosynthesis and metabolism, immune disease, immune system, and translation. In aquaculture Amur grayling, 23 pathways were more highly abundant compared with wild fish, including those related to amino acid metabolism, biosynthesis of other secondary metabolites, carbohydrate metabolism, cell growth and death, and energy metabolism. Overall, these results clearly demonstrate that immune suppression in farmed Amur grayling corresponds to decreased abundances of Bacillota and other potentially beneficial microbes, highlighting the interconnectedness of diet, microbiota, and host immunity.

Figure 8

Figure 8. KEGG pathways that are enriched or depleted in the intestinal microbiota of wild (WAG) and farmed (CAG) Amur grayling.

3.6 Correlation between intestinal microbiota and immune- and inflammatory-related indices

Spearman correlation coefficient was used to test the relationship between the abundance of intestinal microbiota at the phylum level and immune- and inflammatory-related indices (Figure 9). Significant correlations were observed between intestinal and liver immune-related indicators (i.e., liver ACP, liver AKP, liver LYZ, liver il-10, liver Tnf-α, liver tlr3, intestinal il-10, intestinal Tnf-α, intestinal lyz, intestinal mpo) and the gut microbiota (i.e., Pseudomonadota, Bacillota, Chloroflexota, Acidobacteriota, Thermodesulfobacteriota, Planctomycetota, Verrucomicrobiota, Fibrobacterota) in the WAG group, as shown in the heatmap. Pseudomonadota, Chloroflexota, Thermodesulfobacteriota, Planctomycetota, Verrucomicrobiota, and Fibrobacterota were positively correlated with LYZ and Tnf-α in the liver and with il-10, Tnf-α, lyz, and mpo in the intestine (R > 0.5, p < 0.01), but negatively correlated with ACP, AKP, il-10, and tlr3 in the liver (R ≤ 0.5, p < 0.01). Bacillota was strongly positively correlated with liver ACP, liver AKP, liver il-10, and liver tlr3 (R > 0.5, p < 0.01), and negatively correlated with liver lyz, liver Tnf-α, intestinal il-10, intestinal Tnf-α, intestinal lyz, and intestinal mpo (R ≤ 0.5, p < 0.01). Spearman correlation was performed between immune parameters and phylum-level intestinal microorganisms in the CAG group. The relative abundance of Actinomycetota, Bacteroidota, Chloroflexota, Acidobacteriota, Bdellovibrionota, and Nitrospirota was significantly positively correlated with liver ACP and intestinal myd88, NF-κB, and C3 mRNA levels (R > 0.5, p < 0.01). However, their relative abundance was significantly negatively correlated with intestinal ACP, il-10, Tnf-α, and IgM, as well as with liver lyz, mpo, and ssa1 (R ≤ 0.5, p < 0.01), whereas Fusobacteriota showed the opposite correlation. The abundance of Patescibacteria, Myxococcota, unclassified_k_norank_d_Bacteria, and Entotheonellaeota was positively correlated with immune indices (AKP, liver C3, intestinal lyz) and inversely correlated with genes (liver myd88, intestinal il-6, tlr1, tlr3, foxo1, mpo, ssa1) that enhance immunity.

Figure 9

Figure 9. Correlation analyses between the abundance of the gut microbiota and gut and liver immune- and inflammation-related indices. (a) Correlation analysis between the gut microbiota at the phylum level of captive Amur grayling and immune- and inflammation-related indices. (b) Correlation analysis between the gut microbiota at the phylum level of wild Amur grayling and immune- and inflammation-related indices (^**p < 0.01). Red represents a positive correlation, while green indicates a negative correlation.

4 Discussion

As an important digestive organ, the intestine absorbs nutrients from the diet and participates in various immune responses of the body (22). Due to the different feed types, foraging habits, and habitats between wild and captive cold-water fish, it is anticipated that their gut microbiota communities will differ (23). Our main observation is the significant difference in the microbiota depending on the origin of the fish (wild or farmed) and the immune functions of wild and farmed Amur grayling, as well as exploring the interactions between the host immunity and intestinal microorganisms, which is very meaningful for maintaining fish health.

4.1 Comparative analysis of the immune system between wild and captive Amur grayling

The fish immune system is crucial for host defense and is considered an important marker for disease prevention and for maintaining fish health (24). In our trial, a series of immune-related indicators in the liver and gut tissues of wild and farmed Amur grayling were measured. Among them, significantly higher AKP and LYZ activities were found in the liver and gut tissues of wild Amur grayling. AKP and LYZ are important components of innate immunity and play a vital role in mediating host protection against bacterial invasion (25, 26). This study indicated the superior innate immune performance of wild Amur grayling.

