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Article

Application of Magnetic Resonance Tools for Qualification and Traceability of Mullets

by
Fabíola Helena dos Santos Fogaça
1,*,
Nara Regina Brandão Cônsolo
2,
Eduardo S. Pina dos Santos
2,
Brenda S. de Oliveira
2,
Luísa Souza Almeida
3,
Leonardo Rocha V. Ramos
4 and
Luiz Alberto Colnago
3
1
Embrapa Food Technology, Laboratory of Bioaccessibility, Rio de Janeiro 23020-470, RJ, Brazil
2
School of Veterinary Medicine and Animal Science, São Paulo University, Pirassununga 13635-900, SP, Brazil
3
Laboratory of Nuclear Magnetic Resonance, Embrapa Instrumentation, São Carlos 13561-206, SP, Brazil
4
Department of Animal Production, Institute of Animal Science, Federal Rural University of Rio de Janeiro, Seropédica 23897-000, RJ, Brazil
*
Author to whom correspondence should be addressed.
Fishes 2026, 11(5), 263; https://doi.org/10.3390/fishes11050263
Submission received: 22 February 2026 / Revised: 27 March 2026 / Accepted: 24 April 2026 / Published: 28 April 2026
(This article belongs to the Special Issue Seafood Products: Nutrients, Safety, and Sustainability)
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Abstract

The global seafood industry faces persistent challenges related to product quality, safety, and authenticity, driven by complex supply chains, increasing demand, and the perishable nature of aquatic products. Traditional analytical methods often fall short in providing rapid, comprehensive, and non-destructive insights into the intricate biochemical changes occurring in seafood. 1H Nuclear Magnetic Resonance (1H NMR) spectroscopy has emerged as a powerful and versatile tool for metabolomics, offering a holistic view of the low-molecular-mass compounds (metabolites) present in biological samples. The present study applied 1H NMR for chemical fingerprint identification in mullets (Mugil liza) from Brazil. Dorsal muscle samples were taken from the fish during summer, autumn, and winter. The procedure involved freeze-drying the muscle tissue, thereafter extracting polar metabolites using designated solvents (methanol, water, and chloroform), and analyzing them using a 600 MHz spectrometer. As a result, 23 metabolites related to degradation biomarkers, essential metabolites, energy expenditure, and muscle structure were identified. The statistical analysis demonstrated a distinct separation between the geographical origins (RJ vs. SC), mostly influenced by variations in the concentrations of lactate, histidine, threonine, phenylalanine, and ornithine. Factors like fish size and seasonal variations did not markedly affect the overall metabolic profile, underscoring the reliability of these chemicals as stable origin indicators. The Principal Component Analysis identified two distinct groups of metabolites, establishing a profile for each geographical origin. The developed protocol can be applied to the processes of geographical identification. Thus, the 1H NMR tool was efficient in determining metabolites that can be considered biomarkers in analyses for seafood traceability.
Keywords:
authenticity; metabolites; biomarkers; fingerprinting; Proton Nuclear Magnetic Resonance
Key Contribution: This work emphasizes metabolic fingerprinting of biological samples, transitioning from targeted analysis of markers to a comprehensive view of low-molecular-mass compounds. 1H NMR is a non-destructive way to monitor a sample’s metabolic state, effectively distinguishing the geographical origin and quality of species. By analyzing specific metabolites, including flavor-related amino acids and biomarkers of muscle integrity, distinct chemical profiles can be developed, serving as barcodes for seafood products.

Graphical Abstract

1. Introduction

The global seafood industry is currently operating under complex supply chains, constant environmental changes, and customers who demand transparency, safety, and authenticity. The inherent perishability of aquatic products, coupled with complex processing and worldwide trading, has significantly increased the likelihood of mislabeling, quality degradation, and geographical and species fraud [1]. In 2022, the aquaculture and fisheries business was valued at approximately $264.8 billion, underscoring the necessity for the development of validated authentication solutions. Conventional analytical techniques are applicable for certain situations; however, they frequently lack the requisite speed, repeatability, or multidimensional depth necessary to get a comprehensive biochemical profile of seafood products [2]. The application of modern molecular techniques, particularly 1H Nuclear Magnetic Resonance (1H NMR) spectroscopy in conjunction with metabolomics, has emerged as a transformative method for the qualification and tracing of seafood. This novel approach pertains to the metabolic fingerprinting of biological specimens. 1H NMR is an effective method for determining the origin and quality of a species, due to its rapid, non-destructive, and highly reliable assessment of a sample’s metabolic state [3]. The technique relies on the interaction of atomic nuclei (specifically, 1H) with radiofrequency when the samples are placed in a magnetic field. The method generates unique spectral signals that correspond to different chemical environments of the molecules within the sample. The intensity of these signals is directly proportional to the concentration of the respective metabolites, enabling both qualitative identification and quantitative determination [4]. Its ability to provide a holistic metabolic profile makes it particularly well-suited for addressing the multifaceted challenges in seafood quality and traceability.
Several studies have demonstrated the efficacy of 1H NMR, exemplified by the accurate differentiation of five fish species, including flounder (Glyptoce-phalus cynoglossus) and European sole (Lepidopsetta spp.), with 100% precision [5]. Investigations on the Amazonian fish pirarucu (Arapaima gigas) have revealed biomarkers, including acetate, lactate, and creatinine, to assess molecular alterations during the salting and drying processes [6]. A pertinent study examined the traceability of tropical tunas, successfully distinguishing samples by species, size, geographical origin (including the Mozambique Channel), and onboard storage conditions [7]. Additionally, 1H NMR has been employed to examine the liberation of metabolites and protein breakdown during the in vitro digestion of sea bass (Dicentrarchus labrax) filets [8].
The mullets (Mugil spp.) are tropical fish species residing in coastal and estuarine habitats, found along the southwestern coast of South America. In Brazil, two species are particularly abundant: Mugil liza, prevalent in the Southeast region, and Mugil curema, found in the Northeast region. M. liza have economic significance for both industrial and artisanal fishing, ranking among the most intensively caught fishery resources in Brazil.
Similar to all marine fish, mullets possess significant nutritional value, particularly for macronutrients (proteins and lipids) and micronutrients (inorganic elements, amino acids, and fatty acids). These nutrients and their metabolites reflect the environmental history, nutritional condition, and physiological adaptation of the fish. They may be regarded as biomarkers, signifying a distinct identity for fish from specific locales.
Thus, this study established the profile for M. liza from Araruama lagoon by analyzing their concentrations of specific metabolites, such as flavor-enhancing amino acids, osmolytes, and muscle health biomarkers. These profiles could function as mullets’ chemical barcodes.

