Biochemical and Multi-Omics Analyses Reveal Skeletal Muscle Adaptation to Chronic Low-Salinity Stress of Marine Medaka (Oryzias melastigma)

Biochemical and Multi-Omics Analyses Reveal Skeletal Muscle Adaptation to Chronic Low-Salinity Stress of Marine Medaka (Oryzias melastigma) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Biochemical and Multi-Omics Analyses Reveal Skeletal Muscle Adaptation to Chronic Low-Salinity Stress of Marine Medaka (Oryzias melastigma) Tian-Hong Chen, Qing-Hao Zhan, Xiao-Yu Zeng, Ning-Ning Ma, Qi-Liang Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9208878/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Salinity fluctuations are key environmental drivers that shape physiological homeostasis in euryhaline teleosts by altering osmotic balance and energy allocation. In this study, marine medaka ( Oryzias melastigma ) was used to elucidate skeletal muscle adaptation to chronic low-salinity stress by integrating histology, transmission electron microscopy (TEM), antioxidant indices, transcriptomics, and metabolomics. Offspring ( F₁ ) derived from low-salinity-acclimated parents were reared at a salinity of 2.5‰ and sampled at 4 months, with fish from 25‰ seawater serving as controls. Low salinity significantly reduced the mean cross-sectional area of myofibers while increasing fiber density. TEM revealed a marked widening of the I-band without changes in sarcomere length, suggesting an altered actin–myosin overlap that may help maintain contractile performance under osmotic stress. Biochemical assays showed unchanged catalase activity but significantly elevated total antioxidant capacity (TAC) and malondialdehyde (MDA)levels, indicating enhanced lipid peroxidation accompanied by compensatory activation of the antioxidant defense network. Transcriptome profiling identified 1266 differentially expressed genes (985 downregulated, 281 upregulated), enriched in cytoskeletal and contractile remodeling (desmosomes, myofibrils, myosin filaments) as well as signaling pathways including Wnt/β-catenin and mTOR. Metabolomics detected 112 differential metabolites; the pro-inflammatory oxidized phospholipid POVPC accumulated, 3-hydroxycoumarin levels increased, and uric acid levels decreased. Enrichment analyses highlighted autophagy, mTOR signaling, and the sulfur relay system, suggesting a metabolic shift from hypertrophic growth towards maintenance and repair. Collectively, marine medaka adapts to chronic low salinity through multi-layered remodeling of myofiber architecture, cytoskeletal networks, and integration of antioxidant and autophagy mechanisms. These findings provide a multi-omics framework for understanding muscle plasticity under hypo-osmotic stress and offer candidate targets for optimizing brackish and freshwater aquaculture practices. salinity Oryzias melastigma skeletal muscle transcriptomics metabolomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Salinity is an important abiotic factor in aquatic ecosystems. It primarily affects physiological homeostasis of aquatic organisms by altering osmotic balance thereby exerting profound impacts on metabolic networks, biological rhythms, and adaptive evolution (Li et al. 2022 ). Accumulating evidence indicates that salinity fluctuations systematically regulate multiple molecular and physiological processes in aquatic organisms, including reproduction, survival, distribution, osmoregulation, and gene expression patterns (Kültz 2015 ; Liang et al. 2021 ). Changes in environmental salinity have also been shown to influence tissue composition and morphological traits in fish (Martins et al. 2014 ). For example, in grass carp, increasing salinity significantly decreases the diameter of of skeletal muscle while increasing sarcolemma thickness (Zhang et al. 2021 ). Physiologically, compared to freshwater culture conditions, high-salinity stress markedly upregulates the relative gene expression of Na⁺/K⁺-ATPase and cytosolic carbonic anhydrase in Nile tilapia , accompanied by histopathological damage in gills, liver, and kidney (Mohamed et al. 2021 ). In terms of growth and behavior, African catfish display increased abnormal behaviors as salinity rises, and excessive salinity reduces survival and growth performance (Zidan et al. 2022 ). From an energetic perspective, the reorganization of energy allocation is a key strategy for aquatic animals to cope with salinity changes (Long et al. 2018 ; Ye et al. 2014 ). When salinity variation remains within the tolerance range, organisms must expend substantial energy to maintain internal stability, thereby reducing the energy available for growth and development (Tian et al. 2020 ). However, when salinity changes exceed regulatory capacity, homeostasis is disrupted, triggering inflammatory responses, endoplasmic reticulum stress (ERS), apoptosis, and other physiological injuries (Li et al. 2024 ; Qiang et al. 2013 ). The antioxidant enzyme system is a core defense network against environmental stress, and changes in its activity are widely used as indicators of fish environmental adaptability. Fish antioxidant defenses include both enzymatic and non-enzymatic components (metabolites) and are regulated by hormones (e.g., cortisol, thyroid hormones, insulin-like growth factor) as well as signaling pathways; key enzymes include superoxide dismutase and catalase (Winston 1991 ). Catalase (CAT) decomposes hydrogen peroxide into water and oxygen, preventing the formation of highly toxic hydroxyl radicals while maintaining redox balance (Anwar et al. 2024 ). Malondialdehyde (MDA), a major product of lipid peroxidation, exacerbates oxidative damage to biological membranes and serves as an important biomarker of lipid peroxidation and cellular injury (Grotto et al. 2009 ). Catalase is essential for growth, development, and metabolism (Nandi et al. 2019 ). Previous studies have shown that moderate salinity reduction can stimulate antioxidant enzyme activities in kidney and muscle of juvenile silver pomfret, thereby removing excessive reactive oxygen species (ROS) and alleviating damage; this response is time-dependent and tissue-specific, whereas salinity beyond tolerance may suppress antioxidant enzyme activities (Yin et al. 2011 ). Although the effects of salinity stress have been extensively studied in gills (Zhou et al. 2021 ), gut microbiota (Sun et al. 2023 ), brain (Liu et al. 2018 ), kidney (Zhang et al. 2025 ) and liver gene expression (Liang et al. 2021 ), adaptive mechanisms and regulatory networks in skeletal muscle, a highly energy-demanding tissue, remain poorly understood under low-salinity stress. Therefore, using marine medaka as a model, this study systematically investigates the adaptive responses of skeletal muscle to low salinity, with a particular focus on expression patterns and regulatory networks of muscle growth and development genes. The findings will enhance our understanding of skeletal muscle adaptive evolution in small teleosts under low-salinity environments and provide insights into the molecular basis of salinity adaptation in aquatic organisms. Materials and Methods Ethical statement This study was conducted in accordance with the ethical guidelines of Zhejiang Ocean University (ZJOU) and was approved by the Institutional Ethics Committee of ZJOU. Experimental design and sampling A two-group design was employed, consisting of a low-salinity treatment (2.5‰) and a high-salinity control (25‰). The parental generation ( F₀ ) in the low-salinity group was gradually acclimated to 2.5‰ under laboratory conditions and was stably maintained at this salinity. Their offspring ( F₁ ) were reared exclusively at 2.5‰ for their entire lifespan. In contrast, both the parental and offspring generations in the control group were continuously maintained in natural seawater at 25‰. At the start of the formal experiment, 480 healthy juveniles were randomly selected from each group and distributed into three replicate units (n = 3; 160 fish per unit). Salinity was calibrated weekly using a high-precision conductivity salinometer (±0.1‰). The photoperiod was set to 14 hours of light and 10 hours of darkness (light on from 08:00 to 22:00). Water temperature, pH, and dissolved oxygen levels were maintained at 26.5 ± 0.5°C, 7.5 ± 0.3, and ≥ 6 mg L⁻¹, respectively. Fish were fed a commercial diet twice daily at 9:00 and 15:00. The experiment continued until the fish reached 4 months of age. Fish were fasted for 24 h before sampling and were rapidly anesthetized in an ice-water mixture (0-1°C) until reflexes ceased. Epaxial muscle was dissected on ice from both sides of the lateral line above the neural arches to ensure consistent tissue origin. For biochemical assays, muscle from 10 individuals was pooled as one biological replicate, snap-frozen and stored at -80°C for measuring TAC, MDA and CAT. For transcriptomics, muscle from four individuals per group was pooled and immersed in RNA stabilization solution at room temperature for 30 min, then stored at -80°C for total RNA extraction and gene expression analysis. For metabolome analysis, muscle from twenty individuals per group was pooled and rapidly frozen in liquid nitrogen, then stored at -80°C for subsequent metabolites extraction and analysis. Structure of muscle fibers Histological analysis was conducted following standard paraffin sectioning procedures (Peng et al. 2022). Tissues were fixed in 4% neutral paraformaldehyde for 24 h, dehydrated through graded ethanol, cleared in xylene, and embedded in paraffin. Serial sections (3-4 μm thick) were stained with hematoxylin and eosin (H&E). Stained sections were examined using an Olympus BX53 microscope at 40× magnification. Three non-overlapping fields were randomly