The intestinal barrier is composed of biological, chemical, mechanical, and immune barriers, which can protect the host from pathogen invasion (27). Chemical barriers include a series of chemical substances such as complement proteins, lysozyme, and intestinal antimicrobial peptides in the outer mucus layer of intestinal epithelial cells (28, 29). In this study, the expression levels of genes that encode C3, lyz, and antibacterial enzymes such as tlr1 and tlr3 were significantly elevated in wild Amur grayling, implying superior intestinal chemical barrier function in wild Amur grayling. Inflammation is a protective biological response of the body to external injury and is mediated by several cytokines (30). In fish, the immune barrier in the intestine largely depends on their immune response (31). Lu et al. (32) have shown that a successful host immune response is generally the result of the actions of both pro- and anti-inflammatory cytokines, which clear pathogens and reduce tissue damage. The cytokines Tnf-α, il-lβ, and il-6 are considered proinflammatory cytokines (33). However, the anti-inflammatory cytokine il-10 is an immunoregulatory molecule that regulates the activity of proinflammatory cytokines (34). Currently, few studies have reported on the immunological barrier in wild and cultured Amur grayling. The present study revealed the upregulated mRNA expression trends of pro-inflammatory genes (Tnf-α, il-lβ, and il-6) and anti-inflammatory genes (il-10) in the liver and intestine of wild Amur grayling. TLRs can activate NF-κB by mediating myd88 to enhance the formation of proinflammatory factors (35). The wild individuals had higher relative mRNA expression levels of myd88 and NF-κB in the liver than the cultured group. The results of this study indicated that Amur grayling exhibit enhanced antimicrobial effects and immune function in the wild. In addition, IgM produced by B lymphocytes participates in specific immune responses and is an important indicator for measuring immune response capability (36). In this study, significantly higher mRNA expression of IgM in the liver was observed in wild Amur grayling, whereas the expression of IgM decreased significantly in the gut, implying that the farm and wild environments activate different immune-related genes to mediate various immune responses in a tissue-specific manner.

In normal metabolism, the dynamic balance of redox maintains a stable state. When fish are subjected to internal and external stress, reactive oxygen species are produced, and the balance of the antioxidant system in the body is impaired, ultimately leading to a reduction in intestinal health, immunity, and growth performance (37, 38). SOD, CAT, GSH, and MDA are important indicators of antioxidant function. SOD, CAT, and GSH can scavenge free radicals to reduce damage to the intestinal mucosa caused by oxidative stress, playing important roles in intestinal defense and repair (39, 40), while MDA content represents the degree of lipid peroxidation and indirectly reflects the extent of cellular damage (41). In the gut, the activities of antioxidant enzymes in wild Amur grayling were significantly higher, while the MDA levels in the liver and gut were lower compared with those in cultured individuals, indicating that the antioxidant capacity of wild Amur grayling is stronger than that of cultured ones.

4.2 Differences in the composition of the gut microbiota between wild and captive Amur grayling

Intestinal microbiota constitute a complex and diverse ecosystem comprising many microorganisms (42). The gut microbiome is crucial for the health and survival of fish (43). In this study, the dominant phyla in wild and captive groups were Bacillota and Pseudomonadota, respectively. This result was similar to a previous comparative study of the gut microbiota in wild and farmed Malaysian Mahseer (Tor tambroides) by Tan et al. (2019). Similarly, Pseudomonadota is also regarded as the dominant phylum in many captive fish species, such as rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) (44, 45). Moreover, it has been demonstrated that an increased abundance of Pseudomonadota is a potential diagnostic signature of metabolic and immune dysbiosis (46). Zhao et al. (47) reported that the abundance of Pseudomonadota increased after immune suppression. Therefore, we hypothesize that Pseudomonadota could inhibit the immune responses and decrease the expression of hepatic and intestinal immune-related genes in farmed Amur grayling.

Studies have shown that Bacillota could provide nutrients and energy substances to epithelial and gastrointestinal cells, which can improve mucus production, act as an anticancer and anti-inflammatory agent, and maintain intestinal barrier integrity (48). In cultured Amur grayling fish, the significantly increased abundance of Pseudomonadota and decreased abundance of Bacillota caused immune suppression, as indicated by the significantly downregulated relative expression of lyz, NF-κB, and il-10. Similar findings have been reported in cultured Japanese seabass (Lateolabrax japonicus) exposed to high dietary soybean meal levels (49). Dysbiosis of the intestinal microbiota could lead to disorders of the intestinal immune system and disease occurrence in farmed Amur grayling. In addition, Bacillota showed a greater abundance in the wild group than in the farm group. It was speculated that the gut health of wild Amur grayling was superior to that of captive Amur grayling. Ammonia is the inorganic nitrogen source for various Cyanobacteriota taxa (50). Compared with the farm group, Cyanobacteriota increased in the wild group, which may have been caused by the reproduction of Cyanobacteriota in the water and subsequent ingestion by the Amur grayling. Similar results have been reported for oysters (Crassostrea gigas) (51). Therefore, it is hypothesized that the ammonia content in wild habitats might be higher than that in aquaculture water, which could promote an increased stress response to ammonia exposure in wild Amur grayling.