2. Materials and Methods

2.1. Study Area

This research was performed using mullet specimens from the State of Rio de Janeiro, southeastern Brazil. The Araruama Lagoon (−22.788, −42.275), situated in the Lakes Region, is acknowledged as the biggest permanently hypersaline lagoon globally, including roughly 225 km2 of water surface and exhibiting an average salinity of 52 ‰ (range from 12 to 60) [9,10] (Figure 1).

2.2. Samples

The first trial used fish from Araruama Lagoon and Santa Catarina State. Fish were collected at four different points in Araruama Lagoon, in the summer, autumn, and winter, between January and July 2024. A total of 16–24 fish were collected per season of the year. They were transported in styrofoam boxes with potable ice (−18 °C). Table 1 shows the mass (g), dimensions and male/female percentage of the fish collected in summer, autumn and winter. A sample of about 10 g on a wet mass (WM) basis was collected from the dorsal muscle [7]. Muscles were homogenized, lyophilized, and preserved at −80 °C until chemical characterization analyses. Six mullets (1200 ± 132 g) from Santa Catarina State were purchased at the fish market during the winter for comparative analysis. To mitigate the specific impact of each fish on the analytical results, at each collection site, 12 pools were obtained from a 50 g section of the filet loin of each fish.
A second trial was conducted using 20 samples from Araruama Lagoon (1727.75 ± 290.39 g; 58.39 ± 2.72 cm) and 20 samples from Sepetiba Bay (1515.54 ± 261.66 g; 57.52 ± 3.46 cm), both from Rio de Janeiro State. Sepetiba Bay has an area of approximately 305 km2, situated between the Serra do Mar and the city, whose salinity approximates that of the ocean (35‰).
Water samples, collected at the same points of Araruama Lagoon, were obtained with a Van Dorn bottle to assess the physicochemical properties (temperature, pH, salinity, dissolved oxygen, and conductivity) (Table 2).

2.3. Metabolomics Analysis 1H NMR

For the extraction of polar metabolites, approximately 20 mg of lyophilized mullet muscle was homogenized for 30 s by using a commercial tip ultrasound with a cold solution of methanol (0.400 mL) and MilliQ water (0.285 mL), followed by a second homogenization with cold chloroform (0.400 mL). Samples were kept on ice throughout the procedure. Then, the homogenates were centrifuged for 10 min at 12,700 rpm at 4 °C to remove precipitated protein and lipid supernatants. Superior aqueous extracts (0.450 mL) were carefully collected, transferred to Eppendorf tubes, and dried in a centrifugal concentrator (Speed-Vac, Thermo Savant, Holbrook, NY, USA) overnight (13 h) at room temperature (25 °C). The dried extract was resuspended in 500 μL of phosphate buffer (0.10 M, pH = 7.4), prepared in D2O (99.9%; Sigma-Aldrich, San Luis, CA, USA), containing 0.5 mM of 2,2-dimethyl-2-silapentane-5-sulfonate-d6 (DSS-d6) as an internal standard. The mixture was vortexed briefly and centrifuged at 14,000× g for 5 min. Subsequently, the supernatant was carefully transferred to 5 × 178 mm thin-walled Nuclear Magnetic Resonance (NMR) tubes (VWR International) and placed in the NMR spectrometer for analysis.
A 14.1 T Bruker spectrometer (600 MHz for 1H frequency) fitted with a 5 mm BBA probe was used to record NMR spectra at 298 K (Bruker Biospin GmbH, Rheinstetten, Germany). The 1H-NMR spectra were acquired with a standard Bruker pulse sequence with a water pre-saturation (noesygppr1d) with the following parameters: number of scans (128), recycle delay (4 s), spectral width (30 ppm), acquisition time (3.635 s), dummy scans (4), and a 90° pulse time (9.75 s. For every sample, the procedure was carried out in fully automatic mode via the ICON-NMR interface, utilizing Bruker routines (load, automatic tuning, locking, phase, shimming, acquisition, process).
The 1H NMR spectra were analyzed utilizing the Chenomx NMR Suite Professional 7.7 software (Chenomx Inc., Edmonton, AB, Canada). Phasing and baseline correction were carried out, and pH was calibrated via imidazole resonances. The spectra were calibrated to the DSS-d6 methyl peak at 0.00 ppm. The identical peak was utilized as a chemical shape indication, serving as an internal reference for quantification [11].