selected for each sample. Image J 6.0 was used for morphometric analysis to quantify muscle fiber density (fibers·mm⁻²), mean fiber cross-sectional area (mm²), and the fiber area to gap area ratio. Each parameter was measured three times, and the results were averaged. Ultrastructure was examined using transmission electron microscopy (TEM) (Wang et al. 2019). After dissection, approximately 1 mm³ of dorsal muscle was immediately fixed in 2.5% glutaraldehyde at 4°C, post-fixed in 1% osmium tetroxide prepared in 0.1 M phosphate buffer (PBS, pH 7.4) in the dark, dehydrated in graded ethanol, and then infiltrated and embedded in resin. Ultrathin sections (60-80 nm) were cut, contrasted and imaged using a Hitachi HT7800 TEM. Sarcomere length (μm) and I-band length (μm) were quantified using Image J 6.0. Antioxidant responses CAT activity, TAC and MDA levels in muscle were measured using commercial kits from Nanjing Jiancheng Bioengineering Institute (Nanjing, China). Absorbance was measured using a multimode microplate reader (Spark 10M, Tecan, Switzerland), strictly following the kit instructions. Dorsal epaxial muscle was cleaned of skin and visible connective tissues, homogenized in 9 volumes of PBS (w/v = 1:9) using a frozen tissue grinder (Servicebio, Wuhan, China) at 70 Hz for 3 min. Homogenates were centrifuged at 12,000 g for 15 min at 4°C; and the supernatants were collected for biochemical assays. CAT activity was determined by terminating H₂O₂ decomposition with ammonium molybdate; the residual H₂O₂ reacts to form a light-yellow complex measured at 405 nm. One unit (U) was defined as the decomposition of 1 μmol H₂O₂ per second per mg protein. MDA was quantified using the thiobarbituric acid (TBA) method, forming a red adduct with maximal absorption at 532 nm; results were normalized to protein content. TAC was defined as the activity that increases optical density (OD) by 0.01 per minute at 37°C per mg tissue protein (U). Transcriptomic analysis To evaluate transcriptional responses to long-term low salinity, dorsal muscle from fish maintained at 25‰ and 2.5‰ was subjected to RNA sequencing (RNA-seq) with three biological replicates per group. The workflow included RNA extraction, quality assessment, library construction and Illumina sequencing. Poly(A)+ mRNA was enriched with Oligo(dT) magnetic beads, fragmented, reverse-transcribed using random hexamers to generate first-strand cDNA, followed by second-strand synthesis. Double-stranded cDNA was purified, end-repaired, A-tailed, adapter-ligated, and PCR-amplified to generate final libraries. Clean reads were mapped to the reference genome (GCF_002922805.2). Structural analyses (including alternative splicing, novel gene discovery and gene structure optimization) and expression analyses (including differential expression, functional annotation and enrichment) were performed. Sample naming conventions: C denotes control (high-salinity control) and F denotes low-salinity treatment (low-salinity); biological replicates were labeled C1-C3 and F1-F3. Sequencing data were deposited in the NCBI under BioProject PRJNA1271342 and BioSample accessions SAMN48862424-SAMN48862429. Metabolome analysis Metabolite extraction and LC-QTOF-MS/MS-based metabolomics were conducted following standard procedures. Frozen tissues were thawed on ice until they were cuttable, minced and thoroughly mixed, and 20 ± 1 mg was sampled into a centrifuge tube with a steel bead. Samples were homogenized using a ball mill at 70 Hz for 20 s and then centrifuged at 3000 r/min for 30 s at 4°C. Then, 400 μL of 70% methanol-water extraction solution containing internal standards was added, vortexed at 2500 r/min for 5 min, and incubated on ice for 15 min. Samples were centrifuged at 12,000 r/min for 10 min at 4°C; 300 μL of the supernatant was transferred to a new tube and held at -20°C for 30 min, then centrifuged again for 3 min. Finally, 200 μL of the supernatant was transferred to an autosampler vial insert for analysis. Data were acquired using an UPLC system (ExionLC AD) coupled with tandem mass spectrometry (QTRAP®). Separation was performed using a Waters ACQUITY UPLC BEH HILIC column (1.7 μm, 1 mm × 100 mm) at 40°C, with a flow rate of 0.4 mL/min. Mobile phase A consisted of 20 mM ammonium formate, 10% water, 10% methanol and 80% acetonitrile; mobile phase B consisted of 20 mM ammonium formate, 60% water and 40% acetonitrile. The injection volume was 2 μL. Real-time quantitative PCR To validate RNA-seq results, six differentially expressed genes (DEGs) were randomly selected for qRT-PCR as described by Chen et al (Chen et al. 2022). Gene-specific primers and 18S rRNA primers were designed using Primer 6.0 and are listed in supplementary Table S1. RNA quality was confirmed by agarose gel electrophoresis, which showed clear 18S and 28S bands, with OD260/280 ratios of 1.8-2.1. qRT-PCR was performed on an ABI 7500 real-time system in 96-well plates using SYBR Green PCR Master Mix (Takara, Japan), with three biological replicates per group. Relative expression levels were calculated using the 2 -ΔΔCT method. Statistical analysis All data are presented as Mean ± SEM from three biological replicates. Statistical differences between the two groups were evaluated using Student’s t-test. Differences were considered statistically significant at P < 0.05. Results Histology and ultrastructure of muscle fibers Fig.1A-B show longitudinal sections of dorsal muscle from the high-salinity control and low-salinity groups, respectively. The perimysium subdivided the muscle into fascicles, and regularly aligned fibers with fibrous septa were visible. Based on structural characteristics, the observation area from the dorsal apex was divided into regions A, B and C, with region B designated for primary quantitative analysis. H&E staining showed no obvious differences in regions A and C between the groups, whereas clear group differences were observed in region B. Compared with controls, the low-salinity group dexhibited a looser fiber arrangement, enlarged inter-fiber spaces and a relatively less compact fascicle structure (Fig. 1A-B). Quantification (Fig. 1C-E) indicated that the mean fiber cross-sectional area was significantly reduced ( P <0.05) while fiber density significantly increased ( P <0.05) under low salinity. The fiber area to gap area ratio did not differ significantly. Fig.2A-B present ultrastructural features. TEM revealed orderly sarcomere organization in both groups, with parallel Z-discs and uniform spacing; no structural damage (such as breakage, blurring or serration) was observed, indicating overall sarcomere stability under low salinity. Quantification revealed significant I-band widening in the low-salinity group ( P <0.05; Fig. 2C), while sarcomere length remained approximately 1.51 ± 0.02 μm (mean ± SD, n = 10) with no significant difference (Fig. 2D). These findings indicate subtle remodeling of sarcomeric architecture under chronic low-salinity conditions, without disruption of overall sarcomere integrity. Antioxidant responses TAC and MDA levels were significantly higher in the low-salinity group than in the control group ( P 0.05; Fig. 3C). These results indicate enhanced oxidative stress accompanied by compensatory activation of total antioxidant capacity. Transcriptomics analysis To investigate molecular responses to salinity stress, Illumina paired-end sequencing was performed on dorsal muscle from fish maintained long-term at 25‰ and 2.5‰, with three biological replicates for each condition (six libraries total). After filtering adapters and low-quality reads, each library yielded over 50 million clean reads with Q20 > 98%, indicating high sequencing quality. Clean reads were mapped to the reference genome using HISAT2; with mapping rates ranging from 83.71% to 87.08% (Supplementary Table 1), supporting good coverage and reliability. Differential expression analysis was conducted using high salinity as the control and low salinity as the treatment. After normalization and Benjamini–Hochberg correction (FDR control), DEGs were defined as |log₂Fold Change| ≥ 1 and FDR < 0.05 (DESeq2/edgeR). A total of 1266 DEGs were identified, including 281 upregulated genes and 985 downregulated genes (Fig. 4A). The predominance of downregulated genes suggests that skeletal muscle may reduce energy expenditure by suppressing subsets of metabolic and structural transcripts under chronic hypo-osmotic conditions. GO enrichment analysis indicated that DEGs were mainly associated with muscle structure assembly and contractile function, including desmosomes, myofibrils, contractile fibers, muscle system processes, and myosin filaments (Fig. 4B). KEGG enrichment analysis showed significant clustering in pathways related to cytoskeletal remodeling and signaling, including the cytoskeleton in muscle cells, motor protein complexes, Wnt/β-catenin signaling, and tight junctions (Fig. 4C). Together, these results indicate substantial molecular remodeling of the cytoskeletal and contractile system to maintain structural integrity and coordinated contraction under low salinity. qRT-PCR validation To assess the reliability of RNA-seq, six DEGs were randomly selected for qRT-PCR, using 18S rRNA as the reference gene. qRT-PCR results were highly consistent with RNA-seq data (R = 0.875; Fig. S1), confirming the reliability of the transcriptomic data. Metabolomics analysis Metabolomics (UHPLC-MS/MS) was performed to characterize metabolic remodeling in skeletal muscle (Fig. 5). A total of 1318 quantifiable metabolite precursor ions were identified. Differential analysis identified 112 metabolites with significant differences between low-salinity treatment and high-salinity controls (VIP > 1, |log₂FC| ≥ 1, P < 0.05; Fig. 5B), 59 significant metabolites were upregulated and 53 downregulated, indicating pronounced metabolic reprogramming. POVPC (1-palmitoyl-2-(5′-oxovaleroyl)-sn-glycero-3-phosphocholine), an oxidized phospholipid marker with pro-inflammatory activity, accumulated under low salinity and is known to promote oxidative stress (Lu et al. 2024). 