The use of large amounts of organic and inorganic fertilizers, fecal waste generation, and low-quality feed conversion induces pollution in captive water (52). Delftia can degrade and transform organic and inorganic pollutants in the aquatic environment (53, 54). Thus, Delftia showed a higher relative abundance in the captive group. Studies have shown that frequent exposure of cultured fish to various pollutants leads to a decline in intestinal health and immunity (55). We hypothesized that this results in reduced immune function in cultured Amur grayling. High-carbohydrate and high-lipid diets have been widely used in aquaculture practices, but they can also cause excessive lipid accumulation in fish liver (56). In contrast, wild Amur grayling mainly consume small fish and zoobenthos with a high protein content. As observed in many animals, diet is a key factor influencing the gut microbiota (57). Thus, the gut microbiota in captive Amur grayling showed higher carbohydrate metabolism levels. In addition, increases in “carbohydrate metabolism” and “lipid metabolism” were observed. The pronounced disparity in dietary composition between farmed and wild Amur grayling profoundly shapes their respective gut microbial communities. We therefore encourage optimal wilderness training before artificial stock enhancement to adjust the gut microbial community of fish species and improve their adaptability to wild populations in reintroduction projects.

4.3 Interactions between host immunity and intestinal microorganisms in captive and wild Amur grayling

Interactions between the host and intestinal microbiota form the basis for the development of immunity (58). In our study, Actinomycetota, Bacteroidota, and Bdellovibrionota were positively correlated with the immune parameter (liver ACP) and intestinal immune-related genes (myd88, NF-κB, and C3) in captive Amur grayling. According to Jakubiec-Krzesniak et al. (59), Actinomycetota can secrete secondary metabolites that could inhibit pathogenic bacteria. Bdellovibrionota can disrupt the colonization of the Shigella genus, thereby enhancing the survival of zebrafish (Danio rerio) (60). Bacteroidota can improve the decomposition of nutrients and digestibility of the host, and their abundance is closely related to maintaining the intestinal environmental balance in animals (61). Therefore, the decreased abundances of Actinomycetota, Bdellovibrionota, and Bacteroidota in cultivated Amur grayling allowed undigested nutrients and harmful substances to enter into liver through the hepatic portal vein, thereby inducing a liver immune response. In addition, Actinomycetota, Bdellovibrionota, and Bacteroidota were considered important factors contributing to the increased survival rate of Amur grayling in the wild environment after artificial enhancement and release. Fusobacteriota have protective effects on fish and can produce butyrate and vitamin B12, which are involved in the immune-regulatory processes in the body (62). In our study, Fusobacteria were positively associated with intestinal immune response cytokine IgM, and both the relative abundance of Fusobacteria and the expression level of IgM increased in the captive group. It has been demonstrated that Fusobacteria are a gut microbiota biomarker closely related to the immune response in captive Amur grayling.

The gut microbiota regulates immunity via the gut axis. Planctomycetota influence complex chemical metabolism. In addition, Verrucomicrobiota benefit fish gut health by enhancing immune responses, regulating microbial communities, and promoting mucosal repair (63). Fibrobacterota are small but important phyla, mainly reported as cellulose-degrading bacteria (64). In addition, Thermodesulfobacteriota, Planctomycetota, Verrucomicrobiota, and Fibrobacterota were positively associated with inflammatory factors (hepatic LYZ and Tnf-α, intestinal il-10, Tnf-α, lyz, and mpo) but negatively correlated with liver immune- and inflammatory-related parameters (ACP, AKP, il-10, and tlr3) in the intestine tissue of wild Amur grayling. Bacillota showed the opposite correlation. The results indicated that Amur grayling immune responses can be linked to the abundance levels of Bacillota, Planctomycetota, Verrucomicrobiota, and Fibrobacterota. Based on the above studies, we postulate that intestinal microbes in Amur grayling may modulate host immunity by enhancing the expression of immune-related genes (il-10, Tnf-α, lyz, and mpo). Further research is required to understand how host–microbiome interactions coevolve and adapt, as well as the specific roles of certain microorganisms in nutrient processing and immune regulation. Studying the gut microbiomes of wild fish populations is important for understanding their natural microbial communities and ecological functions, in addition to research focused on aquaculture or laboratory fish.

4.4 Limitations

Firstly, we acknowledge that our experimental groups comprised n = 15 fish per treatment, which limits the statistical power to detect subtle microbiota shifts. Secondly, all farmed samples were collected from the Bohai Cold Water Fish Experimental Station of the Heilongjiang Institute of Fisheries Research; thus, the findings may not generalize to Amur grayling in other geographic regions or rearing systems. Thirdly, all wild samples were captured in the Huma River, from the upper Amur River, in autumn. The diet of Amur grayling varies with the season; thus, the results of comparisons of gut microbiota between wild and farmed Amur grayling may differ across seasons.