2.4. Metabolite Identification and Quantification

Metabolites in the 1H NMR spectra were identified using the integrated 1D spectrum library of Magnet metabolomic online platform [12]. A total of 23 metabolites were quantified in muscle extracts utilizing the profiler module (Figure 2). Quantification was conducted by comparing the identified metabolite peaks’ area to the area beneath the DSS-d6 methyl peak, which is associated with a known concentration of 0.5 mM in each sample. Then, metabolite concentrations were exported to Excel for data processing.

2.5. Statistical Analysis

Means and standard deviations were determined using Excel. Principal Component Analysis (PCA), normality tests (Shapiro–Wilk), and ANOVA (Kruskal–Wallis) were conducted utilizing PAST (Paleontological Statistics Software Package, version 5) [13]. The estimation of missing values (approximately 10% of the input values) was carried out utilizing the k-nearest neighbors (KNN) approach, relying on analogous samples [11]. A one-way ANOVA was conducted with Tukey’s HSD as a post hoc analysis, and significance was defined at p < 0.05. PCA was validated through Leave-One-Out-Cross-Validation (LOOCV) with 1000 permutations. To compare the Araruama and Sepetiba samples, the Shapiro–Wilk normality test was conducted for each group. Only the glucose group had a normal distribution, prompting the application of an independent t-test. The non-parametric Kruskal–Wallis test was utilized in the other groups, accompanied by multiple testing correction (Benjamini–Hochberg FDR) to regulate the false discovery rate throughout simultaneous tests (23 tests for the metabolites).

2.6. IA Uses

During the preparation of this manuscript/study, the authors used Google NotebookLM [2025] for the purposes of analysis of results and abstract suggestions. And the authors used Gemini [Google, 2026] to create the Graphical abstract.

3. Results

3.1. Identification of Mullet Muscle Metabolite Profiles

The 1H NMR spectra of mullet muscle samples revealed multiple recognizable amino acids, organic acids, glucose, and lipids, aligning with previous research on fish muscle [14]. Twenty-three metabolites were identified by their 1D and 2D spectra, with the corresponding compounds listed in Table 3. The analysis of muscle spectra permitted the identification of four categories of signals (according to 7) corresponding to metabolites: (i) Group I—degradation biomarkers: the NMR spectra from 8.5 to 4.2 ppm display the signals belonging to adenosine triphosphate (ATP)-degraded compounds as hypoxantine and inosine-5-monophosphate; (ii) Group II—essential metabolites: the NMR spectra from 4.4 to 3.5 ppm display the signals of choline derivate metabolites as glycerophosphorycholine (GPC) and also characterized by glucose presence; (iii) Group III—energy expenditure: the highest intensity of signals was observed for lactate in the high-filed (2.7–1.4 ppm) and creatine in the mild-field (4.2–3.0 ppm) NMR spectra regions; (iv) Group IV—muscle structure and its degradation: the signals from 2.8 to 0.8 ppm, from 3.5 to 3.4 ppm, and from 7.0 to 7.9 ppm correspond to aliphatic and aromatic groups, with 15 amino acids determined (Table 3).

3.2. Effect of Season on Mullet Muscle Metabolite Profiles

The metabolite profile of fish captured across different seasons was analyzed to determine the impact of the fishing season on fish quality in terms of metabolites. There was a significant difference between the samples only for succinate, a metabolite for energy expenditure (Table 4). This result indicates that the fish from the Lagoon exhibit a chemical composition pattern associated with environmental characteristics (diet, salinity, inorganic element content in the water, etc.), irrespective of seasonal variations that result from environmental changes, especially in temperature (Table 2).

3.3. Effect of Size Category on Mullet Muscle Metabolite Profiles

To evaluate the impact of fish size, samples were categorized into three groups: (I) mass up to 700 g; (II) mass from 701 to 1400 g; and (III) mass over 1401 g. No significant differences were identified among the various mass classes assessed (p > 0.05), as observed for the collection periods. For easier visualization of the results, a PCA was performed to assess the clustering of the different groups (Figure 3a). The figure indicates an absence of group segregation for the metabolites determined based on sample mass. The dendrogram illustrates a correlation among the samples; however, it reveals no discernible pattern, indicating similarities among the samples irrespective of the fish mass (Figure 3b).

3.4. Effect of Geographical Origin on Mullet Muscle Metabolite Profiles

When comparing mullets with different origins (Araruama Lagoon, RJ, and Santa Catarina State), collected simultaneously in winter, a segregation of groups was observed, indicating differences in the metabolite profiles between the samples (Figure 4). The statistical analysis validated the distinctions between the metabolites: lactate, histidine, threonine, phenylalanine and ornithine (Table 5).
To achieve a more comprehensive outcome, a wider sample size of mullets from the Araruama Lagoon and Sepetiba Bay was analyzed comparatively. PCA revealed the establishment of two separate groups in the composition of metabolites, indicating a variation in chemical composition among the samples (Figure 5), as observed between samples from Araruama and Santa Catarina State.
Amongst the 23 measured metabolites, only lysine, phenylalanine, serine, and ornithine exhibited no statistically significant variation (p < 0.05) between the Araruama and Sepetiba samples (Figure 6). The metabolites GCP, glycine, creatine, valine, alanine, IMP, lactate, and histidine exhibited elevated averages in the fish from Sepetiba, demonstrating strong significance (p < 0.001). The mullets from Sepetiba also exhibited elevated averages for the metabolites threonine, proline, glutamate, isoleucine, carnosine, and glucose (medium significance), as well as leucine, methionine, hypoxanthine, and taurine (low significance). In Araruama, succinate exhibited the highest average metabolite level (p < 0.001) (Figure 6).