3-Hydroxycoumarin, which can directly scavenge free radicals and inhibit lipid peroxidation, was found to be increased (Yoda 2020). Among the downregulated metabolites, uric acid, an important endogenous water-soluble antioxidant scavenging •OH and ONOO⁻ decreased (Kushiyama et al. 2016),implying altered redox buffering and possible links to energy-sensing pathways. KEGG enrichment analysis suggested that the differential metabolites were mainly involved in efferocytosis/autophagy, mTOR signaling, amino acid metabolism, and the sulfur relay system. These results indicate that chronic low salinity not only reshapes antioxidant-related metabolites but may also influence cellular homeostasis via mTOR-linked energy sensing and autophagy-related remodeling. Discussion Low-salinity is a common environmental challenge for marine fish in estuaries and in desalination-based culture systems. Using marine medaka as a model and integrating histology, ultrastructure, transcriptomics, metabolomics and biochemical analyses, this study systematically elucidated the adaptive strategies of skeletal muscle under chronic low salinity (2.5‰). Low salinity significantly altered muscle microstructure, energy metabolism, and redox homeostasis, activating molecular response networks centered on cytoskeletal remodeling and signaling regulation. Histological and TEM analyses indicated increased fiber density and reduced fiber size in low-salinity fish, reflecting a higher proportion of small-diameter fibers. This pattern contrasts with reports in grass carp, where fiber diameter decreases with increased salinity and slight increases in salinity improve muscle quality (Zhang et al. 2021), suggesting species- and habitat-dependent muscle plasticity strategies. Smaller fiber diameter and higher density can enhance diffusion of oxygen and substrates, potentially improving metabolic activity and oxidative stress resistance (Li et al. 2023). Therefore, by reducing fiber cross-sectional area and increasing fiber number, marine medaka may shorten diffusion distances while maintaining overall muscle volume, facilitating ion and metabolite exchange and improving tolerance to osmotic fluctuations. Ultrastructural observations showed significant changes in the I-band, while sarcomere length remained stable, implying altered actin-myosin overlap and potentially improved force generation per unit area. Classic sliding filament theory suggests that A-band length is relatively constant, whereas extension of thin filaments into the A-band can reduce I- and H-band widths without substantially changing Z-to-Z distance (sarcomere length) (Squire 2016). Active force generation depends on sarcomere length via thick-thin filament overlap (Mead et al. 2020). Therefore, micro-adjustments in thin filament positioning within sarcomeres may represent a key adaptation to optimize contractile efficiency and structural stability under hypo-osmotic stress (Gordon et al. 1966). At the biochemical level, low salinity increased MDA levels, indicating intensified lipid peroxidation and membrane oxidative damage (Chen et al. 2025). Oxidative injury can disrupt membrane integrity (including that of mitochondria), contribute to cellular swelling, and impair myofibrillar organization, ultimately reducing fiber diameter. mTORC1 is a central hub maintaining skeletal muscle mass by promoting protein synthesis and suppressing catabolism; its altered activity can markedly affect hypertrophy and remodeling (Yoon 2017). Given the transcriptomic enrichment involving PI3K-Akt-mTOR-related pathways, it is plausible that oxidative pressure under low salinity modulates translational programs, limiting the synthesis of myofibrillar proteins (e.g., MyHC) and constraining hypertrophy (Agrawal et al. 2023). Meanwhile, elevated TAC likely reflects compensatory activation of the antioxidant defense network to buffer excessive ROS and mitigate secondary damage from lipid peroxidation (Del Rio et al. 2005), The coexistence of high MDA and high TAC suggests a dynamic “damage-repair” balance in muscle tissue. Beyond oxidative stress, osmotic fluctuations impose mechanical challenges on muscle tissue. To preserve cell-cell and cell-matrix adhesion, desmosomes and adherens junctions may undergo rapid assembly and remodeling to resist mechanical stress (Müller et al. 2021; Zimmer and Kowalczyk 2024). Myofibrils can adjust actin filament dynamics to buffer osmotic-mechanical perturbations. The enrichment of desmosome, myofibril, and myosin filament terms supports adaptive structural remodeling. KEGG enrichment analysis in actin cytoskeleton and motor protein pathways further suggests dynamic reconfiguration of contractile machinery to preserve stability and contraction. Previous studies have demonstrated that molecular motors are involved not only in sarcomere contraction, but also in the transport, positioning, and anchoring of organelles such as mitochondria along cytoskeletal tracks, thereby contributing to local ATP supply, organelle homeostasis, and stress recovery capacity (Kruppa and Buss 2021). Thus, the enrichment of motor protein may reflect both contractile adjustments and energy distribution under stress. Metabolomics revealed enrichment in tyrosine metabolism, arginine biosynthesis, and mTOR signaling pathways. Tyrosine catabolism yields fumarate and acetoacetate (glucogenic/ketogenic substrates) and can support energy balance during stress (Chakrapani et al. 2022). The arginine-NO axis participates in metabolic regulation and is linked to vascular control, mitochondrial biogenesis, and antioxidant responses (Moncada and Higgs 1992). Arginine also supports polyamine synthesis and tissue repair (Pegg 2009) and connects multiple pathways via conversion to proline and glutamate (Phang et al. 2015). Differential metabolites were mainly enriched in pathways related to efferocytosis (autophagy), mTOR signaling, and amino acid metabolism, suggesting that long-term low-salinity stress may induce processes such as clearance of damaged cells or debris, structural injury, and metabolic reprogramming in the muscle microenvironment (He 2022). Autophagy is tightly coupled with the regulation of lipid, carbohydrate, and amino acid metabolism (Sheng et al. 2024). In muscle tissue, the enrichment of this pathway may reflect low-salinity–induced cellular damage that requires immune-related clearance mechanisms to reduce secondary inflammation and oxidative stress, thereby facilitating the restoration of tissue homeostasis. Meanwhile, autophagy and lysosome-related processes are closely interconnected with mTOR signaling. As a key negative regulator of autophagy, mTOR enables cells to achieve material recycling and energy redistribution by modulating the mTOR-autophagy network under conditions of nutrient or energy deficiency or elevated oxidative stress (Heras-Sandoval et al. 2014). The role of autophagy has been investigated mainly by focusing on protein degradation. In response to environmental stressors, autophagy is commonly induced and elevated, promoting stress adaptation and maintaining intracellular homeostasis (Kuma and Mizushima 2010). Under normal physiological conditions, autophagy is maintained at a relatively low basal level, but its activity can be induced by various stress stimuli. Accumulating evidence indicates that Autophagy is upregulated in response to extra- or intracellular stress and signals such as starvation, growth factor deprivation, ER stress, and pathogen infection (He and Klionsky 2009). Previous studies have also shown that the sulfur transfer system in oysters is closely coupled with glutathione metabolism, jointly maintaining intracellular sulfur homeostasis and antioxidant capacity, and playing a regulatory role under heavy metal stress (Dong et al. 2024). Together with transcriptomic enrichment in Wnt and mTOR pathways, these data imply coordinated regulation of structural repair and anabolic/catabolic balance. Wnt/β-catenin signaling is essential for organizing centers during zebrafish fin regeneration (Wehner et al. 2014); and induces satellite cell proliferation in adult muscle regeneration (Otto et al. 2008). Therefore, chronic low salinity may induce micro-damage and trigger transcriptional programs associated with regeneration. Additionally, the apelin/APJ system promotes skeletal formation, muscle metabolism, and myogenesis (Luo et al. 2021). Combined with the enrichment of PI3K-Akt-mTOR-related pathways observed in this study, it can be inferred that apelin-associated upregulation under low-salinity conditions may contribute to maintaining muscle protein homeostasis and adaptive energy metabolism. This regulation may help limit excessive proteolysis and support structural maintenance under stressful conditions. Taken together, the present results support a model in which chronic low salinity induces coordinated remodeling of skeletal muscle at morphological, biochemical, transcriptional, and metabolic levels (Figure 6). Rather than favoring hypertrophic growth, low-salinity exposure appears to shift muscle toward a maintenance-oriented state characterized by reduced fiber size, cytoskeletal reorganization, elevated oxidative pressure, and activation of redox buffering and autophagy-associated pathways. Conclusions This study demonstrates that chronic low-salinity exposure induces marked skeletal