4.5 Future directions

Firstly, we outline plans for repeated sampling from the same individuals across an entire production cycle to capture temporal trajectories of the gut microbiota. Secondly, we propose controlled feeding experiments with candidate probiotic strains (e.g., Bacillota isolated from wild conspecifics) to test whether targeted microbial interventions can restore immune-relevant taxa in farmed fish.

5 Conclusion

In conclusion, this study revealed the differences in the composition of the intestinal microbiota and immune response between wild origin and aquacultured Amur grayling, while the liver–gut–microbiota axis may play an essential role in the underlying mechanisms. Moreover, Actinomycetota, Bdellovibrionota, Bacteroidota, and Fusobacteriota might provide important functions for the increased survival rate of Amur grayling in the wild environment after artificial enhancement and release. Future research could focus on isolating those bacteria that may be used as potential probiotics. The results of this study provide a promising direction for the healthy aquaculture and species reintroduction programs of Amur grayling and offer a theoretical basis for its conservation.

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 below: https://www.ncbi.nlm.nih.gov/, PRJNA1309249.

Ethics statement

The animal study was approved by Laboratory Animal Ethics Committee of the Research Institute of Fisheries of the Heilongjiang River. The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

CZ: Conceptualization, Methodology, Software, Data curation, Formal analysis, Writing – original draft. ZW: Writing – original draft, Validation, Software. LB: Writing – original draft, Data curation, Visualization. HH: Writing – original draft, Data curation, Software. BM: Supervision, Writing – review & editing, Funding acquisition, Resources, Project administration, Methodology, Conceptualization.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. The study was supported by the 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,” and Central Public-interest Scientific Institution Basal Research Fund (No. 2023TD07).

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.

Generative AI statement

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

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2025.1654437/full#supplementary-material

References

1. Liu L, Luo Y, Liang X, Ma B, and Song D. Occurrence of Amur grayling (Thymallus grubii grubii Dybowski, 1869) in the Amur River. J Appl Ichthyol. (2013) 29:666–7. doi: 10.1111/jai.12138

Crossref Full Text | Google Scholar

2. Wang S, Zheng G, and Wang Q. China red data book of endangered animals. Beijing, China: Science Press (1998) p. 204–6.

Google Scholar

3. Willoughby JR, Fernandez NB, Lamb MC, Ivy JA, Lacy RC, and Dewoody JA. The impacts of inbreeding, drift and selection on genetic diversity in captive breeding populations. Mol Ecol. (2015) 24:98–110. doi: 10.1111/mec.13020

PubMed Abstract | Crossref Full Text | Google Scholar

4. Wiredu Ocansey DK, Hang S, Yuan X, Qian H, Zhou M, Valerie Olovo C, et al. The diagnostic and prognostic potential of gut bacteria in inflammatory bowel disease. Gut Microbes. (2023) 15:2176118. doi: 10.1080/19490976.2023.2176118

PubMed Abstract | Crossref Full Text | Google Scholar

5. Zhang BY, Yang HL, Cai GH, Nie QJ, and Sun YZ. The interactions between the host immunity and intestinal microorganisms in fish. Appl Microbiol Biotechnol. (2024) 108:30. doi: 10.1007/s00253-023-12934-1

PubMed Abstract | Crossref Full Text | Google Scholar

6. Sun H, Chen F, Zheng W, Huang Y, Peng H, Hao H, et al. Impact of captivity and natural habitats on gut microbiome in Epinephelus akaara across seasons. BMC Microbiol. (2024) 24:239–57. doi: 10.1186/s12866-024-03398-y

PubMed Abstract | Crossref Full Text | Google Scholar

7. Kanika NH, Liaqat N, Chen H, Ke J, Lu G, Wang J, et al. Fish gut microbiome and its application in aquaculture and biological conservation. Front Microbiol. (2025) 15:1521048. doi: 10.3389/fmicb.2024.1521048

PubMed Abstract | Crossref Full Text | Google Scholar

8. Dallas JW and Warne RW. Captivity and animal microbiomes: potential roles of microbiota for influencing animal conservation. Microb Ecol. (2023) 85:820–38. doi: 10.1007/s00248-022-01991-0

PubMed Abstract | Crossref Full Text | Google Scholar

9. Ley RE, Turnbaugh PJ, Klein S, and Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. (2006) 444:1022–3. doi: 10.1038/4441022a

PubMed Abstract | Crossref Full Text | Google Scholar

10. Schuijt TJ, Van Der Poll T, De Vos WM, and Wiersinga WJ. The intestinal microbiota and host immune interactions in the critically ill. Trends Microbiol. (2013) 21:221–9. doi: 10.1016/j.tim.2013.02.001