4. Discussion

Fish from Araruama Lagoon showed elevated levels of lactate and creatine (Table 3), related to increased muscular activity, supporting the hypothesis of a metabolic shift following escape from fishing vessels [15] or displacement to the ocean for reproduction. Lactate accumulates in white muscle during burst swimming (anaerobic) and also during post-mortem alterations [16]. This accumulation causes intracellular acidosis, leading to muscle fatigue, while creatine helps buffer this and accelerates muscle recovery [17].
The mullet exhibits a typical behavior for marine-reproducing species, wherein its juveniles inhabit estuaries and lagoons for feeding and growth, subsequently returning to the ocean once reaching reproductive maturity to ensure species perpetuation [18,19]. In the Araruama lagoon, juvenile recruitment occurs throughout the closed season, ranging from August to November annually. During summer and autumn, fishing targets adult specimens in the early stages of gonadal maturation [20], as indicated by the samples in this study (Table 1). During winter, the mature adults leave the Lagoon for the sea via a channel [21], where fishing cages or hooks are situated, resulting in the catch of some of these fish. Consequently, there exists a persistent pattern of foraging for sustenance, incessant swimming, and returning to the ocean during winter. This trend can be attributed to the increased concentrations of lactate and creatine in the analyzed samples.
Mullets also exhibit elevated concentrations of taurine and lysine (Table 3). Taurine has a crucial role in osmoregulation, membrane integrity, and the metabolism of energy, amino acids, proteins, and lipids, in addition to promoting development and facilitating antioxidative processes [22,23,24,25]. Lysine is an essential amino acid that significantly contributes to protein synthesis, muscle development, and the maintenance of a positive nitrogen balance [26]. It is crucial for collagen synthesis, immunological response, and the production of carnitine, which facilitates energy metabolism. The presence of these two amino acids indicates the good nutritional status of the fish in the Lagoon. Research indicates that wild fish exhibit elevated taurine levels compared to cultivated and escaped fish from marine aquaculture farms [15]. Recently, studies determined that taurine may serve as a potential biomarker for identifying the origin of fish and can also indicate the health of fish cultivated in marine aquaculture facilities, in contrast to wild fish [23,27].
The reduced concentrations of inosine-5-monophosphate (IMP), GPC, and succinate indicate the favorable nutritional condition of the fish. Elevated levels of succinate and IMP are frequently associated with metabolic stress. IMP and GPC are metabolites resulting from the degradation of ATP during intense muscle exercise or post-mortem decomposition (loss of freshness). Spoilage changes nucleotides (e.g., ATP →IMP → inosine), providing these metabolites significant markers of freshness [28,29]. Succinic acid increases during hypoxia or metabolic stress; it functions as a signaling molecule to activate the immune response [30].
Concerning seasonal variations, only the fish harvested in winter exhibited reduced succinate levels relative to those gathered in summer and autumn. Succinate is recognized for its role as a growth enhancer and is utilized in feed to enhance protein efficiency in juveniles [31,32]. As the fish progresses beyond the high-growth phase, the physiological demand for elevated succinate levels for swift growth decreases. It is an essential step in the tricarboxylic acid (TCA) cycle, which is involved in energy metabolism. The elevated activity levels and swift growth in juveniles necessitate accelerated and more vigorous energy processing in contrast to the slower metabolic state observed in many adult fish [33]. Table 1 illustrates that during winter, we gathered a greater number of adults in the reproductive phase, but in summer and fall, we collected more juveniles, which accounts for the variation in succinate levels.
Previous studies indicate that the results for mullets (Mugil liza) in Brazil can be directly associated with the application of metabolites for geographical differentiation, a method already substantiated for species such as tunas (Thunnus albacares, Katsuwonus pelamis, and T. obesus) [7], salmon (Salmo salar) [34,35], pikeperch (Sander lucioperca), perch (Perca fluviatilis), and bream (Abramis brama) [36]. The study substantiates three primary dimensions: the effectiveness of NMR spectroscopy, the detection of certain biomarkers, and the impact of behavior and environment on the metabolic profile.
Similar to research conducted on tropical tunas and fish from Northeast Europe, the 1H-NMR technique demonstrated exceptional efficacy in discerning a chemical “fingerprint” of mullets, facilitating a distinct differentiation between the origins of Lagoa de Araruama (RJ) and Santa Catarina through PCA, which established the correlation among the metabolite profiles of samples from various locations. The regional differentiation of mullets was confirmed by notable variations in particular metabolites (lactate, histidine, threonine, and ornithine), several of which also serve as critical differentiators in other species. Lactate and creatine exhibited higher levels in the mullets from Araruama Lagoon, attributed to vigorous muscle activity (explosive swimming and reproductive migration). In the study involving tunas, lactate and creatine/phosphocreatine were recognized as essential metabolites for differentiating fish collected in various regions (e.g., the Mozambique Channel versus the Central Indian Ocean), indicating variations in hunting behavior and habitat [7].
In terms of amino acids, the concentrations of histidine, threonine, and ornithine were essential for geographical differentiation in mullets. In tunas and seabass, free amino acids and dipeptides, including anserine and carnosine, were significant factors in distinguishing between geographical origins and natural diets [7,15]. Histidine is an essential amino acid associated with muscle formation and its decomposition, serving as a precursor to important dipeptides, including carnosine and anserine [37]. These chemicals are present in elevated concentrations in pelagic and migratory species, such as tunas and mullets, since they serve as chemical buffers that mitigate the acidity resulting from lactate accumulation during anaerobic activity [38] associated with long-distance migration and reproduction [39].
Environmental and adaptation factors directly influence the metabolic profile of fish [40,41]. Salinity and osmoregulation may affect the biomarker profile [42]. The Araruama Lagoon is hypersaline (50–55‰), affecting the osmolyte composition of the mullets. The coast of Santa Catarina exhibits typical saltwater salinity levels of 30–35‰. The study developed with Sparus aurata, Dicentrarchus labrax and Argyrosomus regius substantiates this occurrence, emphasizing trimethylamine and taurine as significant biomarkers of environmental adaptation and exposure to varying salinities in natural habitats [15].
