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Frontiers in Marine Science ·

Volume 13 - 2026 | https://doi.org/10.3389/fmars.2026.1950219

Optimal dietary glycerol monolaurate supplementation improves growth performance, antioxidant capacity, immune responses and intestinal microbiota in juvenile largemouth bass

  • Xuehe Li1,2,3*corresponding author
  • Huixuan Xu1
  • Jinjiang Wang1
  • Maozi Lin1
  • Qihui Yang2,3*corresponding author
  1. 1Fujian Provincial Key Lab of Coastal Basin Environment, Fujian Polytechnic Normal University, Fuqing, Fujian, China
  2. 2College of Fisheries, Guangdong Ocean University, Zhanjiang, Guangdong, China
  3. 3Aquatic Animals Precision Nutrition and High Efficiency Feed Engineering Research Center of Guangdong Province, Guangdong Ocean University, Zhanjiang, Guangdong, China
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Abstract

Plant-derived functional additives have gained increasing attention as sustainable alternatives in aquafeed. This study aims to investigate the effects of dietary monolaurin on productive performance, innate immune indicators, antioxidative effects, and gut flora in largemouth bass (Micropterus salmoides). Fish were fed diets containing 0, 500, 800, 1100, and 1400 mg/kg GML for 56 days, with three replicates per treatment. The results showed that GML supplementation significantly improved growth performance. Final body weight was higher in the 800 and 1100 mg/kg groups, while weight gain rate and specific growth rate peaked at 800 mg/kg. Whole-body crude lipid content decreased in the 500 and 800 mg/kg groups, whereas crude protein content increased across all GML-supplemented groups. GML also enhanced antioxidant capacity by increasing total antioxidant capacity and catalase and superoxide dismutase activities while reducing malondialdehyde levels. Serum acid phosphatase and alkaline phosphatase activities peaked in the 800 and 1100 mg/kg groups. The expression levels of il6 and tnfa were significantly downregulated in the 800 and 1100 mg/kg groups, while those of tgfb1a and il22 were significantly upregulated. Intestinal microbiota analysis revealed that GML reshaped the gut microbial community. The relative abundances of Aeromonas and Pseudomonas decreased at 800–1400 mg/kg, whereas those of Cetobacterium and Bacteroides increased at 800 mg/kg and 1100 mg/kg. Regression analysis based on final body weight estimated the optimal dietary GML level at 750 mg/kg. These findings indicate that appropriate dietary GML supplementation can promote growth while improving antioxidant status, selected innate immune responses, and intestinal microbial balance in largemouth bass. Thus, GML may serve as a promising plant-derived functional feed additive in largemouth bass aquaculture.

Keywords

1 Introduction

Largemouth bass (Micropterus salmoides) is one of most economically significant freshwater cultured fish in China. According to the China Fishery Statistical Yearbook, China produced approximately 888, 030 tons of freshwater-cultured perch in 2023. This species ranks seventh among the major freshwater cultured fish in China (China Fishery Statistical Yearbook, 2024). Environmental stressors, including deteriorating water quality, temperature fluctuations, and hypoxia, can trigger excessive reactive oxygen species accumulation in largemouth bass tissues, leading to oxidative stress, immune suppression, and a higher incidence of infectious diseases (Ma et al., 2025; Song et al., 2023; Gu et al., 2023). In response to increasing concerns over antibiotic resistance and food safety, natural plant-derived functional feed additives have attracted growing attention as sustainable, environmentally friendly strategies for improving fish growth performance, antioxidant capacity, intestinal health, and other factors (Hoseinifar et al., 2024; Onomu and Okuthe, 2024). Nevertheless, while numerous studies have validated the efficacy of various phytogenic additives in improving growth, antioxidant capacity, and intestinal health in aquaculture species, systematic investigations targeting freshwater carnivorous fish—particularly largemouth bass—remain scarce. Importantly, digestive physiology and intestinal microbial communities in fish are strongly influenced by host species, habitat, and feeding habit, with substantial differences reported among carnivorous, omnivorous, freshwater, and marine fishes (Jiao et al., 2023; Sullam et al., 2012; Ofek et al., 2021). Therefore, physiological and microbial responses to functional lipid additives observed in other fish species may not be directly extrapolated to largemouth bass. The specific responses of this species to medium-chain fatty acid derivatives, have not been previously examined, representing a critical knowledge gap in the development of species-specific nutritional strategies.

Glycerol monolaurate (GML), also known as monolaurin, is a fatty acid monoester formed by the esterification of lauric acid and glycerol. Lauric acid is widely present in natural lipid sources, including coconut oil, palm kernel oil, and milk fat; therefore, GML has a favorable safety profile and considerable potential for use as a functional feed additive (Ullah et al., 2024; M et al., 2024). Compared with long-chain fatty acid derivatives, it can be absorbed and utilized relatively rapidly and exhibits a range of biological activities. Previous studies have shown that GML possesses antibacterial, antiviral, anti-inflammatory, and immunomodulatory properties and may exert beneficial effects by modulating host nutrient metabolism and the intestinal microbial ecosystem (Kong et al., 2021, Kong et al., 2022). Owing to these distinctive physicochemical and biological characteristics, GML represents a promising functional additive for maintaining metabolic homeostasis and intestinal health in carnivorous fish fed high-fat, high-protein diets.

Unlike conventional antibiotics, GML and other medium-chain monoglycerides have favorable safety profiles and promising potential as feed additives receiving increasing attention as antibiotic alternatives in animal nutrition (Jackman et al., 2022). Previous studies have shown that dietary GML enhances growth performance, antioxidant capacity, innate immune indicators, and gut microbial balance in several cultured aquatic species, including golden pompano (Lin et al., 2022), large yellow croaker (Tang et al., 2023a), hybrid grouper (Li et al., 2022a), black sea bream (Ullah et al., 2024), and common carp (Xu et al., 2024). However, the responses to dietary GML are not always consistent across aquatic species. Studies in white shrimp (Litopenaeus vannamei), black sea bream (Acanthopagrus schlegelii), and hybrid sturgeon have reported limited or non-significant effects on certain growth performance and physiological parameters, while dose and endpoint dependent responses have also been observed (Wang et al., 2020; Xu et al., 2026). And its effects on freshwater carnivorous fish and underlying mechanisms remain poorly understood, as most studies have focused on marine fish and crustaceans. Based on the biological activities of GML and the unique physiological characteristics of largemouth bass, we proposed the following hypothesis. Appropriate dietary GML supplementation would enhance growth performance and antioxidant capacity in juvenile largemouth bass. It would also modulate immune-related indicators, and restructure the intestinal microbiota. Accordingly, this study evaluated the effects of different dietary GML levels on growth performance, body composition, antioxidant capacity, innate immune-related indicators, and intestinal microbial composition. In addition, an appropriate dietary GML supplementation level for juvenile largemouth bass was estimated.