muscle remodeling in marine medaka. Low salinity reduced myofiber cross-sectional area, increased fiber density, and widened the I-band without affecting sarcomere length, indicating structural adjustment of muscle fibers under hypo-osmotic conditions. In addition, elavated TAC and MDA levels suggested disturbed redox homeostasis and enhanced lipid peroxidation, accompanied by compensatory antioxidant responses. Transcriptomic and metabolomic analyses further revealed extensive molecular changes, particularly in pathways related to cytoskeletal organization, Wnt signaling, mTOR signaling, autophagy, and amino acid metabolism. These results indicate that chronic low salinity affects both muscle structure and metabolic homeostasis in marine medaka, and that skeletal muscle adaptation involves coordinated morphological, biochemical, and molecular responses. This study provides new evidence for understanding skeletal muscle plasticity in euryhaline fish under long-term low-salinity stress. Declarations Author Contribution Tian-Hong Chen conducted the research with assitance from Qing-Hao Zhan, Xiao-Yu Zeng and Ning-Ning Ma, Qi-Liang Li and Run-Jie Jin. The first draft of the manuscript was written by Tian-Hong Chen. All authors provided comments on previous versions of the manuscript. All authors read and approved the final manuscript. Jia-Lang Zheng and Qing-Ling Zhu obtained the fund and supervised the research. Funding The study was funded by the Bureau of Science and Technology of Zhoushan (No. 2023C41005) and National Key Research and Development Program of China (No. 2025YFD2400500). Data Availability The data will be available upon reasonable request to the corresponding author. Competing Interests The authors declare no competing interests. References Agrawal S, Chakole S, Shetty N, Prasad R, Lohakare T, Wanjari M (2023) Exploring the role of oxidative stress in skeletal muscle atrophy: mechanisms and implications. Cureus 15(7). https://doi.org/10.7759/cureus.42178 Anwar S, Alrumaihi F, Sarwar T, Babiker AY, Khan AA, Prabhu SV, Rahmani AH (2024) Exploring therapeutic potential of catalase: Strategies in disease prevention and management. 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Cell reports 6(3):467-481. https://doi.org/10.1016/j.celrep.2013.12.036 Winston GW (1991) Oxidants and antioxidants in aquatic animals. Comparative biochemistry and physiology C, Comparative pharmacology and toxicology 100(1-2):173-176. https://doi.org/10.1016/0742-8413(91)90148-m Ye Y, An Y, Li R, Mu C, Wang C (2014) Strategy of metabolic phenotype modulation in Portunus trituberculatus exposed to low salinity. Journal of agricultural and food chemistry 62(15):3496-3503. https://doi.org/10.1021/jf405668a Yin F, Peng S, Sun P, Shi Z (2011) Effects of low salinity on antioxidant enzymes activities in kidney and muscle of juvenile silver pomfret Pampus argenteus . Acta Ecologica Sinica 31(1):55-60. https://doi.org/10.1016/j.chnaes.2010.11.009 Yoda J (2020) Overview of recent advances in 3-hydroxycoumarin chemistry as a bioactive heterocyclic compound. Am J Heterocycl Chem 6(1):6. https://doi.org/10.11648/j.ajhc.20200601.12 Yoon M-S (2017) mTOR as a key regulator in maintaining skeletal muscle mass. Frontiers in physiology 8:788. https://doi.org/10.3389/fphys.2017.00788 Zhang X, Shen Z, Qi T, Xi R, Liang X, Li L, Tang R, Li D (2021) Slight increases in salinity improve muscle quality of grass carp ( Ctenopharyngodon idellus ). Fishes 6(1):7. https://doi.org/10.3390/fishes6010007 Zhang Y, Zhang J, Tan Y, Wang X, Chen H, Yu H, Chen F, Yan X, Sun J, Luo J (2025) Kidney transcriptome analysis reveals the molecular responses to salinity adaptation in largemouth bass ( Micropterus salmoides ). Comparative Biochemistry and Physiology Part D: Genomics and Proteomics 53:101362. https://doi.org/10.1016/j.cbd.2024.101362 Zhou Z, Hu F, Li W, Yang X, Hallerman E, Huang Z (2021) Effects of salinity on growth, hematological parameters, gill microstructure and transcriptome of fat greenling Hexagrammos otakii . Aquaculture 531:735945. https://doi.org/10.1016/j.aquaculture.2020.735945 Zidan EM, Goma AA, Tohamy HG, Soliman MM, Shukry M (2022) Insight study on the impact of different salinity levels on behavioural responses, biochemical stress parameters and growth performance of African catfish ( Clarias gariepinus ). Aquaculture Research 53(7):2750-2759. https://doi.org/10.1111/are.15790 Zimmer SE, Kowalczyk AP (2024) The desmosome as a dynamic membrane domain. Current Opinion in Cell Biology 90:102403. https://doi.org/10.1016/j.ceb.2024.102403 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 May, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Submission checks completed at journal 27 Mar, 2026 First submitted to journal 24 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9208878","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622783247,"identity":"190057a0-af6c-497a-a3e2-ca12dd942d73","order_by":0,"name":"Tian-Hong Chen","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Tian-Hong","middleName":"","lastName":"Chen","suffix":""},{"id":622783248,"identity":"a55867f7-2efe-4ecc-9dc2-1911676c9197","order_by":1,"name":"Qing-Hao Zhan","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Qing-Hao","middleName":"","lastName":"Zhan","suffix":""},{"id":622783249,"identity":"a937cb7f-a5f3-4ed1-b0de-cf4c28c16771","order_by":2,"name":"Xiao-Yu Zeng","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Xiao-Yu","middleName":"","lastName":"Zeng","suffix":""},{"id":622783250,"identity":"65716eea-a222-4081-b53d-7068ef7555f1","order_by":3,"name":"Ning-Ning Ma","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Ning-Ning","middleName":"","lastName":"Ma","suffix":""},{"id":622783251,"identity":"1931c01e-3384-4972-9993-68f09115c225","order_by":4,"name":"Qi-Liang Li","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Qi-Liang","middleName":"","lastName":"Li","suffix":""},{"id":622783252,"identity":"20616902-92ec-43de-8735-aa430d10c548","order_by":5,"name":"Run-Jie Jin","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Run-Jie","middleName":"","lastName":"Jin","suffix":""},{"id":622783253,"identity":"afdf5e26-9e85-4e94-80c0-bb3a2299750a","order_by":6,"name":"Jia-Lang Zheng","email":"","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Jia-Lang","middleName":"","lastName":"Zheng","suffix":""},{"id":622783254,"identity":"d4025814-e62f-4789-afaa-424929097c3f","order_by":7,"name":"Qing-Ling Zhu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIie3QsQrCMBCA4ZRCXKJzQDGvEHHt4KOkCO3UvWOKkCx9gE4+hvPFrH0DHeziLLh0UWwXQRC80SH/fB/HHSGh0F8Wa7iVyZJOLGBJVLmmzdYz1io02fmpOaZ7vpE4IGyqgVHIDSeK9OUBsaPuNHB2Lsy8gqhuT79JzIctkl8LswAVRwZB6EiU9DnlSuIIGwkor/CEs047DdnKDE92qFuE3fr745kIYa279CWCkOG17wAz/0lCoVAo9LUXcoFCem4n5LIAAAAASUVORK5CYII=","orcid":"","institution":"Zhejiang Ocean University","correspondingAuthor":true,"prefix":"","firstName":"Qing-Ling","middleName":"","lastName":"Zhu","suffix":""}],"badges":[],"createdAt":"2026-03-24 08:23:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9208878/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9208878/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107417945,"identity":"9efad740-cb24-4ac4-97d4-91bad231541a","added_by":"auto","created_at":"2026-04-21 10:08:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":453272,"visible":true,"origin":"","legend":"\u003cp\u003eHistological characteristics of dorsal muscle in marine medaka under high-salinity control (25 ‰) and low-salinity treatment (2.5 ‰). (A-B) H\u0026amp;E-stained cross-sections of dorsal muscle, (C) Mean myofiber cross-sectional area, (D) fiber density, and (E) fiber area/gap area ratio. Asterisks indicate significant differences between groups at p \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/6c3b5bf2663e569690439533.png"},{"id":107418090,"identity":"6556e153-42f9-4e40-91ce-27b6ffbe5963","added_by":"auto","created_at":"2026-04-21 10:09:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":330114,"visible":true,"origin":"","legend":"\u003cp\u003eUltrastructural characteristics of dorsal skeletal muscle in marine medaka under chronic low salinity. (A-B) TEM images showing I-band (I), Z-disc (Z) and sarcomere length (SL) under seawater control and low-salinity treatment. (C) Quantification of I-band length. (D) Quantification of sarcomere length. Asterisks indicate significant differences between groups at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/a84f64d8f6079e8ca435ed3b.png"},{"id":107418248,"identity":"1d8bdf8f-f668-4ee5-a91f-c8d89bd751a8","added_by":"auto","created_at":"2026-04-21 10:10:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39364,"visible":true,"origin":"","legend":"\u003cp\u003eOxidative stress-related biochemical responses in dorsal skeletal muscle of marine medaka under chronic low salinity. (A) Total antioxidant capacity (TAC). (B) Malondialdehyde (MDA) levels. (C) Catalase (CAT) activity. Asterisks indicate significant differences between groups at \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/3ffa1b7863816e976ea3fcd8.png"},{"id":107417960,"identity":"1ab709be-b926-4830-a0fb-f7ebf2ded56e","added_by":"auto","created_at":"2026-04-21 10:08:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":144644,"visible":true,"origin":"","legend":"\u003cp\u003eTranscriptomic responses of dorsal skeletal muscle to chronic low-salinity stress in marine medaka. (A) Summary of differentially expressed genes (DEGs). (B) GO enrichment analysis of DEGs. (C) KEGG pathway enrichment analysis of DEGs.