An additional significant influence is the nutritional condition of the fish. Elevated concentrations of taurine and lysine in mullets signify a favorable nutritional condition in the lagoon. The utilization of taurine as a biomarker of origin is substantiated by sources to differentiate not only geographical provenance but also life history (wild versus domesticated) [15]. Threonine is an indispensable amino acid that contributes to the chemical “fingerprint” characteristic of fish. This amino acid serves as a structural element of muscle proteins [43,44], and its concentrations indicate the nutritional background and dietary availability [45] in various environments. A distinction in origin for Brazilian mullets was identified using the quantification of threonine, corroborating its application as a biomarker for origin designation. Ornithine, unlike other amino acids, is a non-proteinogenic amino acid, indicating that it is not utilized in protein synthesis; instead, it plays a role in intermediary metabolic pathways, including nitrogen metabolism and the urea cycle [46]. In the mullets of Araruama Lagoon, ornithine was recognized as a key metabolite facilitating the segmentation of groups based on geographic origin by PCA. This illustrates particular physiological adaptations to the environment, including the lagoon’s hypersalinity, which influences the equilibrium of free amino acids in the tissue [47].
When comparing fish from Araruama Lagoon, characterized by high salinity, with mullets from Sepetiba, which experience typical estuary/bay salinity (~20–35 ‰), the effects of chronic and severe osmotic stress on the Araruama fish become evident. This stress significantly modifies metabolism through four interrelated mechanisms: the energetic expense of osmoregulation, the mobilization of amino acids as intracellular osmolytes, heightened protein and amino acid catabolism, and an increased energetic demand or turnover.
In euryhaline and stenohaline species, variations in ambient salinity induce a synchronized metabolic reprogramming that consumes energy to sustain osmotic equilibrium, adversely affecting the energy resources designated for growth and immunological function [48]. Consequently, the fish from Araruama are utilizing ATP to maintain the Na+/K+-ATPase pump’s functionality in the gills, kidneys, and intestines, whereas the fish from Sepetiba expend energy for the synthesis and storage of nutrients, indicated by higher metabolite content. This elucidates the overall diminished metabolomic profile in the Araruama samples. The reduction in glucose and lactate levels under hypersaline conditions underscores the significance of utilizing these energy substrates in extreme environments [49], particularly during chronic exposure (as observed in Araruama), when reserves are likely diminished due to the persistent demands of osmoregulation. In prolonged hypersalinity, amino acids function as compatible osmolytes, maintaining intracellular proteins without causing denaturation. They are continuously utilized and transferred between tissues and plasma, potentially resulting in lower levels in muscle samples when the organism is adequately adapted [50]. Consequently, elevated concentrations of glycine and proline in the Sepetiba samples, contrasted with diminished levels in the Araruama mullets, suggest the active mobilization of these amino acids as intracellular osmolytes, hence decreasing their concentrations in the analyzed tissues. Research on taurine in tilapia tissues indicated that hyperosmotic circumstances lead to an elevation in taurine transporter mRNA, functioning as an internal organic osmolyte to avert disturbances in cellular metabolism [51].
Research employing metabolomic techniques has shown that adaptations to salinity entail specific modifications in amino acid metabolism and serve as oxidative substrates to generate ATP, which supports osmoregulatory processes across diverse tissues. For freshwater fishes (Oreochromis mossambicus), at salinity levels below 25 ppt, there were considerable decreases in many intestinal amino acids, including N-acetylaspartic acid, γ-glutamylleucine, and l-lysine. The reduction in methionine may signify its transformation into taurine for osmolyte production, but the decline in tyrosine implies possible suppression of phenylalanine hydroxylase. The decrease in valine signifies its utilization as an energy source to facilitate ion-transport mechanisms [52]. In conclusion, fish subjected to persistent hypersalinity frequently elevate protein turnover to liberate free amino acids that function as osmolytes. This diminishes the reservoirs of vital amino acids (Valine, Isoleucine, Leucine, Threonine—all elevated in the Sepetiba samples), elucidating their reduced levels in Araruama.
The glucose in the fish from Araruama may be swiftly catabolized to generate ATP for the Na+/K+-ATPase, leading to reduced tissue concentrations. Creatine can be promptly transformed into phosphocreatine to satisfy osmoregulatory energy requirements, hence diminishing its free form in the tissues. However, the increased succinate levels in Araruama are associated with facultative anaerobic metabolism during the collection period (July), when fish undergo intensive swimming for migration and reproduction in the oceans, as noted in other samples from Araruama Lagoon (Table 4).
Besides post-harvest stress, storage duration, and temperature may alter concentrations of key metabolites such as lactic acid, histidine, and threonine in fish muscle tissue. It is suggested that studies compare mullet samples subjected to similar collection, transport, and processing protocols to validate our prior findings.
The 1H NMR approach could support the identification of fish origins from global regions, contributing to the reduction of fraud and the illegal capture of species subject to quotas or closed seasons. Our study demonstrates that environmental factors are crucial in determining the metabolite profile in muscle tissue. Consequently, metabolite databases of various fish species can provide a basis for investigating the impact of environmental variables and climate change on these species, including alterations in feeding patterns due to the availability or scarcity of natural food, as well as modifications in the profile of inorganic elements that influence the metabolism of proteins and other physiological compounds in fish.
Thus, mullets exhibit a globally recognized pattern wherein the metabolic profile (lactate, creatine, and amino acids) functions as a chemical “barcode” that synthesizes the local diet, the physical exertion demanded by the environment, and the physiological adaptations to the physicochemical conditions of the water.