2 Materials and methods

2.1 Experimental design and feed preparation

The basal diet for the control group was formulated with fish, chicken, peanut, and soybean meals as primary protein sources, while fish oil, soybean oil, and soybean lecithin served as lipid sources (Table 1). It was denoted as FM. Furthermore, GML (500, 800, 1100, and 1400 mg/kg; purity > 95%; Aladdin Reagent, item no. M158544) was added to the basal diet to prepare four experimental diets with equal nitrogen and lipid contents, designated as G1, G2, G3, and G4. First, all raw materials were ground, sieved through a 60-mesh sieve, and evenly mixed in a V-type mixer (M-256, South China University of Technology, Guangzhou, China). Lipid sources, choline chloride, and ultra-pure water (30–40%) were then added and mixed again using a Hobart-type mixer. Finally, the feed was extruded into 2.5-mm pellets using a twin-screw extruder (LG-108, Changzhou Fremar Drying Technology Co., Ltd., Changzhou, China). The pellets were air-dried in a cool place, vacuum-packed in sealed bags, and stored at a low temperature.

Table 1. Ingredients and chemical compositions of experimental diets (% DM basis).

IngredientsGroup
FMG1G2G3G4
Fish meal45.0045.0045.0045.0045.00
Chicken powder15.0015.0015.0015.0015.00
Peanut meal10.0010.0010.0010.0010.00
Soybean meal8.008.008.008.008.00
Wheat flour10.0010.0010.0010.0010.00
Fish oil1.501.501.501.501.50
Soybean oil1.501.501.501.501.50
Lecithin1.001.001.001.001.00
Premix11.001.001.001.001.00
Ca(H2PO4)21.001.001.001.001.00
Choline chloride0.500.500.500.500.50
Vitamin C0.050.050.050.050.05
Microcrystalline cellulose5.455.405.375.345.31
GML0.000.050.080.110.14
Total100.00100.00100.00100.00100.00
Nutrient levels
Crude protein47.6047.6047.6047.6047.60
Crude lipid10.7710.7710.7710.7710.77

Premix: vitamin A 675–000 IU, vitamin D3 180–000 IU, vitamin E 6000mg, vitamin K3 1 200mg, vitamin B1 900mg, vitamin B2 1 350mg, vitamin B6 1 050mg and vitamin B12 7.5mg, calcium pantothenate 4–500 mg, nicotinic acid 6 750mg, folic acid 375mg, biotin 15mg, vitamin C phosphate 42 860mg, inositol 10–000 mg, FeSO4·H2O 64–286 mg, ZnSO4·H2O 26 283mg, MnSO4·H2O 19–688 mg, Ca(IO3) 2·H2O 128.6 mg, CoCl2·6H2O 323 mg, CuSO4·5H2O 2–357 mg, Na2SeO3 87.6 mg. The same as below.

2.2 Experimental fish and feeding management

All juvenile largemouth bass used were purchased from Hanlong Fisheries Co., Ltd. (Fuqing City, Fujian Province, China) and acclimated in a breeding tank (6 m × 3 m × 1 m, L × W × H) for 2 weeks after transportation. After acclimation, fish showing obvious injuries, deformities, signs of disease, or markedly abnormal body weights were excluded. Fifty fish were then randomly selected and weighed to estimate the average initial body weight and establish a predefined body-weight range. Subsequently, all the fish were thoroughly mixed in the storage tank. Using a net, they were collected in batches randomly, weighed, and then randomly distributed to the experimental tanks (30 fish per tank). Treatment labels were assigned to the tanks only after fish allocation had been completed, in order to minimize potential bias associated with the initial distribution of fish. Each group was replicated in three tanks (70 cm × 50 cm × 45 cm, L × W × H), resulting in 15 tanks for an 8-week feeding experiment. Each tank was considered an experimental unit (n = 3). All animal experiments were conducted in accordance with the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines. The experimental protocol was reviewed and approved by the Ethics Committee of Fujian Polytechnic Normal University (Fuzhou, China).

All breeding was conducted in a laboratory circulating water system. In this study, all experimental groups were fed quantitatively (at 08:00 and 17:00) (Supplementary Table S1). After feeding, the remaining feed was collected within 15 minutes, dried, and weighed to calculate the actual feed intake. The water was changed 1–2 times per day, according to water quality. Throughout the experiment, the water quality parameters were as follows: water temperature of 23.91 ± 0.74 °C, dissolved oxygen concentration of 6.79 ± 0.16 mg/L, pH value of 7.36 ± 0.29, and ammonia nitrogen concentration of 0.02 ± 0.01 mg/L.

2.3 Sample collection

A 24-h fasting period was applied at the end of the experiment to minimize handling stress and eliminate gut content interference. After collection, all fish were counted and weighed to determine growth parameters (Supplementary Text S1). Subsequently, 10 fish per tank were anesthetized with MS-222 (100mg/L) and dissected on ice for sample collection (Xu et al., 2026).

Three fish per tank were collected and stored at -80 °C for whole-body analysis. Blood samples were collected from seven fish per tank (≤ 1.0 mL/fish), maintained at 4 °C for serum separation, and centrifuged at 3500 rpm for 10 min. The separated serum was stored at -80 °C for subsequent analysis of immune enzyme activities and biochemical parameters. Intestinal and liver tissues were collected immediately after dissection, frozen in liquid nitrogen, and stored at -80 °C. Intestinal samples from six fish per tank were collected for gut microbiota analysis, whereas liver samples from four fish per tank were collected for analysis of immune-related gene expression and hepatic immune enzyme activities. All sampling procedures were performed on ice to minimize tissue degradation.