PubMed Abstract | Crossref Full Text | Google Scholar

11. Bostick JW and Zhou L. Innate lymphoid cells in intestinal immunity and inflammation. Cell Mol Life Sci. (2016) 73:237–52. doi: 10.1007/s00018-015-2055-3

PubMed Abstract | Crossref Full Text | Google Scholar

12. Hong Y, Huang Y, Yan G, Yin H, and Huang Z. DNA damage, immunotoxicity, and neurotoxicity induced by deltamethrin on the freshwater crayfish, Procambarus clarkii. Environ Toxicol. (2021) 36:16–23. doi: 10.1002/tox.23006

PubMed Abstract | Crossref Full Text | Google Scholar

13. Groot P, Scheithauer T, Bakker GJ, Prodan A, Levin E, and Khan MT. Donor metabolic characteristics drive effects of faecal microbiota transplantation on recipient insulin sensitivity, energy expenditure and intestinal transit time. Gut. (2020) 69:502–12. doi: 10.1136/gutjnl-2019-318320

PubMed Abstract | Crossref Full Text | Google Scholar

14. Kootte RS, Levin E, Salojärvi J, Smits LP, Hartstra AV, and Udayappan SD. Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell Metab. (2017) 26:611–9. doi: 10.1016/j.cmet.2017.09.008

PubMed Abstract | Crossref Full Text | Google Scholar

15. Bledsoe JW, Pietrak MR, Burr GS, Peterson BC, and Small BC. Functional feeds marginally alter immune expression and microbiota of Atlantic salmon (Salmo salar) gut, gill, and skin mucosa though evidence of tissue-specific signatures and host-microbe coadaptation remain. Anim Microbiome. (2022) 4:20. doi: 10.1186/s42523-022-00173-0

PubMed Abstract | Crossref Full Text | Google Scholar

16. Yang H, Yuan Q, Rahman MM, Lv W, Huang W, Hu W, et al. Comparative studies on the intestinal health of wild and cultured ricefield eel (Monopterus albus). Front Immunol. (2024) 15:1411544. doi: 10.3389/fimmu.2024.1411544

PubMed Abstract | Crossref Full Text | Google Scholar

17. Tan CK, Natrah I, Suyub IB, Edward MJ, Kaman N, and Samsudin AA. Comparative study of gut microbiota in wild and captive Malaysian Mahseer (Tor tambroides). Microbiol Open. (2019) 8:e00734. doi: 10.1002/mbo3.734

PubMed Abstract | Crossref Full Text | Google Scholar

18. Wang J, Li S, Sun Z, Lu C, Zhao R, Liu T, et al. Comparative study of immune responses and intestinal microbiota in the gut-liver axis between wild and farmed pike perch (Sander Lucioperca). Front Immunol. (2024) 15:1473686. doi: 10.3389/fimmu.2024.1473686

PubMed Abstract | Crossref Full Text | Google Scholar

19. Zhang W, Tan B, Deng J, Dong X, Yang Q, Chi S, et al. Effects of high level of fermented soybean meal substitution for fish meal on the growth, enzyme activity, intestinal structure protein and immune-related gene expression and intestinal flora in juvenile pearl gentian grouper. Aquaculture Nutr. (2021) 27:1433–47. doi: 10.1111/anu.13281

Crossref Full Text | Google Scholar

20. Li YT, Wang J, Xing HJ, and Bao J. Selenium mitigates ammonia-induced neurotoxicity by suppressing apoptosis, immune imbalance, and gut microbiota-driven metabolic disturbance in fattening pigs. Biol Trace Elem Res. (2023) 201:3341–55. doi: 10.1007/s12011-022-03434-w

PubMed Abstract | Crossref Full Text | Google Scholar

21. Liu C, Zhao D, Ma W, Guo Y, Wang A, Wang Q, et al. Denitrifying sulfide removal process on high-salinity wastewaters in the presence of Halomonas sp. Appl Microbiol Biotechnol. (2016) 100:1421–6. doi: 10.1007/s00253-015-7039-6

PubMed Abstract | Crossref Full Text | Google Scholar

22. Yu MH, Li XS, Wang J, Long SM, Song K, Wang L, et al. Substituting fish meal with a bacteria protein (Methylococcus capsulatus, Bath) grown on natural gas: effects on growth non-specific immunity and gut health of spotted seabass (Lateolabrax maculatus). Anim. Feed Sci Technol. (2023) 296:115556. doi: 10.1016/j.anifeedsci.2022.115556

Crossref Full Text | Google Scholar

23. Pan YZ, Li ZC, Zhou JS, Wang QL, Xu HF, and Mou ZB. Cupriavidus in the intestinal microbiota of Tibet endemic fish Glyptosternum maculatum can help it adapt to habitat of the Qinghai Tibet Plateau. BMC Vet Res. (2021) 17:1–9. doi: 10.1186/s12917-021-03092-5