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/b03717ca4f8381031bf21b39.png"},{"id":107417958,"identity":"64fd8078-70d5-4e21-9a1c-f6ca2d900aa1","added_by":"auto","created_at":"2026-04-21 10:08:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":172228,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolomic responses of dorsal skeletal muscle to chronic low-salinity stress in marine medaka. (A) Principal component analysis (PCA). (B) Volcano plot of differential metabolites. (C) Top 30 differential metabolites. (D) KEGG pathway enrichment analysis of differential metabolites.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/63fa8cff7f23b6488a6e2536.png"},{"id":107418008,"identity":"ec3c8b6a-e449-4b88-b23e-2b6c897ed145","added_by":"auto","created_at":"2026-04-21 10:09:06","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":223341,"visible":true,"origin":"","legend":"\u003cp\u003eProposed model of skeletal muscle adaptation to chronic low-salinity stress in marine medaka (\u003cem\u003eOryzias melastigma\u003c/em\u003e). Chronic low salinity induces osmotic and oxidative challenges in skeletal muscle, leading to reduced myofiber size, increased fiber density, I-band widening, enhanced total antioxidant capacity, elevated lipid peroxidation, and broad transcriptomic-metabolomic reprogramming. These coordinated responses suggest a shift from growth-oriented processes toward maintenance, repair, and functional stabilization under prolonged hypo-osmotic stress.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/c5a5b021376a5d2cb9cf92b8.png"},{"id":107418745,"identity":"5c86c3aa-608d-4821-a466-57f9f3299ce0","added_by":"auto","created_at":"2026-04-21 10:11:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1524914,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/37e43bd9-a866-4434-9f32-f99d1b2009d2.pdf"},{"id":107417944,"identity":"1be97697-8c04-4e29-a77c-bc042433b843","added_by":"auto","created_at":"2026-04-21 10:08:36","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":23943,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-9208878/v1/d9e2f754aa3196f84d726a0c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biochemical and Multi-Omics Analyses Reveal Skeletal Muscle Adaptation to Chronic Low-Salinity Stress of Marine Medaka (Oryzias melastigma)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSalinity is an important abiotic factor in aquatic ecosystems. It primarily affects physiological homeostasis of aquatic organisms by altering osmotic balance thereby exerting profound impacts on metabolic networks, biological rhythms, and adaptive evolution (Li et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Accumulating evidence indicates that salinity fluctuations systematically regulate multiple molecular and physiological processes in aquatic organisms, including reproduction, survival, distribution, osmoregulation, and gene expression patterns (K\u0026uuml;ltz \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Liang et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Changes in environmental salinity have also been shown to influence tissue composition and morphological traits in fish (Martins et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For example, in grass carp, increasing salinity significantly decreases the diameter of of skeletal muscle while increasing sarcolemma thickness (Zhang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Physiologically, compared to freshwater culture conditions, high-salinity stress markedly upregulates the relative gene expression of Na⁺/K⁺-ATPase and cytosolic carbonic anhydrase in \u003cem\u003eNile tilapia\u003c/em\u003e, accompanied by histopathological damage in gills, liver, and kidney (Mohamed et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In terms of growth and behavior, African catfish display increased abnormal behaviors as salinity rises, and excessive salinity reduces survival and growth performance (Zidan et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). From an energetic perspective, the reorganization of energy allocation is a key strategy for aquatic animals to cope with salinity changes (Long et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ye et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen salinity variation remains within the tolerance range, organisms must expend substantial energy to maintain internal stability, thereby reducing the energy available for growth and development (Tian et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, when salinity changes exceed regulatory capacity, homeostasis is disrupted, triggering inflammatory responses, endoplasmic reticulum stress (ERS), apoptosis, and other physiological injuries (Li et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Qiang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The antioxidant enzyme system is a core defense network against environmental stress, and changes in its activity are widely used as indicators of fish environmental adaptability. Fish antioxidant defenses include both enzymatic and non-enzymatic components (metabolites) and are regulated by hormones (e.g., cortisol, thyroid hormones, insulin-like growth factor) as well as signaling pathways; key enzymes include superoxide dismutase and catalase (Winston \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Catalase (CAT) decomposes hydrogen peroxide into water and oxygen, preventing the formation of highly toxic hydroxyl radicals while maintaining redox balance (Anwar et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Malondialdehyde (MDA), a major product of lipid peroxidation, exacerbates oxidative damage to biological membranes and serves as an important biomarker of lipid peroxidation and cellular injury (Grotto et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Catalase is essential for growth, development, and metabolism (Nandi et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Previous studies have shown that moderate salinity reduction can stimulate antioxidant enzyme activities in kidney and muscle of juvenile silver pomfret, thereby removing excessive reactive oxygen species (ROS) and alleviating damage; this response is time-dependent and tissue-specific, whereas salinity beyond tolerance may suppress antioxidant enzyme activities (Yin et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough the effects of salinity stress have been extensively studied in gills (Zhou et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), gut microbiota (Sun et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), brain (Liu et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), kidney (Zhang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and liver gene expression (Liang et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), adaptive mechanisms and regulatory networks in skeletal muscle, a highly energy-demanding tissue, remain poorly understood under low-salinity stress. Therefore, using marine medaka as a model, this study systematically investigates the adaptive responses of skeletal muscle to low salinity, with a particular focus on expression patterns and regulatory networks of muscle growth and development genes. The findings will enhance our understanding of skeletal muscle adaptive evolution in small teleosts under low-salinity environments and provide insights into the molecular basis of salinity adaptation in aquatic organisms.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eEthical statement\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical guidelines of Zhejiang Ocean University (ZJOU) and was approved by the Institutional Ethics Committee of ZJOU.\u003c/p\u003e\n\u003cp\u003eExperimental design and sampling\u003c/p\u003e\n\u003cp\u003eA two-group design was employed, consisting of a low-salinity treatment (2.5‰) and a high-salinity control (25‰). The parental generation (\u003cem\u003eF₀\u003c/em\u003e) in the low-salinity group was gradually acclimated to 2.5‰ under laboratory conditions and was stably maintained at this salinity. Their offspring (\u003cem\u003eF₁\u003c/em\u003e) were reared exclusively at 2.5‰ for their entire lifespan. In contrast, both the parental and offspring generations in the control group were continuously maintained in natural seawater at 25‰.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the start of the formal experiment, 480 healthy juveniles were randomly selected from each group and distributed into three replicate units (n = 3; 160 fish per unit). Salinity was calibrated weekly using a high-precision conductivity salinometer (±0.1‰). The photoperiod was set to 14 hours of light and 10 hours of darkness (light on from 08:00 to 22:00). Water temperature, pH, and dissolved oxygen levels were maintained at 26.5 ± 0.5°C, 7.5 ± 0.3, and ≥ 6 mg L⁻¹, respectively. Fish were fed a commercial diet twice daily at 9:00 and 15:00. The experiment continued until the fish reached 4 months of age.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFish were fasted for 24 h before sampling and were rapidly anesthetized in an ice-water mixture (0-1°C) until reflexes ceased. Epaxial muscle was dissected on ice from both sides of the lateral line above the neural arches to ensure consistent tissue origin. For biochemical assays, muscle from 10 individuals was pooled as one biological replicate, snap-frozen and stored at -80°C for measuring TAC, MDA and CAT. For transcriptomics, muscle from four individuals per group was pooled and immersed in RNA stabilization solution at room temperature for 30 min, then stored at -80°C for\u0026nbsp;total RNA extraction and gene expression analysis. For metabolome analysis, muscle from twenty individuals per group was pooled and rapidly frozen in liquid nitrogen, then stored at -80°C for subsequent metabolites extraction and analysis.