2.4 Determination of immune enzyme activities and antioxidant indices

Hepatic superoxide dismutase (SOD), catalase (CAT), total antioxidant capacity (T-AOC), and malondialdehyde (MDA) levels were measured using commercial enzyme-linked immunosorbent assay kits (Shanghai Meilian Biotechnology Co., Ltd., Shanghai, China). Serum alkaline phosphatase (AKP) and acid phosphatase (ACP) activities were determined using the same kits according to the instructions of the manufacturer.

2.5 Quantitative real-time polymerase chain reaction analysis

Total RNA was extracted from liver tissues using an RNA extraction kit (TransGen, Beijing, China). RNA concentration and purity were assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA), and only RNA samples with A260/A280 ratios between 1.8 and 2.1 were used for subsequent analysis. RNA integrity was verified by agarose gel electrophoresis. Reverse transcription was performed using the Evo M-MLV RT Kit (Accurate Biology, Hunan, China), with 1 μg of total RNA used in each 20-μL reaction. Quantitative real-time PCR (qRT-PCR) was performed using the SYBR® Green Pro Taq HS Premix II Kit (Accurate Biology, Hunan, China) on a Roche LightCycler 480 II system (Switzerland). Each 20-μL qRT-PCR reaction contained 1 μL of cDNA. The reaction conditions were as follows: 95 °C for 30 s; 40 cycles of 95 °C for 5 s and 60 °C for 30 s; and 60 °C for 5 min. Primer amplification efficiencies, determined from standard curves, ranged from 90% to 110%, with R² values > 0.98. Primer specificity was confirmed by the presence of a single peak in the melting curve analysis and a single specific band on agarose gel electrophoresis. The target genes included reference gene beta-actin (β-actin) (Song et al., 2023), transforming growth factor-β (tgfb1a), interleukin-6 (il6), interleukin-22 (il22), and tumor necrosis factor-α (tnfa). Three technical replicates were conducted for each sample, and the relative gene expression was analyzed using the 2^-ΔΔCT method. The primer sequences and accession number for each target gene and the reference gene (β-actin) are listed in Table 2.

Table 2. Primer sequences for real-time PCR.

GenePrimer sequence (5′–3′)GenBank accession No.
β-actinF: GGACACGGAAAGGATTGACAGR: CGGAGTCTCGTTCGTTATCGGXM_038695351.1
il22F: GGGCGAGCGAGGTATAAACAR:GTGGCGGTGGAGTTTTTCAGXM_038709272.1
tnfaF: CTTCGTCTACAGCCAGGCATCGR: TTTGGCACACCGACCTCACCXM_038710731.1
tgfb1aF: GCTCAAAGAGAGCGAGGATGR: TCCTCTACCATTCGCAATCCXM_038693206.1
il6F: GGAACCCTGAACAGGTAACGR: TGTGCGGTCATCTTTCTGTGGXM_038725465.1

β-actin, beta-actin; il6, interleukin-6; il22, interleukin-22; tnfa, tumor necrosis factor-α; tgfb1a, transforming growth factor-β.

2.6 Intestinal microbiota analysis

2.6.1 Experimental process

Genomic DNA was extracted from intestinal samples using a DNA extraction kit (Omega Bio-Tek, USA). The V3–V4 hypervariable region of the bacterial 16S rRNA gene was amplified using barcoded primers: 341F (CCTACGGGGNGGCWGCAG) and 806R (GGACTACHVGGGTATCTAAT). PCR products were first examined with 2% agarose gel electrophoresis and subsequently purified using the AxyPrep DNA Gel Extraction Kit (Axygen, USA) following the instructions of the manufacturer. The purified amplicons were ligated with sequencing adapters to construct libraries. The libraries were then sequenced on the Illumina platform.

2.6.2 Data processing

Raw sequencing reads were quality-filtered, denoised, and screened for chimeras using the DADA2 pipeline. Amplicon sequence variants (ASVs) were inferred using DADA2 with single-nucleotide resolution. ASV sequences were aligned against the SILVA database (version 138.2) for taxonomic annotation using the RDP classifier software (version 2.14) with a naive Bayesian model with confidence threshold was set at ≥ 0.8.

2.6.3 Diversity analysis

Alpha diversity was evaluated using the Shannon and Simpson indices, and differences among the five groups were assessed using the Kruskal-Wallis test. Beta diversity was analyzed based on Bray-Curtis dissimilarity matrices calculated from microbial community abundance profiles. PERMANOVA was used to evaluate differences in microbial community composition among groups.

2.6.4 Species identification analysis

To identify shared and unique bacterial genera across the five dietary groups, Venn diagrams were constructed at the genus level to visualize the intersections and group-specific genera. Genera detected in all replicates within a treatment were defined as core genera for that treatment. Given the complexity of multiple-group comparisons, UpSet plots were further generated using the UpSetR package in R to visualize the intersection patterns and distribution of bacterial genera among the five dietary treatments. Furthermore, Random Forest analysis was performed based on genus-level relative abundance data using the caret package in R (method = “rf”). Variable importance was evaluated using the mean decrease in accuracy (MDA), and genera with MDA values greater than the mean MDA across all genera were identified as discriminatory genera.

2.6.5 Functional analysis

The functional profiles of microbial communities were predicted using PICRUSt2 based on the 16S rRNA sequencing data. Functional annotation was performed using the KEGG Orthology (KO) database, and the predicted functions were categorized according to KEGG hierarchical classification. The analyzed functional categories included Level 1 and Level 2 KEGG pathways, such as metabolism, genetic information processing, cellular processes, environmental information processing, and related metabolic pathways.

2.6.6 Spearman’s correlation analysis

Spearman’s rank correlation analysis was performed to evaluate the associations between the relative abundances of key intestinal bacterial genera (Aeromonas, Cetobacterium, and Bacteroides) and host physiological parameters, including growth performance (FBW, WGR, and FCR), nonspecific immune indicators (ACP and AKP), antioxidant parameters (SOD, CAT, T-AOC, and MDA), and immune-related genes (tgfb1a, il6, il22, and tnfa).The Spearman’s correlation coefficients were calculated using GraphPad Prism 9.5.0. Correlations were considered statistically significant at P < 0.05.