PubMed Abstract | Crossref Full Text | Google Scholar

24. Tort L. Stress and immune modulation in fish. Dev Comp Immunol. (2011) 35:1366–75. doi: 10.1016/j.dci.2011.07.002

PubMed Abstract | Crossref Full Text | Google Scholar

25. Li L, Cardoso JCR, Félix RC, Mateus AP, Canário AVM, and Power DM. Fish lysozyme gene family evolution and divergent function in early development. Dev Comp Immunol. (2021) 114:103772. doi: 10.1016/j.dci.2020.103772

PubMed Abstract | Crossref Full Text | Google Scholar

26. Li H, Di GL, Zhang Y, Liang JP, Wang XF, Xu ZS, et al. MiR-217 through SIRT1 regulates the immunotoxicity of cadmium in Cyprinus carpio. Comp Biochem Physiol Toxicol Pharmacol CBP. (2021) 248:123–109086. doi: 10.1016/j.cbpc.2021.109086

PubMed Abstract | Crossref Full Text | Google Scholar

27. Wu XQ, Chen XM, Pan YY, Sun C, Tian JX, Qian AD, et al. Changes of intestinal barrier in the process of intestinal inflammation induced by Aeromonas hydrophila in snakehead (Channa argus). Fish Shellfish Immunol. (2024) 152:109775. doi: 10.1016/j.fsi.2024.109775

PubMed Abstract | Crossref Full Text | Google Scholar

28. Rauta PR, Nayak B, and Das S. Immune system and immune responses in fish and their role in comparative immunity study: a model for higher organisms. Immunol Lett. (2012) 148:23–33. doi: 10.1016/j.imlet.2012.08.003

PubMed Abstract | Crossref Full Text | Google Scholar

29. Nayak SK. Role of gastrointestinal microbiota in fish. Aquac Res. (2010) 41:1553–73. doi: 10.1111/j.1365-2109.2010.02546.x

Crossref Full Text | Google Scholar

30. Nathan C. Points of control in inflammation. Nature. (2002) 420:846–52. doi: 10.1038/nature01320

PubMed Abstract | Crossref Full Text | Google Scholar

31. Niklasson L, Sundh H, Fridell F, Taranger GL, and Sundell K. Disturbance of the intestinal mucosal immune system of farmed Atlantic salmon (Salmo salar), in response to long-term hypoxic conditions. Fish Shellfish Immunol. (2011) 31:1072–80. doi: 10.1016/j.fsi.2011.09.011

PubMed Abstract | Crossref Full Text | Google Scholar

32. Lu M, Su M, Liu N, and Zhang J. Effects of environmental salinity on the immune response of the coastal fish Scatophagus argus during bacterial infection. Fish Shellfish Immunol. (2022) 124:401–10. doi: 10.1016/j.fsi.2022.04.029

PubMed Abstract | Crossref Full Text | Google Scholar

33. Dinarello C. Impact of basic research on tomorrow’s medicine. Chest. (2000) 118:503–8. doi: 10.1378/chest.118.2.503

PubMed Abstract | Crossref Full Text | Google Scholar

34. Opal SM and DePalo VA. Anti-inflammatory cytokines. Chest. (2000) 117:1162–72. doi: 10.1378/chest.117.4.1162

PubMed Abstract | Crossref Full Text | Google Scholar

35. Gu Z, Jia R, He Q, Cao L, Du J, Feng W, et al. Alteration of lipid metabolism, autophagy, apoptosis and immune response in the liver of common carp (Cyprinus carpio) after long-term exposure to bisphenol A. Ecotoxicol Environ Saf. (2021) 211:111923. doi: 10.1016/j.ecoenv.2021.111923

PubMed Abstract | Crossref Full Text | Google Scholar

36. Yu Z, Zheng YG, Du HL, Li HJ, and Wu LF. Bioflocs protects copper-induced inflammatory response and oxidative stress in Rhynchocypris lagowski Dybowski through inhibiting NF-κB and Nrf2 signaling pathways. Fish Shellfish Immunol. (2020) 98:466–76. doi: 10.1016/j.fsi.2020.01.048

PubMed Abstract | Crossref Full Text | Google Scholar

37. Hoseinifar SH, Yousefi S, Van Doan H, Ashouri G, Gioacchini G, Maradonna F, et al. Oxidative stress and antioxidant defense in fish: the implications of probiotic, prebiotic, and synbiotics. Rev Fisheries Sci Aquaculture. (2020) 29:198–217. doi: 10.1080/23308249.2020.1795616

Crossref Full Text | Google Scholar

38. Kakade A, Salama ES, Pengya F, Liu P, and Li X. Long-term exposure of high concentration heavy metals induced toxicity, fatality, and gut microbial dysbiosis in common carp, Cyprinus carpio. Environ pollut (Barking Essex: 1987). (2020) 266:115293. doi: 10.1016/j.envpol.2020.115293

PubMed Abstract | Crossref Full Text | Google Scholar

39. Tunç A, Erdoğan O, Vural O, and Aksakal E. Impact of acute and long-term hypoxia and hyperoxia on antioxidant metabolism and gene expression in juvenile rainbow trout (Oncorhynchus mykiss). Aquaculture Res. (2025) 2025:6628284.