5. Conclusions

1H NMR spectroscopy is a potent technique for mapping the metabolism of mullet (Mugil liza), identifying metabolites that function as species-specific chemical fingerprints. The metabolic profile varies significantly based on geographical origin. This registration enhances traceability, combats fraud, and ensures food safety and market value.

6. Patents

The findings will constitute the report for the registration of the Geographical Indication under the Denomination of Origin category for the mullet from the Araruama Lagoon at the Brazilian National Institute of Intellectual Property (INPI).

Author Contributions

Conceptualization, F.H.d.S.F.; methodology, N.R.B.C. and L.A.C.; software, E.S.P.d.S., B.S.d.O., L.S.A. and F.H.d.S.F.; validation, E.S.P.d.S., B.S.d.O. and F.H.d.S.F.; formal analysis, F.H.d.S.F. and L.R.V.R.; investigation, F.H.d.S.F. and L.R.V.R.; resources, F.H.d.S.F., L.A.C. and N.R.B.C.; data curation, F.H.d.S.F.; writing—original draft preparation, F.H.d.S.F.; writing—review and editing, E.S.P.d.S., B.S.d.O., N.R.B.C., L.A.C. and L.S.A.; visualization, N.R.B.C. and L.A.C.; supervision, L.A.C.; project administration, F.H.d.S.F.; funding acquisition, F.H.d.S.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Faperj, grant number E-26/290.110/2023.

Institutional Review Board Statement

This study was registered in the National System for the Management of Genetic Heritage and Associated Traditional Knowledge (SisGen) with the number AEC8FA4.

Data Availability Statement

Data is unavailable due to privacy or ethical restrictions related to the patent.

Acknowledgments

We express our gratitude to Macedo J.R., Dart R.O. and Oliveira J.P.M.D. for working on the Araruama Lagoon map. During the preparation of this manuscript/study, the authors used Google NotebookLM [2025] for the purposes of analysis of results and abstract suggestions; and Google Gemini [2026] to create graphical abstract. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
1H NMR1H Nuclear Magnetic Resonance
ATPAdenosine Triphosphate
DSS-d62,2-dimethyl-2-silapentane-5-sulfonate-d6
GPCGlycerophosphorylcholine
IMPInosine-5-monophosphate
LOOCVLeave-One-Out-Cross-Validation
NMRNuclear Magnetic Resonance
PCAPrincipal Component Analysis
TCATricarboxylic acid