2.7 Statistical analysis

Each tank was treated as the experimental unit (n = 3), data normality was assessed using the Shapiro-Wilk test, and homogeneity of variances was evaluated using Levene’s test. One-way analysis of variance (ANOVA) was performed using IBM SPSS Statistics version 21.0 (SPSS Inc., Chicago, IL, USA), followed by Duncan’s multiple range test for post hoc comparisons. Differences were considered statistically significant at P < 0.05.

3 Results

3.1 Growth performance

The effects of dietary supplementation with different levels of GML on the growth performance of largemouth bass are shown in Table 3. With increasing dietary GML levels, final body weight (FBW), weight gain rate (WGR), and specific growth rate (SGR) first increased and then decreased. FBW reached the highest values in the G2 and G3 groups. WGR and SGR reached the highest values in the G2 group, and both were significantly higher than those in the FM group (P < 0.05). FCR first decreased and then increased, with the lowest values observed in the G2 and G3 groups. The feed conversion ratio (FCR) values in these two groups were significantly lower than that in the FM group (P < 0.05). No significant difference in survival rate (SR) was observed among all groups (P > 0.05). Based on the regression equation model fitted by FBW, the optimal level of GML was 750 mg/kg (Figure 1).

Table 3. Effects of GML on growth performance of largemouth bass.

GroupItems
IBW/gFBW/gWGR/%SGR/%/dSR/%FCR
FM7.42 ± 0.0231.37 ± 0.55a324.48 ± 9.33a2.58 ± 0.04a98.67 ± 2.311.17 ± 0.03b
G17.39 ± 0.0332.33 ± 0.42ab337.52 ± 4.26ab2.63 ± 0.02ab100 ± 0.001.12 ± 0.02ab
G27.45 ± 0.0133.51 ± 0.32c350.82 ± 3.99b2.69 ± 0.02b97.33 ± 2.311.07 ± 0.02a
G37.41 ± 0.0633.07 ± 0.69bc347.32 ± 8.78b2.68 ± 0.04b98.67 ± 2.311.09 ± 0.03a
G47.41 ± 0.0432.20 ± 0.87ab335.33 ± 11.50ab2.63 ± 0.05ab100 ± 0.001.13 ± 0.04ab
P-value0.6030.0120.0180.0160.3820.020
η²0.2210.6940.6640.6760.3180.660
CV0.492.843.501.861.853.83

Data were derived from mean ± SD of three biological replicates. Different letters in the table indicate significant differences (P < 0.05) and the same letter indicates non-significant differences (P > 0.05). P-values < 0.05 were considered statistically significant, P-values < 0.01 were considered highly statistically significant, and P-values ≥ 0.05 were considered not statistically significant. IBW, initial body weight; FBW, final body weight; WGR, weight gain rate; SGR, specific growth rate; SR, survival rate; FCR, feed conversion ratio. P-value, probability value; η², effect size; CV, coefficient of variation.

Quadratic regression analysis was performed to estimate the optimal dietary GML supplementation level based on FBW. Data are presented as mean ± SD (n = 3), and error bars represent SD. Dietary GML supplementation level (mg/kg) was used as the independent variable (X), and mean FBW (g) was used as the dependent variable (Y). When the fitted curve was concave (a < 0), the dietary GML level corresponding to the maximum predicted FBW was calculated from the vertex of the quadratic equation as X = −b/(2a). Based on the fitted regression equation, the estimated optimal dietary GML supplementation level was 750 mg/kg.
Figure 1. Quadratic regression analysis was performed to estimate the optimal dietary GML supplementation level based on FBW. Data are presented as mean ± SD (n = 3), and error bars represent SD. Dietary GML supplementation level (mg/kg) was used as the independent variable (X), and mean FBW (g) was used as the dependent variable (Y). When the fitted curve was concave (a < 0), the dietary GML level corresponding to the maximum predicted FBW was calculated from the vertex of the quadratic equation as X = −b/(2a). Based on the fitted regression equation, the estimated optimal dietary GML supplementation level was 750 mg/kg.

3.2 Whole body composition

The effects of dietary supplementation with different levels of GML on the whole body composition of largemouth bass are shown in Figure 2. After GML supplementation, the CL contents in the G1 and G2 groups were significantly decreased (P < 0.05). Compared with the control group (FM), the CP content was significantly increased in all experimental groups (P < 0.05), with the highest crude protein contents observed in the G2 and G3 groups. No significant difference in moisture content was observed among all groups (P > 0.05).

Effects of GML on whole-body composition of largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. Different lowercase letters indicate significant differences among groups (*P* < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test. CL, total protein of whole fish; CP, total crude fat of the whole fish.
Figure 2. Effects of GML on whole-body composition of largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. Different lowercase letters indicate significant differences among groups (P < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test. CL, total protein of whole fish; CP, total crude fat of the whole fish.

3.3 Hantioxidant capacity

The effects of dietary supplementation with different levels of GML on hepatic antioxidant of largemouth bass are shown in Figure 3. Dietary GML supplementation significantly increased the activities of CAT, SOD, and T-AOC (P < 0.05). CAT and SOD activities reached the highest values in the G2 group (Figures 3A, B). T-AOC activity showed high values in the G2 and G3 groups (P < 0.05) (Figure 3C). MDA content first decreased and then increased with GML supplementation. The MDA contents in all GML-supplemented groups were significantly lower than that in the control group (FM) (P < 0.05), with the lowest values observed in the G2 and G3 groups (Figure 3D).

Effects of GML on hepatic antioxidant capacity of largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. **(A)** represents catalase (CAT) activity; **(B)** represents superoxide dismutase (SOD) activity; **(C)** represents total antioxidant capacity (T-AOC); and D represents malondialdehyde (MDA) content. Different lowercase letters indicate significant differences among groups (*P* < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test.
Figure 3. Effects of GML on hepatic antioxidant capacity of largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. (A) represents catalase (CAT) activity; (B) represents superoxide dismutase (SOD) activity; (C) represents total antioxidant capacity (T-AOC); and D represents malondialdehyde (MDA) content. Different lowercase letters indicate significant differences among groups (P < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test.