Google Scholar

40. Joy S, Alikunju AP, Jose J, Sudha HSH, Parambath PM, Puthiyedathu ST, et al. Oxidative stress and antioxidant defense responses of Etroplus suratensis to acute temperature fluctuations. J Therm Biol. (2017) 70:20–6. doi: 10.1016/j.jtherbio.2017.10.010

PubMed Abstract | Crossref Full Text | Google Scholar

41. Zhou X, Yang X, Liu X, Jiang L, and Jiang Y. Hexavalent chromium (Cr6+) induces oxidative stress, inflammatory response, apoptosis, and DNA damage in the liver of largemouth bass by inhibiting the Nrf2-Keap1 signal pathway. Fish Physiol Biochem. (2025) 51:53. doi: 10.1007/s10695-025-01469-z

PubMed Abstract | Crossref Full Text | Google Scholar

42. Arjomand Fard N, Bording-Jorgensen M, and Wine E. A potential role for gut microbes in mediating effects of omega-3 fatty acids in inflammatory bowel diseases: a comprehensive review. Curr Microbiol. (2023) 80:363. doi: 10.1007/s00284-023-03482-y

PubMed Abstract | Crossref Full Text | Google Scholar

43. Ruiz A, Gisbert E, and Andree KB. Impact of the diet in the gut microbiota after an inter-species microbial transplantation in fish. Sci Rep. (2024) 14:4007. doi: 10.1038/s41598-024-54519-6

PubMed Abstract | Crossref Full Text | Google Scholar

44. Li L, Liu Z, Quan J, Sun J, Lu J, and Zhao G. Dietary nano-selenium alleviates heat stress-induced intestinal damage through affecting intestinal antioxidant capacity and microbiota in rainbow trout (Oncorhynchus mykiss). Fish Shellfish Immun. (2023) 133:108537. doi: 10.1016/j.fsi.2023.108537

PubMed Abstract | Crossref Full Text | Google Scholar

45. Gajardo K, Rodiles A, Kortner T, Krogdahl Å, Bakke AM, Merrifield D, et al. A high-resolution map of the gut microbiota in Atlantic salmon (Salmo salar): A basis for comparative gut microbial research. Sci Rep. (2016) 6:30893. doi: 10.1038/srep30893

PubMed Abstract | Crossref Full Text | Google Scholar

46. Litvak Y, Byndloss MX, Tsolis RM, and Baumler AJ. Dysbiotic Proteobacteria expansion: A microbial signature of epithelial dysfunction. Curr Opin Microbiol. (2017) 39:1–6. doi: 10.1016/j.mib.2017.07.003

PubMed Abstract | Crossref Full Text | Google Scholar

47. Zhao Y, Liu H, Wang Q, Li BJ, Zhang HX, and Pi YR. The effects of benzo[a]pyrene on the composition of gut microbiota and the gut health of the juvenile sea cucumber Apostichopus japonicus Selenka. Fish Shellfish Immun. (2019) 93:369–79. doi: 10.1016/j.fsi.2019.07.073

PubMed Abstract | Crossref Full Text | Google Scholar

48. Collinder E, Cardona ME, Berge GN, Norin E, Stern S, and Midtvedt T. Influence of zinc bacitracin and Bacillus licheniformis on microbial intestinal functions in weaned piglets. Vet Res Commun. (2003) 27:513–26. doi: 10.1023/A:1026043623194

PubMed Abstract | Crossref Full Text | Google Scholar

49. Liu ZX, Zhang BY, Yuan ZH, Ye JD, and Sun YZ. Preventive and reparative functions of host-associated probiotics against soybean meal induced growth, immune suppression and gut injury in Japanese seabass (Lateolabrax japonicus). Fish Shellfish Immun. (2022) 128:651–63. doi: 10.1016/j.fsi.2022.08.034

PubMed Abstract | Crossref Full Text | Google Scholar

50. Boussiba S and Gibson J. Ammonia translocation in cyanobacteria. FEMS Microbiol Lett. (1991) 88:1–14. doi: 10.1111/j.1574-6968.1991.tb04953.x

Crossref Full Text | Google Scholar

51. Avila-Poveda OH, Torres-Arino A, Girón-Cruz DA, and Cuevas-Aguirre A. Evidence for accumulation of Synechococcus elongatus (Cyanobacteria: Cyanophyceae) in the tissues of the oyster Crassostrea gigas (Mollusca: Bivalvia). Tissue Cell. (2014) 46:379–87. doi: 10.1016/j.tice.2014.07.001