\u003c/p\u003e\n\u003cp\u003eStructure of muscle fibers\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHistological analysis was conducted following standard paraffin sectioning procedures\u0026nbsp;(Peng et al. 2022). Tissues were fixed in 4% neutral paraformaldehyde for 24 h, dehydrated through graded ethanol, cleared in xylene, and embedded in paraffin. Serial sections (3-4 μm thick) were stained with hematoxylin and eosin (H\u0026amp;E). Stained sections were examined using an Olympus BX53 microscope at 40× magnification. Three non-overlapping fields were randomly selected for each sample. Image J 6.0 was used for morphometric analysis to quantify muscle fiber density (fibers·mm⁻²), mean fiber cross-sectional area (mm²), and the fiber area to gap area ratio. Each parameter was measured three times, and the results were averaged.\u003c/p\u003e\n\u003cp\u003eUltrastructure was examined using transmission electron microscopy (TEM) (Wang et al. 2019). After dissection, approximately 1 mm³ of dorsal muscle was immediately fixed in 2.5% glutaraldehyde at 4°C, post-fixed in 1% osmium tetroxide prepared in 0.1 M phosphate buffer (PBS, pH 7.4) in the dark, dehydrated in graded ethanol, and then infiltrated and embedded in resin. Ultrathin sections (60-80 nm) were cut, contrasted and imaged using a Hitachi HT7800 TEM. Sarcomere length (μm) and I-band length (μm) were quantified using Image J 6.0.\u003c/p\u003e\n\u003cp\u003eAntioxidant responses\u003c/p\u003e\n\u003cp\u003eCAT activity, TAC and MDA levels in muscle were measured using commercial kits from Nanjing Jiancheng Bioengineering Institute (Nanjing, China). Absorbance was measured using a multimode microplate reader (Spark 10M, Tecan, Switzerland), \u0026nbsp;strictly following the kit instructions. Dorsal epaxial muscle was cleaned of skin and visible connective tissues, homogenized in 9 volumes of PBS (w/v = 1:9) using a frozen tissue grinder (Servicebio, Wuhan, China) at 70 Hz for 3 min. Homogenates were centrifuged at 12,000 g for 15 min at 4°C; and the supernatants were collected for biochemical assays. CAT activity was determined by terminating H₂O₂ decomposition with ammonium molybdate; the residual H₂O₂ reacts to form a light-yellow complex measured at 405 nm. One unit (U) was defined as the decomposition of 1 μmol H₂O₂ per second per mg protein. MDA was quantified using the thiobarbituric acid (TBA) method, forming a red adduct with maximal absorption at 532 nm; results were normalized to protein content. TAC was defined as the activity that increases optical density (OD) by 0.01 per minute at 37°C per mg tissue protein (U).\u003c/p\u003e\n\u003cp\u003eTranscriptomic analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo evaluate transcriptional responses to long-term low salinity, dorsal muscle from fish maintained at 25‰ and 2.5‰ was subjected to RNA sequencing (RNA-seq) with three biological replicates per group. The workflow included RNA extraction, quality assessment, library construction and Illumina sequencing. Poly(A)+ mRNA was enriched with Oligo(dT) magnetic beads, fragmented, reverse-transcribed using random hexamers to generate first-strand cDNA, followed by second-strand synthesis. Double-stranded cDNA was purified, end-repaired, A-tailed, adapter-ligated, and PCR-amplified to generate final libraries. Clean reads were mapped to the reference genome (GCF_002922805.2). Structural analyses (including alternative splicing, novel gene discovery and gene structure optimization) and expression analyses (including differential expression, functional annotation and enrichment) were performed. Sample naming conventions: C denotes control (high-salinity control) and F denotes low-salinity treatment (low-salinity); biological replicates were labeled C1-C3 and F1-F3. Sequencing data were deposited in the NCBI under BioProject PRJNA1271342 and BioSample accessions SAMN48862424-SAMN48862429.\u003c/p\u003e\n\u003cp\u003eMetabolome analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMetabolite extraction and LC-QTOF-MS/MS-based metabolomics were conducted following standard procedures. Frozen tissues were thawed on ice until they were cuttable, minced and thoroughly mixed, and 20 ± 1 mg was sampled into a centrifuge tube with a steel bead. Samples were homogenized using a ball mill at 70 Hz for 20 s and then centrifuged at 3000 r/min for 30 s at 4°C. Then, 400 μL of 70% methanol-water extraction solution containing internal standards was added, vortexed at 2500 r/min for 5 min, and incubated on ice for 15 min. Samples were centrifuged at 12,000 r/min for 10 min at 4°C; 300 μL of the supernatant was transferred to a new tube and held at -20°C for 30 min, then centrifuged again for 3 min. Finally, 200 μL of the supernatant was transferred to an autosampler vial insert for analysis.\u003c/p\u003e\n\u003cp\u003eData were acquired using an UPLC system (ExionLC AD) coupled with tandem mass spectrometry (QTRAP®). Separation was performed using a Waters ACQUITY UPLC BEH HILIC column (1.7 μm, 1 mm × 100 mm) at 40°C, with a flow rate of 0.4 mL/min. Mobile phase A consisted of 20 mM ammonium formate, 10% water, 10% methanol and 80% acetonitrile; mobile phase B consisted of 20 mM ammonium formate, 60% water and 40% acetonitrile. The injection volume was 2 μL.\u003c/p\u003e\n\u003cp\u003eReal-time quantitative PCR\u003c/p\u003e\n\u003cp\u003eTo validate RNA-seq results, six differentially expressed genes (DEGs) were randomly selected for qRT-PCR as described by Chen et al (Chen et al. 2022). Gene-specific primers and 18S rRNA primers were designed using Primer 6.0 and are listed in supplementary Table S1. RNA quality was confirmed by agarose gel electrophoresis, which showed clear 18S and 28S bands, with OD260/280 ratios of 1.8-2.1. qRT-PCR was performed on an ABI 7500 real-time system in 96-well plates using SYBR Green PCR Master Mix (Takara, Japan), with three biological replicates per group. Relative expression levels were calculated using the 2\u003csup\u003e-ΔΔCT\u003c/sup\u003e method.\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eAll data are presented as Mean ± SEM from three biological replicates. Statistical differences between the two groups were evaluated using Student’s t-test. Differences were considered statistically significant at P \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eHistology and ultrastructure of muscle fibers\u003c/p\u003e\n\u003cp\u003eFig.1A-B\u0026nbsp;show longitudinal sections of dorsal muscle from the high-salinity control and low-salinity groups, respectively. The perimysium subdivided the muscle into fascicles, and regularly aligned fibers with fibrous septa were visible. Based on structural characteristics, the observation area from the dorsal apex was divided into regions A, B and C, with region B designated for primary quantitative analysis. H\u0026amp;E staining showed no obvious differences in regions A and C between the groups, whereas clear group differences were observed in region B. Compared with controls, the low-salinity group dexhibited a looser fiber arrangement, enlarged inter-fiber spaces and a relatively less compact fascicle structure (Fig. 1A-B). Quantification (Fig. 1C-E) indicated that the mean fiber cross-sectional area was significantly reduced (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) while fiber density significantly increased (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) under low salinity. The fiber area to gap area ratio did not differ significantly.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFig.2A-B\u0026nbsp;present ultrastructural features. TEM revealed orderly sarcomere organization in both groups, with parallel Z-discs and uniform spacing; no structural damage (such as breakage, blurring or serration) was observed, indicating overall sarcomere stability under low salinity. Quantification revealed significant I-band widening in the low-salinity group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; Fig. 2C), while sarcomere length remained approximately 1.51 ± 0.02 μm (mean ± SD, n = 10) with no significant difference (Fig. 2D). These findings indicate subtle remodeling of sarcomeric architecture under chronic low-salinity conditions, without disruption of overall sarcomere integrity.\u003c/p\u003e\n\u003cp\u003eAntioxidant responses\u003c/p\u003e\n\u003cp\u003eTAC and MDA levels were significantly higher in the low-salinity group than in the control group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; Fig. 3A-B), whereas CAT activity did not differ significantly between groups ((\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05; Fig. 3C). These results indicate enhanced oxidative stress accompanied by compensatory activation of total antioxidant capacity.\u003c/p\u003e\n\u003cp\u003eTranscriptomics analysis\u003c/p\u003e\n\u003cp\u003eTo investigate molecular responses to salinity stress, Illumina paired-end sequencing was performed on dorsal muscle from fish maintained long-term at 25‰ and 2.5‰, \u0026nbsp;with three biological replicates for each condition (six libraries total). After filtering adapters and low-quality reads, each library yielded over 50 million clean reads with Q20 \u0026gt; 98%, indicating high sequencing quality. Clean reads were mapped to the reference genome using HISAT2; with mapping rates ranging from 83.71% to 87.08% (Supplementary Table 1), supporting good coverage and reliability. Differential expression analysis was conducted using high salinity as the control and low salinity as the treatment. After normalization and Benjamini–Hochberg correction (FDR control), DEGs were defined as |log₂Fold Change| ≥ 1 and FDR \u0026lt; 0.05 (DESeq2/edgeR). A total of 1266 DEGs were identified, including 281 upregulated genes and 985 downregulated genes\u0026nbsp;(Fig. 4A). The predominance of downregulated genes suggests that skeletal muscle may reduce energy expenditure by suppressing subsets of metabolic and structural transcripts under chronic hypo-osmotic conditions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGO enrichment analysis indicated that DEGs were mainly associated with muscle structure assembly and contractile function, including desmosomes, myofibrils, contractile fibers, muscle system processes, and myosin filaments (Fig. 4B). KEGG enrichment analysis showed significant clustering in pathways related to cytoskeletal remodeling and signaling, including the cytoskeleton in muscle cells, motor protein complexes, Wnt/β-catenin signaling, and tight junctions\u0026nbsp;(Fig. 4C). Together, these results indicate substantial molecular remodeling of the cytoskeletal and contractile system to maintain structural integrity and coordinated contraction under low salinity.