3.4 Serum immune performance

The effects of dietary supplementation with different levels of GML on serum immune performance of largemouth bass are shown in Figure 4. The activities of ACP and AKP in the serum of largemouth bass were significantly affected by dietary GML levels (P < 0.05). ACP activity reached the highest value in the G2 group (Figure 4A). AKP activity reached the highest values in the G2 and G3 groups (Figure 4B), and these values were significantly higher than that in the control group FM (P < 0.05).

Effects of GML on serum immune performance of largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. **(A)** represents acid phosphatase (ACP) activity; **(B)** represents alkaline phosphatase (AKP) activity. Different lowercase letters indicate significant differences among groups (*P* < 0.05), as determined by one-way ANOVA followed by Duncan's multiple range test.
Figure 4. Effects of GML on serum immune performance of largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. (A) represents acid phosphatase (ACP) activity; (B) represents alkaline phosphatase (AKP) activity. Different lowercase letters indicate significant differences among groups (P < 0.05), as determined by one-way ANOVA followed by Duncan's multiple range test.

3.5 Expression levels of genes related to inflammation in the liver

In this study, the expression levels of genes related to inflammation in liver tissues were measured (Figure 5). The addition of GML significantly increased the levels of anti-inflammatory tgfb1a and il22, and these indicators were significantly lower in the FM group than in the G2 and G3 groups (P < 0.05); the contents of pro-inflammatory cytokines il6 and tnfa in the G2 and G3 groups were significantly lower than those in the FM group (P < 0.05).

Effects of GML on the expression levels of genes related to inflammation in the liver of largemouth bass. *tgfb1a*, transforming growth factor-β; *il6*, interleukin-6; *il22*, interleukin-22; and *tnfa*, tumor necrosis factor-α, tumor necrosis factor-α. Data are presented as mean ± SD (n = 3), and error bars represent SD. Different lowercase letters indicate significant differences among groups (*P* < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test.
Figure 5. Effects of GML on the expression levels of genes related to inflammation in the liver of largemouth bass. tgfb1a, transforming growth factor-β; il6, interleukin-6; il22, interleukin-22; and tnfa, tumor necrosis factor-α, tumor necrosis factor-α. Data are presented as mean ± SD (n = 3), and error bars represent SD. Different lowercase letters indicate significant differences among groups (P < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test.

3.6 Intestinal microbiota

3.6.1 Intestinal microbiota composition

At the phylum level, Pseudomonadota, Bacillota, and Bacteroidota dominated the intestinal microbiota in all groups (Figure 6A). The relative abundances of Pseudomonadota in the G2 and G4 groups were significantly lower than those in the other groups (P < 0.05). The relative abundances of Bacillota in the G2 and G4 groups were significantly higher than those in the other groups (P < 0.05). Meanwhile, the relative abundances of Bacteroidota in the G2 and G3 groups were significantly higher than those in the other groups (P < 0.05) (Figure 6C).

Effects of GML on intestinal microbiota of largemouth bass. **(A)** represents the species composition of the intestinal microbiota at the phylum level; **(B)** represents the species composition of the intestinal microbiota at the genus level; **(C)** shows the top three phylum; **(D)** shows the top five genus. Different lowercase letters indicate significant differences among groups (*P* < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test.
Figure 6. Effects of GML on intestinal microbiota of largemouth bass. (A) represents the species composition of the intestinal microbiota at the phylum level; (B) represents the species composition of the intestinal microbiota at the genus level; (C) shows the top three phylum; (D) shows the top five genus. Different lowercase letters indicate significant differences among groups (P < 0.05), as determined by one-way ANOVA followed by Duncan’s multiple range test.

At the genus level, the bacterial community composition became more complex. The dominant genera mainly included Citrobacter, Plesiomonas, Stenotrophomonas, Acinetobacter, Bacteroides, Cetobacterium, Pseudomonas, Mesomycoplasma, and Aeromonas (Figure 6B). With increasing dietary GML levels, the relative abundances of Aeromonas, Pseudomonas, and Mesomycoplasma first increased and then decreased, with the lowest values observed in the G2 and G3 groups (P < 0.05). The relative abundances of Bacteroides and Cetobacterium in the G2 and G3 groups were significantly higher than those in the other groups (P < 0.05) (Figure 6D).

3.6.2 A-diversity of intestinal microbiota

After dietary GML supplementation, the α-diversity of intestinal microbiota in largemouth bass fluctuated slightly, but no significant differences were observed among all groups (P > 0.05) (Figure 7).

Effects of GML on α-diversity of intestinal microbiota in largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. Different lowercase letters indicate significant differences among groups (*P* < 0.05). Differences in alpha diversity were assessed using the Kruskal–Wallis test, whereas differences in beta diversity were evaluated using PERMANOVA.
Figure 7. Effects of GML on α-diversity of intestinal microbiota in largemouth bass. Data are presented as mean ± SD (n = 3), and error bars represent SD. Different lowercase letters indicate significant differences among groups (P < 0.05). Differences in alpha diversity were assessed using the Kruskal–Wallis test, whereas differences in beta diversity were evaluated using PERMANOVA.

3.6.3 Indicator species of intestinal microbiota

The results of UpSet plot analysis (Figure 8A) were consistent with those of the Venn diagram (Figure 8B). Among the five groups (FM, G1, G2, G3, and G4), the G2 group had the highest total number of intestinal microbial species (259), followed by G4 (151), G3 (126), G1 (59), and the FM control group (51). In terms of unique species composition, the G2 group had 124 unique species, which was higher than those in G4 (46), G3 (16), FM (9), and G1 (11). A total of 14 genera were shared by all five groups. These genera represented the inherent core microbiota in the intestine and were not affected by GML supplementation.