PubMed Abstract | Crossref Full Text | Google Scholar

52. Tacon AGJ, Phillips MJ, and Barg UC. Aquaculture feeds and the environment: The Asian experience. Water Sci Technol. (1995) 31:41–59. doi: 10.2166/wst.1995.0363

Crossref Full Text | Google Scholar

53. Liu Y, Tie B, Li Y, Lei M, Wei X, Liu X, et al. Inoculation of soil with cadmium-resistant bacterium Delftia sp. B9 reduces cadmium accumulation in rice (Oryza sativa L.) grains. Ecotoxicol Environ Saf. (2018) 163:223–9. doi: 10.1016/j.ecoenv.2018.07.081

PubMed Abstract | Crossref Full Text | Google Scholar

54. Wu W, Huang H, Ling Z, Yu Z, Jiang Y, Liu P, et al. Genome sequencing reveals mechanisms for heavy metal resistance and polycyclic aromatic hydrocarbon degradation in Delftia lacustris strain LZ-C. Ecotoxicology. (2016) 25:234–47. doi: 10.1007/s10646-015-1583-9

PubMed Abstract | Crossref Full Text | Google Scholar

55. Zhang J, Wang Y, Liu J, Xu W, Yin Z, Liu Y, et al. Effects of fecal bacteria on growth, digestive capacity, antioxidant capacity, intestinal health of large yellow croaker (Larimichthys crocea) larvae. Aquaculture. (2023) 562:738796. doi: 10.1016/j.aquaculture.2022.738796

Crossref Full Text | Google Scholar

56. Xie D, Yang L, Yu R, Chen F, Lu R, Qin C, et al. Effects of dietary carbohydrate and lipid levels on growth and hepatic lipid deposition of juvenile tilapia, Oreochromis niloticus. Aquaculture. (2017) 479:696–703. doi: 10.1016/j.aquaculture.2017.07.013

Crossref Full Text | Google Scholar

57. Hills RD Jr, Pontefract BA, Mishcon HR, Black CA, Sutton SC, and Theberge CR. Gut microbiome: profound implications for diet and disease. Komp Nutr Diet. (2022) 11:1–16. doi: 10.1159/000523712

PubMed Abstract | Crossref Full Text | Google Scholar

58. Ruff WE, Greiling TM, and Kriegel MA. Host-microbiota interactions in immune-mediated diseases. Nat Rev Microbiol. (2020) 9:521–38. doi: 10.1038/s41579-020-0367-2

PubMed Abstract | Crossref Full Text | Google Scholar

59. Jakubiec-Krzesniak K, Rajnisz-Mateusiak A, Guspiel A, Ziemska J, and Solecka J. Secondary metabolites of actinomycetes and their antibacterial, antifungal and antiviral properties. Pol J Microbiol. (2018) 67:259–72. doi: 10.21307/pjm-2018-048

PubMed Abstract | Crossref Full Text | Google Scholar

60. Willis AR, Moore C, Mazon-Moya M, Krokowski S, Lambert C, Till R, et al. Injections of predatory bacteria work alongside host immune cells to treat Shigella infection in zebrafish larvae. Curr Biol. (2016) 26:3343–51. doi: 10.1016/j.cub.2016.09.067

PubMed Abstract | Crossref Full Text | Google Scholar

61. Ley RE, Turnbaugh PJ, Klein S, and Gordon JI. Human gut microbes associated with obesity. Nature. (2006) 444:1022–3. doi: 10.1038/4441022a

PubMed Abstract | Crossref Full Text | Google Scholar

62. Elsheshtawy A, Clokie BGJ, Albalat A, Beveridge A, Hamza A, Ibrahim A, et al. Characterization of external mucosal microbiomes of nile tilapia and grey mullet co-cultured in semi-intensive pond systems. Front Microbiol. (2021) 12:773860. doi: 10.3389/fmicb.2021.773860

PubMed Abstract | Crossref Full Text | Google Scholar

63. Wu H, Gao J, Xie M, Wu J, Song R, Yuan X, et al. Chronic exposure to deltamethrin disrupts intestinal health and intestinal microbiota in juvenile crucian carp. Ecotoxicol Environ Saf. (2022) 241:113732. doi: 10.1016/j.ecoenv.2022.113732

PubMed Abstract | Crossref Full Text | Google Scholar

64. Ransom-Jones E, Jones DL, McCarthy AJ, and McDonald JE. The Fibrobacteres: an important phylum of cellulose-degrading bacteria. Microbial Ecol. (2012) 63:267–81. doi: 10.1007/s00248-011-9998-1

PubMed Abstract | Crossref Full Text | Google Scholar