\u003c/p\u003e\n\u003cp\u003eqRT-PCR validation\u003c/p\u003e\n\u003cp\u003eTo assess the reliability of RNA-seq, six DEGs were randomly selected for qRT-PCR, using 18S rRNA as the reference gene. qRT-PCR results were highly consistent with RNA-seq data (R = 0.875; Fig. S1), confirming the reliability of the transcriptomic data.\u003c/p\u003e\n\u003cp\u003eMetabolomics analysis\u003c/p\u003e\n\u003cp\u003eMetabolomics (UHPLC-MS/MS) was performed to characterize metabolic remodeling in skeletal muscle (Fig. 5). A total of 1318 quantifiable metabolite precursor ions were identified. Differential analysis identified 112 metabolites with significant differences between low-salinity treatment and high-salinity controls (VIP \u0026gt; 1, |log₂FC| ≥ 1, P \u0026lt; 0.05; Fig. 5B), 59 significant metabolites were upregulated and 53 downregulated, indicating pronounced metabolic reprogramming. POVPC (1-palmitoyl-2-(5′-oxovaleroyl)-sn-glycero-3-phosphocholine), an oxidized phospholipid marker with pro-inflammatory activity, accumulated under low salinity and is known to promote oxidative stress (Lu et al. 2024). 3-Hydroxycoumarin, which can directly scavenge free radicals and inhibit lipid peroxidation, was found to be increased (Yoda 2020). Among the downregulated metabolites, uric acid, an important endogenous water-soluble antioxidant scavenging •OH and ONOO⁻ decreased (Kushiyama et al. 2016),implying altered redox buffering and possible links to energy-sensing pathways.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKEGG enrichment analysis suggested that the differential metabolites were mainly involved in efferocytosis/autophagy, mTOR signaling, amino acid metabolism, and the sulfur relay system. These results indicate that chronic low salinity not only reshapes antioxidant-related metabolites but may also influence cellular homeostasis via mTOR-linked energy sensing and autophagy-related remodeling.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLow-salinity is a common environmental challenge for marine fish in estuaries and in desalination-based culture systems. Using marine medaka as a model and integrating histology, ultrastructure, transcriptomics, metabolomics and biochemical analyses, this study systematically elucidated the adaptive strategies of skeletal muscle under chronic low salinity (2.5\u0026permil;). Low salinity significantly altered muscle microstructure, energy metabolism, and redox homeostasis, activating molecular response networks centered on cytoskeletal remodeling and signaling regulation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHistological and TEM analyses indicated increased fiber density and reduced fiber size in low-salinity fish, reflecting a higher proportion of small-diameter fibers. This pattern contrasts with reports in grass carp, where fiber diameter decreases with increased salinity and slight increases in salinity improve muscle quality (Zhang et al. 2021), suggesting species- and habitat-dependent muscle plasticity strategies. Smaller fiber diameter and higher density can enhance diffusion of oxygen and substrates, potentially improving metabolic activity and oxidative stress resistance (Li et al. 2023). Therefore, by reducing fiber cross-sectional area and increasing fiber number, marine medaka may shorten diffusion distances while maintaining overall muscle volume, facilitating ion and metabolite exchange and improving tolerance to osmotic fluctuations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUltrastructural observations showed significant changes in the I-band, while sarcomere length remained stable, implying altered actin-myosin overlap and potentially improved force generation per unit area. Classic sliding filament theory suggests that A-band length is relatively constant, whereas extension of thin filaments into the A-band can reduce I- and H-band widths without substantially changing Z-to-Z distance (sarcomere length) (Squire 2016). Active force generation depends on sarcomere length via thick-thin filament overlap (Mead et al. 2020). Therefore, micro-adjustments in thin filament positioning within sarcomeres may represent a key adaptation to optimize contractile efficiency and structural stability under hypo-osmotic stress (Gordon et al. 1966).\u003c/p\u003e\n\u003cp\u003eAt the biochemical level, low salinity increased MDA levels, indicating intensified lipid peroxidation and membrane oxidative damage (Chen et al. 2025). Oxidative injury can disrupt membrane integrity (including that of mitochondria), contribute to cellular swelling, and impair myofibrillar organization, ultimately reducing fiber diameter. mTORC1 is a central hub maintaining skeletal muscle mass by promoting protein synthesis and suppressing catabolism; its altered activity can markedly affect hypertrophy and remodeling (Yoon 2017). Given the transcriptomic enrichment involving PI3K-Akt-mTOR-related pathways, it is plausible that oxidative pressure under low salinity modulates translational programs, limiting the synthesis of myofibrillar proteins (e.g., MyHC) and constraining hypertrophy (Agrawal et al. 2023). Meanwhile, elevated TAC likely reflects compensatory activation of the antioxidant defense network to buffer excessive ROS and mitigate secondary damage from lipid peroxidation (Del Rio et al. 2005), The coexistence of high MDA and high TAC suggests a dynamic \u0026ldquo;damage-repair\u0026rdquo; balance in muscle tissue.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBeyond oxidative stress, osmotic fluctuations impose mechanical challenges on muscle tissue. To preserve cell-cell and cell-matrix adhesion, desmosomes and adherens junctions may undergo rapid assembly and remodeling to resist mechanical stress (M\u0026uuml;ller et al. 2021; Zimmer and Kowalczyk 2024). Myofibrils can adjust actin filament dynamics to buffer osmotic-mechanical perturbations. The enrichment of desmosome, myofibril, and myosin filament terms supports adaptive structural remodeling. KEGG enrichment analysis in actin cytoskeleton and motor protein pathways further suggests dynamic reconfiguration of contractile machinery to preserve stability and contraction. Previous studies have demonstrated that molecular motors are involved not only in sarcomere contraction, but also in the transport, positioning, and anchoring of organelles such as mitochondria along cytoskeletal tracks, thereby contributing to local ATP supply, organelle homeostasis, and stress recovery capacity (Kruppa and Buss 2021). Thus, the enrichment of motor protein may reflect both contractile adjustments and energy distribution under stress.\u003c/p\u003e\n\u003cp\u003eMetabolomics revealed enrichment in tyrosine metabolism, arginine biosynthesis, and mTOR signaling pathways. Tyrosine catabolism yields fumarate and acetoacetate (glucogenic/ketogenic substrates) and can support energy balance during stress (Chakrapani et al. 2022). The arginine-NO axis participates in metabolic regulation and is linked to vascular control, mitochondrial biogenesis, and antioxidant responses \u0026nbsp;(Moncada and Higgs 1992). Arginine also supports polyamine synthesis and tissue repair (Pegg 2009) and connects multiple pathways via conversion to proline and glutamate (Phang et al. 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDifferential metabolites were mainly enriched in pathways related to efferocytosis (autophagy), mTOR signaling, and amino acid metabolism, suggesting that long-term low-salinity stress may induce processes such as clearance of damaged cells or debris, structural injury, and metabolic reprogramming in the muscle microenvironment (He 2022). Autophagy is tightly coupled with the regulation of lipid, carbohydrate, and amino acid metabolism (Sheng et al. 2024). In muscle tissue, the enrichment of this pathway may reflect low-salinity\u0026ndash;induced cellular damage that requires immune-related clearance mechanisms to reduce secondary inflammation and oxidative stress, thereby facilitating the restoration of tissue homeostasis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMeanwhile, autophagy and lysosome-related processes are closely interconnected with mTOR signaling. As a key negative regulator of autophagy, mTOR enables cells to achieve material recycling and energy redistribution by modulating the mTOR-autophagy network under conditions of nutrient or energy deficiency or elevated oxidative stress (Heras-Sandoval et al. 2014). The role of autophagy has been investigated mainly by focusing on protein degradation. In response to environmental stressors, autophagy is commonly induced and elevated, promoting stress adaptation and maintaining intracellular homeostasis (Kuma and Mizushima 2010). Under normal physiological conditions, autophagy is maintained at a relatively low basal level, but its activity can be induced by various stress stimuli. Accumulating evidence indicates that Autophagy is upregulated in response to extra- or intracellular stress and signals such as starvation, growth factor deprivation, ER stress, and pathogen infection (He and Klionsky 2009). Previous studies have also shown that the sulfur transfer system in oysters is closely coupled with glutathione metabolism, jointly maintaining intracellular sulfur homeostasis and antioxidant capacity, and playing a regulatory role under heavy metal stress (Dong et al. 