Effects of GML on indicator species of intestinal microbiota in largemouth bass. **(A)** shows the Venn diagram at the genus level among the five groups. Each circle represents a group of samples. The numbers in overlapping areas indicate the total number of genera shared by the corresponding groups, while numbers in non-overlapping areas represent the genera unique to each group. **(B)** shows the distribution of common and unique genera among the five groups as presented in the Upset diagram. The black dots in the matrix indicate the participation of each group in the corresponding intersection. The left and upper bar charts represent the combinations of each intersection and the number of elements in each group respectively. **(C)** is the random forest analysis that identifies key classification markers (FM and G2). The x-axis represents MeanDecreaseGini, and the y-axis represents the different species. The size of the points indicates the relative abundance, and the color indicates the change in abundance. Data are presented as mean ± SD (n = 3).
Figure 8. Effects of GML on indicator species of intestinal microbiota in largemouth bass. (A) shows the Venn diagram at the genus level among the five groups. Each circle represents a group of samples. The numbers in overlapping areas indicate the total number of genera shared by the corresponding groups, while numbers in non-overlapping areas represent the genera unique to each group. (B) shows the distribution of common and unique genera among the five groups as presented in the Upset diagram. The black dots in the matrix indicate the participation of each group in the corresponding intersection. The left and upper bar charts represent the combinations of each intersection and the number of elements in each group respectively. (C) is the random forest analysis that identifies key classification markers (FM and G2). The x-axis represents MeanDecreaseGini, and the y-axis represents the different species. The size of the points indicates the relative abundance, and the color indicates the change in abundance. Data are presented as mean ± SD (n = 3).

Random Forest analysis was performed between the FM and G2 groups (Figure 8C). The results showed that Aeromonas was the key species distinguishing the intestinal microbiota of largemouth bass under different GML treatments. It had the highest classification contribution and the highest mean abundance within groups. Combined with the genus-level microbiota composition results (Figures 6B, D), dietary GML supplementation significantly reduced the relative abundance of Aeromonas in the intestine (P < 0.05).

3.6.4 Functional analysis of intestinal microbiota

To further clarify the potential effects of GML on the intestinal microbiota of largemouth bass, the functional profiles of the intestinal microbial communities were predicted using PICRUSt2. The results showed that the predicted functions were mainly associated with KEGG Level 2 metabolic categories, including carbohydrate metabolism, amino acid metabolism, metabolism of cofactors and vitamins, energy metabolism, and lipid metabolism. Among the five groups, the G2 group exhibited relatively higher predicted abundances in several metabolic categories, including carbohydrate, amino acid, energy, and lipid metabolism (Supplementary Figure S1A). Based on these patterns, a pairwise comparison between the FM and G2 groups was further performed. The predicted abundances of carbohydrate metabolism, metabolism of cofactors and vitamins, and amino acid metabolism (top three) were significantly higher in the G2 group than in the FM group (P < 0.05) (Supplementary Figure S1B).

3.6.5 Spearman’s correlation analysis

Spearman’s correlation analysis revealed significant associations between key bacterial genera and host physiological parameters (Supplementary Figure S2). Aeromonas was generally negatively correlated with growth, antioxidant, and immune-related indicators, whereas Cetobacterium and Bacteroides showed predominantly positive correlations with these parameters and negative correlations with FCR or MDA (P < 0.05). Notably, the strongest associations were observed between Aeromonas and CAT (rs = −0.857, P < 0.001), Cetobacterium and ACP (rs = 0.724, P = 0.003), and Bacteroides and TGF-β (rs = 0.745, P = 0.002).

4 Discussion

Growth performance is a key indicator of animal growth and feed conversion ratio (Onomu and Okuthe, 2024; Lin et al., 2022; Ullah et al., 2024). Although functional feed additives have gained increasing attention in aquaculture, their practical application remains limited (Onomu and Okuthe, 2024). Therefore, their effects on cultured fish species require further evaluation.

The results showed that the GML diet significantly improved the growth performance of juvenile largemouth bass. FBW, WGR, and SGR increased significantly. The secondary regression analysis revealed 750 mg/kg as the optimal dietary GML supplementation level. The estimated optimal GML supplementation level in the present study was lower than those reported for juvenile grouper (1700 mg/kg; Li et al., 2022a) and Trachinotus ovatus (1500 mg/kg; Lin et al., 2022), identical to that reported for zebrafish (750 mg/kg; Wang et al., 2021), and comparable to those reported for Litopenaeus vannamei (700 mg/kg; Wang et al., 2020) and Monopterus albus (1000 mg/kg; Liu et al., 2026). These differences potentially reflect species-specific metabolism, basal diet composition, lipid utilization ability, gut microbiota, culture conditions, and the evaluation criteria used. GML functions as an energy source and contributes to antioxidant defense, anti-inflammatory responses, lipid metabolism, and intestinal microbiota regulation (Ullah et al., 2024; Xu et al., 2024). Therefore, the optimal GML supplementation level may vary among fish species depending on diet composition and culture conditions. In this study, a appropriate level of GML improved the growth performance of juvenile largemouth bass, whereas higher supplementation levels did not provide additional growth-promoting benefits.

Whole-body composition is a key indicator of nutrient deposition and product quality because it reflects the conversion of dietary nutrients into body protein, lipid, and water (Lin et al., 2022). Studies show that GML increases whole-body crude protein (CP) content and decreases crude lipid content (Li et al., 2022c; Zhuang et al., 2022; Wang et al., 2020). These findings are consistent with those of this study and may reflect distinct metabolic properties of GML. In the intestine, GML is hydrolyzed into lauric acid and glycerol (Lin et al., 2022). Lauric acid, a medium-chain fatty acid, is converted to lauroyl-CoA and rapidly undergoes β-oxidation, resulting in acetyl-CoA, NADH, and FADH2. These metabolites enter the tricarboxylic acid cycle and oxidative phosphorylation pathways to generate ATP (Watanabe and Tsujino, 2022). The resulting energy supply likely reduces protein catabolism and promotes protein deposition (Schönfeld and Wojtczak, 2016). Lauric acid preferentially undergoes β-oxidation rather than re-esterification with glycerol-3-phosphate to form triacylglycerols, likely reducing lipid storage (Watanabe and Tsujino, 2022; Schönfeld and Wojtczak, 2016). Since lipids represent an important form of energy storage in fish, the reduced whole-body CL content observed in the GML-treated groups may indicate decreased lipid deposition and altered energy partitioning. This suggests that GML may shift lipid utilization from storage toward oxidative energy production, thereby providing energy for growth and other physiological processes (Liu et al., 2026; Watanabe and Tsujino, 2022). In the functional analysis of the intestinal microbiota, GML enhanced the energy metabolism of largemouth bass, which also provided some supporting evidence. Previous studies have shown that dietary GML can improve flesh quality by modulating muscle nutrient composition, fatty acid profiles, and texture (Zhuang et al., 2022; Ye et al., 2026). However, since only whole-body CL was measured in the present study, whether the reduced lipid content translates into improved flesh quality and altered energy storage requires further investigation.