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Figure 1. Location of Araruama Lagoon.
Figure 1. Location of Araruama Lagoon.
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Figure 2. Typical 600 MHz 1H NMR spectra from muscle of wild mullet collected in summer, autumn and winter.
Figure 2. Typical 600 MHz 1H NMR spectra from muscle of wild mullet collected in summer, autumn and winter.
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Figure 3. Metabolite profile of mullet muscle across different sizes, from Araruama Lagoon, RJ. Group I (black points): ≤700 g; group II (red points): 701–1400 g; group III (blue points): ≥1401 g. (a) PCA between groups; (b) Dendrogram with correlations of groups.
Figure 3. Metabolite profile of mullet muscle across different sizes, from Araruama Lagoon, RJ. Group I (black points): ≤700 g; group II (red points): 701–1400 g; group III (blue points): ≥1401 g. (a) PCA between groups; (b) Dendrogram with correlations of groups.
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Figure 4. PCA of metabolite profile of mullet muscle from Araruama Lagoon, Rio de Janeiro State (black points) and Santa Catarina State (red points).
Figure 4. PCA of metabolite profile of mullet muscle from Araruama Lagoon, Rio de Janeiro State (black points) and Santa Catarina State (red points).
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Figure 5. PCA of metabolite profile of mullet muscle from Araruama Lagoon (black points) and Sepetiba Bay (orange points), Rio de Janeiro State.
Figure 5. PCA of metabolite profile of mullet muscle from Araruama Lagoon (black points) and Sepetiba Bay (orange points), Rio de Janeiro State.
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Figure 6. Metabolite profile of mullet muscle from Araruama Lagoon and Sepetiba Bay, RJ. Mean ± SD. n = 20 samples for Araruama and n = 20 samples for Sepetiba.
Figure 6. Metabolite profile of mullet muscle from Araruama Lagoon and Sepetiba Bay, RJ. Mean ± SD. n = 20 samples for Araruama and n = 20 samples for Sepetiba.
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Table 1. Biometric parameters for the mullets of Araruama Lagoon, RJ.
Table 1. Biometric parameters for the mullets of Araruama Lagoon, RJ.
SeasonTotal Length (cm)Standard Length (cm)Total Mass (g)Height (cm)Males/Females (%)
Summer 144.48 ± 10.6635.63 ± 4.94834.92 ± 362.3311.62 ± 1.9337.50/62.50
Autumn 254.27 ± 3.8544.81 ± 3.561539.45 ± 367.0612.06 ± 0.3743.75/56.25
Winter 347.40 ± 11.8940.78 ± 9.59977.94 ± 704.1910.62 ± 2.3068.42/31.58
1 n = 24, one female with developed gonads; 2 n = 16, two females with developed gonads; 3 n = 19, all samples were adults reproductive phase.
Table 2. Water physicochemical properties, Araruama Lagoon, RJ.
Table 2. Water physicochemical properties, Araruama Lagoon, RJ.
SeasonDissolved Oxygen (mg/L)pHTemperature (°C)Conductivity (mS)Salinity (‰)
Summer 16.73 ± 0.127.99 ± 0.1029.78 ± 0.6773.08 ± 4.3050.50 ± 1.00
Autumn 28.78 ± 2.767.93 ± 0.1128.48 ± 0.3181.20 ± 5.8654.43 ± 2.19
Winter 37.43 ± 1.327.84 ± 0.2126.23 ± 0.5478.78 ± 3.3553.31 ± 2.25
Mean ± SD. n = 4 samples/season. 1 n = 24, one female with developed gonads; 2 n = 16, two females with developed gonads; 3 n = 19, all samples were adults reproductive phase.
Table 3. Representative 1H NMR assignments for mullet muscles at 600 MHz.
Table 3. Representative 1H NMR assignments for mullet muscles at 600 MHz.
MetaboliteConcentration Range *GroupType
Hypoxantine543.2–6.5IPurine
Inosine-5-monophosphate97.8–0.2IEnzyme
Glycerophosphorylcholine171.1–4.9IIEssential nutrient
Glucose4563.3–215.8IIMonosaccharide
Lactate24,418.9–522.7IIIOrganic acid
Succinate155.3–12.6IIIOrganic acid
Carnosine372.0–14.1IIIDipeptide
Creatine10,918.0–381.1IIINitrogen organic acid
Glutamate512.1–29.8IVAmino acid
Histidine4422.5–338.8IVAmino acid
Glycine2188.3–43.1IVAmino acid
Taurine5303.4–14.4IVAmino acid
Proline1476.4–216.7IVAmino acid
Valine483.7–21.2IVAmino acid
Lysine6522.5 -3.8IVAmino acid
Alanine518.3–11.0IVAmino acid
Isoleucine707.8–23.0IVAmino acid
Leucine1505.4–35.8IVAmino acid
Methionine834.3–28.2IVAmino acid
Threonine470.2–3.1IVAmino acid
Phenylalanine849.1–12.9IV Amino acid
Serine868.6–16.3IVAmino acid
Ornithine862.5–17.7IVNon-proteinogenic amino acid
* (mM/g muscle).
Table 4. Metabolite profile of mullet muscle across different seasons, from Araruama Lagoon, RJ.
Table 4. Metabolite profile of mullet muscle across different seasons, from Araruama Lagoon, RJ.
Metabolite *SummerAutumnWinter