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTogether with transcriptomic enrichment in Wnt and mTOR pathways, these data imply coordinated regulation of structural repair and anabolic/catabolic balance. Wnt/\u0026beta;-catenin signaling is essential for organizing centers during zebrafish fin regeneration (Wehner et al. 2014); and induces satellite cell proliferation in adult muscle regeneration (Otto et al. 2008). Therefore, chronic low salinity may induce micro-damage and trigger transcriptional programs associated with regeneration. Additionally, the apelin/APJ system promotes skeletal formation, muscle metabolism, and myogenesis (Luo et al. 2021). Combined with the enrichment of PI3K-Akt-mTOR-related pathways observed in this study, it can be inferred that apelin-associated upregulation under low-salinity conditions may contribute to maintaining muscle protein homeostasis and adaptive energy metabolism. This regulation may help limit excessive proteolysis and support structural maintenance under stressful conditions.\u003c/p\u003e\n\u003cp\u003eTaken together, the present results support a model in which chronic low salinity induces coordinated remodeling of skeletal muscle at morphological, biochemical, transcriptional, and metabolic levels (Figure 6). Rather than favoring hypertrophic growth, low-salinity exposure appears to shift muscle toward a maintenance-oriented state characterized by reduced fiber size, cytoskeletal reorganization, elevated oxidative pressure, and activation of redox buffering and autophagy-associated pathways.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates that chronic low-salinity exposure induces marked skeletal muscle remodeling in marine medaka. Low salinity reduced myofiber cross-sectional area, increased fiber density, and widened the I-band without affecting sarcomere length, indicating structural adjustment of muscle fibers under hypo-osmotic conditions. In addition, elavated TAC and MDA levels suggested disturbed redox homeostasis and enhanced lipid peroxidation, accompanied by compensatory antioxidant responses. Transcriptomic and metabolomic analyses further revealed extensive molecular changes, particularly in pathways related to cytoskeletal organization, Wnt signaling, mTOR signaling, autophagy, and amino acid metabolism. These results indicate that chronic low salinity affects both muscle structure and metabolic homeostasis in marine medaka, and that skeletal muscle adaptation involves coordinated morphological, biochemical, and molecular responses. This study provides new evidence for understanding skeletal muscle plasticity in euryhaline fish under long-term low-salinity stress.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTian-Hong Chen conducted the research with assitance from Qing-Hao Zhan, Xiao-Yu Zeng and Ning-Ning Ma, Qi-Liang Li and Run-Jie Jin. The first draft of the manuscript was written by Tian-Hong Chen. All authors provided comments on previous versions of the manuscript. All authors read and approved the final manuscript. Jia-Lang Zheng and Qing-Ling Zhu obtained the fund and supervised the research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was funded by the Bureau of Science and Technology of Zhoushan (No. 2023C41005) and National Key Research and Development Program of China (No. 2025YFD2400500).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data will be available upon reasonable request to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr clear=\"all\"\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAgrawal S, Chakole S, Shetty N, Prasad R, Lohakare T, Wanjari M (2023) Exploring the role of oxidative stress in skeletal muscle atrophy: mechanisms and implications. Cureus 15(7). https://doi.org/10.7759/cureus.42178\u003c/li\u003e\n \u003cli\u003eAnwar S, Alrumaihi F, Sarwar T, Babiker AY, Khan AA, Prabhu SV, Rahmani AH (2024) Exploring therapeutic potential of catalase: Strategies in disease prevention and management. Biomolecules 14(6):697. https://doi.org/10.3390/biom14060697\u003c/li\u003e\n \u003cli\u003eChakrapani A, Gissen P, McKiernan P (2022) Disorders of tyrosine metabolism Inborn metabolic diseases: diagnosis and treatment. Springer, p 355-367\u003c/li\u003e\n \u003cli\u003eChen X, Peng L-B, Wang D, Zhu Q-L, Zheng J-L (2022) Combined effects of polystyrene microplastics and cadmium on oxidative stress, apoptosis, and GH/IGF axis in zebrafish early life stages. 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Current Opinion in Cell Biology 90:102403. https://doi.org/10.1016/j.ceb.2024.102403\u003cstrong\u003e\u003cbr clear=\"all\"\u003e\u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"fish-physiology-and-biochemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fish","sideBox":"Learn more about [Fish Physiology and Biochemistry](https://www.springer.com/journal/10695)","snPcode":"10695","submissionUrl":"https://submission.nature.com/new-submission/10695/3","title":"Fish Physiology and Biochemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"salinity, Oryzias melastigma, skeletal muscle, transcriptomics, metabolomics","lastPublishedDoi":"10.21203/rs.3.rs-9208878/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9208878/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSalinity fluctuations are key environmental drivers that shape physiological homeostasis in euryhaline teleosts by altering osmotic balance and energy allocation. In this study, marine medaka (\u003cem\u003eOryzias melastigma\u003c/em\u003e) was used to elucidate skeletal muscle adaptation to chronic low-salinity stress by integrating histology, transmission electron microscopy (TEM), antioxidant indices, transcriptomics, and metabolomics. Offspring (\u003cem\u003eF₁\u003c/em\u003e) derived from low-salinity-acclimated parents were reared at a salinity of 2.5\u0026permil; and sampled at 4 months, with fish from 25\u0026permil; seawater serving as controls. Low salinity significantly reduced the mean cross-sectional area of myofibers while increasing fiber density. TEM revealed a marked widening of the I-band without changes in sarcomere length, suggesting an altered actin\u0026ndash;myosin overlap that may help maintain contractile performance under osmotic stress. Biochemical assays showed unchanged catalase activity but significantly elevated total antioxidant capacity (TAC) and malondialdehyde (MDA)levels, indicating enhanced lipid peroxidation accompanied by compensatory activation of the antioxidant defense network. Transcriptome profiling identified 1266 differentially expressed genes (985 downregulated, 281 upregulated), enriched in cytoskeletal and contractile remodeling (desmosomes, myofibrils, myosin filaments) as well as signaling pathways including Wnt/β-catenin and mTOR. Metabolomics detected 112 differential metabolites; the pro-inflammatory oxidized phospholipid POVPC accumulated, 3-hydroxycoumarin levels increased, and uric acid levels decreased. Enrichment analyses highlighted autophagy, mTOR signaling, and the sulfur relay system, suggesting a metabolic shift from hypertrophic growth towards maintenance and repair. Collectively, marine medaka adapts to chronic low salinity through multi-layered remodeling of myofiber architecture, cytoskeletal networks, and integration of antioxidant and autophagy mechanisms. These findings provide a multi-omics framework for understanding muscle plasticity under hypo-osmotic stress and offer candidate targets for optimizing brackish and freshwater aquaculture practices.\u003c/p\u003e","manuscriptTitle":"Biochemical and Multi-Omics Analyses Reveal Skeletal Muscle Adaptation to Chronic Low-Salinity Stress of Marine Medaka (Oryzias melastigma)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-21 10:08:00","doi":"10.21203/rs.3.rs-9208878/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"65101020513445428800988818056890464021","date":"2026-05-15T17:25:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T19:55:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T19:52:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T09:05:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Fish Physiology and Biochemistry","date":"2026-03-24T08:11:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"fish-physiology-and-biochemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fish","sideBox":"Learn more about [Fish Physiology and Biochemistry](https://www.springer.com/journal/10695)","snPcode":"10695","submissionUrl":"https://submission.nature.com/new-submission/10695/3","title":"Fish Physiology and Biochemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"66082a13-963e-4e7f-836d-2e19854c53d9","owner":[],"postedDate":"April 21st, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"65101020513445428800988818056890464021","date":"2026-05-15T17:25:51+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T10:08:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-21 10:08:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9208878","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9208878","identity":"rs-9208878","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}