In this study, dietary GML supplementation substantially enhanced AKP and ACP activities. It also upregulated il22 and tgfb1a expression while downregulating IL-6 and TNF-α expression. These findings suggest that GML promotes immune homeostasis by enhancing nonspecific innate immune indicators and limiting excessive inflammatory responses. ACP primarily exhibits hydrolytic activity under acidic conditions and contributes to the degradation of intracellular phosphorylated compounds, lysosomal metabolism, and pathogen clearance. AKP primarily functions under alkaline conditions and participates in phosphate bond hydrolysis, phosphate group transfer, energy metabolism, and cell signaling (Qi et al., 2025). Studies show that ACP and AKP activities respond to environmental stressors, including hypoxia and transportation stress. Therefore, ACP and AKP activities are widely used as indicators of nonspecific innate immune indicators, physiological stress, and health status in aquatic animals (Qi et al., 2025; Nie et al., 2020; Ren et al., 2022). In challenge experiments with Trachinotus ovatus, dietary GML supplementation significantly increased ACP and AKP activities compared to the control group (Lin et al., 2023). Similarly, dietary supplementation at 2000 mg/kg GML significantly increased hemolymph ACP and AKP activities in Eriocheir sinensis (Fu et al., 2022). A study in hybrid grouper also shows that dietary GML supplementation significantly increases serum ACP, AKP, and lysozyme activities, with peak values at 1700 mg/kg (Li et al., 2022a). This finding is consistent with the increased ACP and AKP activities observed in juvenile largemouth bass in this study, suggesting that GML enhances nonspecific innate immune indicators across fish species. In recent aquaculture studies, AKP/ACP activities have also been used as indicators of nutrient absorption capacity. Studies report that ACP and AKP activities reflect the metabolic and nonspecific immune status of fish. Among these, AKP is closely associated with growth, protein synthesis, and nutrient absorption and utilization in aquatic animals (Luo et al., 2023; Yang et al., 2024). In this study, ACP and AKP activities showed trends similar to those of whole-body CP content. These findings suggest that increased immune enzyme activities may partially enhance nutrient absorption and utilization, promoting protein deposition in fish. This relationship further supports these experimental findings. tnfa and il6 are key pro-inflammatory cytokines regulating inflammatory and immune responses in fish. Their downregulation suggests that GML may suppress pro-inflammatory cytokine production and reduce the risk of inflammation-induced tissue damage. il22 and tgfb1a are key immunoregulatory cytokines in fish. TGF-β exerts anti-inflammatory and immunosuppressive effects, whereas il22 contributes to immune regulation, mucosal defense, and tissue protection (Sakai et al., 2021; Zeng et al., 2024). The increased IL-22 and tgfb1a expression suggests that GML enhances anti-inflammatory regulation and immune regulatory feedback. Overall, GML may promote immune homeostasis and improve immune defense by increasing nonspecific immune enzyme activities, enhancing anti-inflammatory regulation, and inhibiting pro-inflammatory cytokine expression.

The antioxidant system is essential for maintaining cellular homeostasis in fish under both normal and stress conditions (Li et al., 2022b). T-AOC represents the overall antioxidant defense capacity of the body or tissue (Wang et al., 2024). SOD is a key antioxidant enzyme that catalyzes the dismutation of superoxide anions (O2⁻) into H2O2 and O2, thereby limiting oxidative chain reactions (Ma et al., 2025). SOD-produced H2O2 is subsequently converted into water and oxygen by CAT, removing hydrogen peroxide and maintaining cellular redox balance (Anwar et al., 2024). MDA, the end product of lipid peroxidation, is formed during free radical-mediated lipid oxidation and serves as a widely recognized marker of oxidative stress and lipid peroxidation (Oliveira et al., 2024). In this study, dietary GML supplementation significantly increased T-AOC, CAT, and SOD activities in juvenile largemouth bass, with the highest activities observed in the G2 group. In contrast, dietary GML supplementation significantly reduced MDA content, with the lowest levels observed in the G2 and G3 groups. These findings indicate that GML enhances antioxidant defense in juvenile largemouth bass, likely promoting ROS clearance and reducing lipid peroxidation. Collectively, these effects suggest that GML may alleviate oxidative capacity by activating the antioxidant enzyme system and maintaining redox homeostasis. Similar effects have also been reported in other animal species. In Trachinotus ovatus, dietary GML supplementation at 1000 mg/kg and 1500 mg/kg significantly increased T-AOC and SOD activities. Similarly, dietary supplementation with 6000 mg/kg α-monolaurin in Oreochromis niloticus resulted in the highest SOD, CAT, glutathione, and glutathione peroxidase levels while significantly reducing MDA content (Ali et al., 2023). In large yellow croaker, dietary GML supplementation improved antioxidant status in different tissues. Specifically, 200–400 mg/kg GML reduced intestinal MDA content and increased CAT and SOD activities, while 400–800 mg/kg GML produced similar antioxidant effects in the liver (Tang et al., 2023a, Tang et al., 2023b). These findings suggest that GML enhances antioxidant defense and reduces lipid peroxidation by increasing T-AOC, SOD, and CAT activities while decreasing MDA content. This possible mechanism may be attributed to the metabolic properties of GML. Given the characteristics of medium-chain fatty acid derivatives, GML may enhance energy utilization by up regulating fatty acid β-oxidation. This process supplies substrates and reducing equivalents for oxidative phosphorylation, supporting ATP production and mitochondrial energy metabolism (Lin et al., 2022; Tahri-Joutey et al., 2021; Deshpande and Mohiuddin, 2023). Improved mitochondrial energy metabolism may reduce electron leakage from the electron transport chain, thereby limiting ROS accumulation, lipid peroxidation, and MDA formation. Mitochondria are a major source of intracellular ROS. Electron leakage from the mitochondrial electron transport chain causes the one-electron reduction of oxygen, generating O2⁻ (Tahri-Joutey et al., 2021; Zhao et al., 2019). Accordingly, improved electron transport efficiency may reduce electron leakage, O2⁻ production, and ROS accumulation (Zhao et al., 2019). Therefore, we hypothesize that changes in mitochondrial energy metabolism may partly contribute to the enhanced antioxidant status and reduced MDA levels observed following GML supplementation.