Hypoxantine298.81 ± 120.0 a319.49 ± 153.65 a248.10 ± 73.35 a
Inosine-5-monophosphate7.93 ± 7.13 a4.50 ± 4.91 a11.93 ± 6.62 a
Glycerophosphorylcholine96.92 ± 26.49 a108.40 ± 35.52 a96.41 ± 41.15 a
Glucose908.75 ± 396.77 a888.74 ± 432.70 a677.16 ± 160.31 a
Lactate15,539.75 ± 3631.36 a17,739.46 ± 5781.62 a15,760.72 ± 1918.71 a
Succinate60.66 ± 41.18 a65.16 ± 33.13 a34.76 ± 21.13 b
Carnosine210.37 ± 78.33 a230.50 ± 84.53 a248.14 ± 83.21 a
Creatine7310.01 + 1405.24 a7423.95 + 3357.65 a6172.06 + 1567.88 a
Glutamate206.20 ± 133.84 a150.80 ± 131.80 a146.81 ± 50.29 a
Histidine3080.28 ± 643.25 a2755.87 ± 943.66 a3368.12 ± 637.02 a
Glycine1058.33 + 409.53 a1209.52 + 721.59 a740.02 + 413.83 a
Taurine39.16 ± 17.21 a40.40 ± 19.87 a34.69 ± 16.83 a
Proline657.98 ± 216.23 a650.01 ± 331.77 a786.22 ± 385.54 a
Valine97.43 + 37.62 a105.37 + 59.55 a80.51 + 34.79 a
Lysine300.62 ± 160.11 a442.71 ± 349.81 a290.69 ± 160.17 a
Alanine772.48 ± 258.15 a 869.11 ± 344.94 a767.01 ± 282.91 a
Isoleucine53.85 ± 24.50 a54.32 ± 32.53 a102.94 ± 110.44 a
Leucine133.17 ± 63.83 a131.96 ± 57.65 a239.73 ± 216.45 a
Methionine131.63 ± 111.34 a146.47 ± 90.11 a92.35 ± 40.99 a
Threonine243.19 ± 124.22 a285.18 ± 111.34 a322.95 ± 66.23 a
Phenylalanine111.54 ± 112.74 a38.04 ± 25.04 a361.37 ± 358.70 a
Serine398.12 ± 225.72 a315.46 ± 193.02 a356.23 ± 262.78 a
Ornithine607.13 ± 226.42 a583.96 ± 263.07 a458.03 ± 381.40 a
* (mM/g muscle). Mean ± SD. n = 12 samples/season. Different letters in the columns indicate a statistically significant variance (p < 0.05) between the treatment means (summer, autumn, and winter).
Table 5. Metabolite profile of mullet muscle from Araruama Lagoon, RJ, and Santa Catarina State.
Table 5. Metabolite profile of mullet muscle from Araruama Lagoon, RJ, and Santa Catarina State.
Metabolite *AraSCp Value
Hypoxantine248.10 ± 73.35 a345.73 ± 254.75 a0.8864
Inosine-5-monophosphate11.93 ± 6.62 a9.52 ± 6.75 a 0.4791
Glycerophosphorylcholine96.41 ± 41.15 a73.60 ± 54.69 a0.1931
Glucose677.16 ± 160.31 a474.63 ± 248.18 a0.1003
Lactate15,760.72 ± 1918.71 a7420.12 ± 5183.60 b0.0066
Succinate34.76 ± 21.13 a33.52 ± 21.86 a0.8137
Carnosine248.14 ± 83.21 a191.85 ± 127.67 a0.1931
Creatine6172.06 ± 1567.88 a3969.27 ± 2451.98 a0.0593
Glutamate146.81 ± 50.29 a188.75 ± 166.96 a0.5677
Histidine3368.12 ± 637.02 a2037.26 ± 1281.17 b0.0187
Glycine740.02 ± 413.83 a487.03 ± 347.10 a0.1289
Taurine34.69 ± 16.83 a 33.26 ± 27.95 a0.6631
Proline786.22 ± 385.54 a315.98 ± 227.24 a0.0424
Valine80.51 ± 34.79 a98.45 ± 71.88 a0.6704
Lysine150.93 ± 100.13 a123.70 ± 106.38 a0.7540
Alanine767.01 ± 282.91 a577.45 ± 400.51 a0.1585
Isoleucine102.94 ± 110.44 a59.07 ± 44.02 a0.5186
Leucine239.73 ± 216.45 a113.18 ± 82.92 a0.0707
Methionine92.35 ± 40.99 a76.20 ± 44.00 a0.5582
Threonine322.95 ± 66.23 a158.82 ± 81.34 b0.0283
Phenylalanine361.37 ± 358.70 a39.38 ± 29.38 b0.0019
Serine356.23 ± 262.78 a279.70 ± 219.49 a0.4822
Ornithine458.03 ± 381.40 a162.33 ± 111.72 b0.0152
* (mM/g muscle). Mean ± SD. n = 10 samples for Araruama (ARA) and n = 6 samples for Santa Catarina State (SC). Different letters in the columns indicate a statistically significant variance (p < 0.05) between the treatment means (Ara × SC).
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Fogaça, F.H.d.S.; Cônsolo, N.R.B.; dos Santos, E.S.P.; de Oliveira, B.S.; Almeida, L.S.; Ramos, L.R.V.; Colnago, L.A. Application of Magnetic Resonance Tools for Qualification and Traceability of Mullets. Fishes 2026, 11, 263. https://doi.org/10.3390/fishes11050263

AMA Style

Fogaça FHdS, Cônsolo NRB, dos Santos ESP, de Oliveira BS, Almeida LS, Ramos LRV, Colnago LA. Application of Magnetic Resonance Tools for Qualification and Traceability of Mullets. Fishes. 2026; 11(5):263. https://doi.org/10.3390/fishes11050263

Chicago/Turabian Style

Fogaça, Fabíola Helena dos Santos, Nara Regina Brandão Cônsolo, Eduardo S. Pina dos Santos, Brenda S. de Oliveira, Luísa Souza Almeida, Leonardo Rocha V. Ramos, and Luiz Alberto Colnago. 2026. "Application of Magnetic Resonance Tools for Qualification and Traceability of Mullets" Fishes 11, no. 5: 263. https://doi.org/10.3390/fishes11050263

APA Style

Fogaça, F. H. d. S., Cônsolo, N. R. B., dos Santos, E. S. P., de Oliveira, B. S., Almeida, L. S., Ramos, L. R. V., & Colnago, L. A. (2026). Application of Magnetic Resonance Tools for Qualification and Traceability of Mullets. Fishes, 11(5), 263. https://doi.org/10.3390/fishes11050263

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