The intestinal microbiota interacts with the immune system to maintain intestinal homeostasis and enhance host immunity (Zhang et al., 2024). In aquatic environments, the gut microbiota of fish is highly responsive to dietary composition and other environmental factors, resulting in high diversity and plasticity (Ruiz et al., 2024). In this study, dietary GML supplementation at 800 mg/kg and 1100 mg/kg significantly increased the relative abundances of Cetobacterium and Bacteroides. Cetobacterium is a common bacterial genus that is closely associated with the intestinal health of fish. Some species synthesize vitamin B12 and improve host resistance to infection by promoting beneficial microbial interactions and strengthen intestinal tight junction integrity (Qi et al., 2023). Additionally, Cetobacterium-derived metabolites, such as acetate, regulate intestinal immune responses. A study reports that VD promotes the growth of acetate-producing Cetobacterium in the intestine of Danio rerio, increasing il22 production (Liao et al., 2023). Similarly, dietary supplementation with Cetobacterium somerae improves intestinal antioxidant capacity and immune function in largemouth bass (Zhang et al., 2023). Bacteroides is crucial for degrading complex polysaccharides and producing short-chain fatty acids, metabolizing complex polysaccharides to produce organic acids, including acetate, propionate, and succinate (Fan et al., 2023; Cheng et al., 2022). Furthermore, studies show that capsular polysaccharides extracted from Bacteroides fragilis suppress tnfa and il6 expression while promoting il10 and il22 secretion, thereby suppressing inflammation (Zhong et al., 2024). These findings are consistent with the results of this study. Dietary GML supplementation increased the relative abundances of Cetobacterium and Bacteroides, accompanied by enhanced nonspecific immune responses and antioxidant capacity. Indicator species analysis identified Aeromonas as a key taxon distinguishing the gut microbiota among the experimental groups. Recent studies report Aeromonas as a common opportunistic pathogen in aquaculture animals that can cause intestinal injury and inflammation, particularly under intensive culture conditions (Zhang et al., 2025). In this study, dietary GML supplementation at 800 mg/kg, 1100 mg/kg, and 1400 mg/kg significantly reduced the relative abundance of Aeromonas. This finding suggests that GML reduces the intestinal burden of potential pathogens and promotes gut microbial homeostasis. The increased relative abundances of genera associated with intestinal health, including Cetobacterium and Bacteroides, together with the reduced abundance of opportunistic taxa (Aeromonas), may be associated with improved intestinal health, innate immune responses, and redox homeostasis in juvenile largemouth bass following appropriate GML supplementation.

5 Conclusion

In conclusion, dietary supplementation with an appropriate level of GML improved growth performance, modulated innate immune biomarkers, and enhanced antioxidant capacity in juvenile largemouth bass. GML supplementation was also associated with shifts in the intestinal microbiota composition, including increased relative abundances of genera associated with host health, such as Cetobacterium and Bacteroides and a decreased relative abundance of the opportunistic pathogen Aeromonas. Based on the regression analysis of FBW, the estimated optimal dietary GML supplementation level was 750 mg/kg under the present experimental conditions. Nevertheless, this study has several limitations, including the use of a single developmental stage, the absence of a disease challenge, intestinal histological and metabolomic analyses, and the largely descriptive nature of the microbiome analysis. Further studies are needed to clarify the underlying mechanisms and validate the effects of GML across different developmental stages.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2026.1950219/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Enric Gisbert, Institute of Agrifood Research and Technology (IRTA), Spain

Reviewed by: Ozdan Akram Ghareeb, Northern Technical University (NTU), Iraq

Leonildo Dos Anjo Viagem, Sokoine University of Agriculture College of Agriculture, Tanzania

Footnotes

GML, glycerol monolaurate; FM, basal diet; SOD, superoxide dismutase; CAT, catalase; T-AOC, total antioxidant capacity; MDA, malondialdehyde; AKP, alkaline phosphatase; ACP, acid phosphatase; tgfb1a, transforming growth factor-β; il6, interleukin-6; il22, interleukin-22; and tnfa, tumor necrosis factor-α; β-actin, beta-actin; CP, crude protein; ROS, reactive oxygen species; ATP, adenosine triphosphate; NADH, nicotinamide adenine dinucleotide (reduced); FADH2, flavin adenine dinucleotide (reduced); RNA, ribonucleic acid; cDNA, complementary DNA; PCR, polymerase chain reaction; rRNA, ribosomal RNA; DADA2, Divisive Amplicon Denoising Algorithm 2.

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

The author(s) declared that financial support was received for this work and/or its publication. Ths work was supported by Natural Science Foundation of Fujian Province, China (No. 2025J08251); Education Research Project for Middle-aged and Young Teachers in Fujian Province (No. JAT241086); Start-up funding for high-level talents (404067). The article processing charge will be covered by the Start-up Funding for High-level Talents (No. 404067). The article processing charge will be covered by the Start-up Funding for High-level Talents (No. 404067).

Data availability

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Ethics approval

The animal study was approved by Ethics Committee of Fujian Polytechnic Normal University/Fujian Polytechnic Normal University. The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

XL: Conceptualization, Data curation, Funding acquisition, Investigation, Writing – original draft. HX: Project administration, Supervision, Writing – review & editing. JW: Project administration, Supervision, Writing – review & editing. ML: Project administration, Supervision, Writing – review & editing. QY: Conceptualization, Methodology, Software, Supervision, Writing – review & editing.

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Citation

Li, X., et al. (2026). Optimal dietary glycerol monolaurate supplementation improves growth performance, antioxidant capacity, immune responses and intestinal microbiota in juvenile largemouth bass. Frontiers in Marine Science, Volume 13. https://doi.org/
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13 - 2026

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Copyright © 2026 Li, Xu, Wang, Lin and Yang.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Xuehe Li; Qihui Yang

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