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. 2026 Feb 27;34:103698. doi: 10.1016/j.fochx.2026.103698

Walnut glutelin antibacterial peptides target Staphylococcus aureus through metabolic pathway and novel antibacterial peptides identification

Hui Ma a,b, Zhiqiang Lu a,⁎, Han Yang a, Yansong Gao a, Songyi Lin c, Fang Li d, Lingming Kong a,⁎
PMCID: PMC12969343  PMID: 41810363

Abstract

To address challenges from biofilm-forming, antibiotic-resistant pathogens like Staphylococcus aureus, this study explored walnut glutelin antibacterial peptides (WGAP) as sustainable alternatives, integrating metabolomics, peptidomics, and computational biology to uncover their mechanisms and identify novel antibacterial peptides. WGAP exhibited significant efficacy against Staphylococcus aureus (MIC = 53.5 μg/mL) with minimal hemolysis (<8.53% at 8 × MIC). WGAP treatment reduced bacterial surface hydrophobicity by 80%, thereby reducing bacterial adhesion to abiotic surfaces and subsequent biofilm formation. Metabolomics revealed that WGAP impaired nicotinamide cofactor synthesis, purine metabolism, and TCA cycle intermediates, thereby undermining energy homeostasis. Furthermore, effective antibacterial components of WGAP were isolated using inhibition zone analysis, ultrafiltration, and chromatography, and peptidomics identified five novel peptides. Molecular docking revealed strong binding of WGAP peptides-especially DVLINAYR and APQLLYIVK-to Staphylococcus aureus endonuclease-IV via hydrogen bonds and hydrophobic interactions at catalytic sites, highlighting WGAP'S antibacterial action and its potential as a sustainable, plant-based solution against food spoilage and antibiotic resistance

Keywords: Walnut glutelin, Antibacterial peptide, Staphylococcus aureus, Metabolomics, Molecular docking

Graphical abstract

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Highlights

  • •

    WGAP, as sustainable alternatives, inhibited the growth of Staphylococcus aureus.

  • •

    WGAP impaired the nicotinamide cofactor synthesis, purine metabolism, and TCA cycle

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    Novel antibacterial peptides (DVLINAYR and APQLLYIVK) were identified from WGAP

1. Introduction

Food spoilage is defined by a series of biochemical reactions initiated by microorganisms that decompose and metabolize nutrients in food, leading to a decline in food quality and safety. Conventionally, chemical preservatives have been utilized to inhibit this process and prolong the shelf life of food items. Utilizing chemical antibacterial agents can effectively mitigate food spoilage; however, their use is associated with several potential disadvantages, notably the possible adverse effects on consumer health. For instance, metabolites of specific antibacterial agents, including nitrite, have been implicated in carcinogenesis, thereby eliciting widespread consumer concerns regarding the safety of chemical additives (Cedillo-Olivos et al., 2024). Hence, identifying and developing safe, non-toxic, and environmentally sustainable alternative antibacterial agents have emerged as critical issues that necessitate urgent attention within the modern food industry.

Bioactive peptides, recognized as novel natural antibacterial agents, have increasingly attracted attention due to their unique properties and advantages. These peptides demonstrate advantageous physicochemical characteristics, including water solubility, thermal stability, and low toxicity, making them ideal candidates for food antibacterial applications. Bioactive peptides effectively inhibit microbial proliferation while preserving the appearance, flavor, texture, and nutritional quality of food products (Yang et al., 2024). They accomplish this by disrupting microbial cell walls or membranes, inhibiting DNA/RNA replication and transcription, and affecting protein synthesis and metabolism (Dong et al., 2024). The current development of antimicrobial peptides is primarily divided into animal- and plant-derived antimicrobial peptides. Compared with the unstable composition of raw materials in animal-derived antimicrobial peptide production, plant-derived antimicrobial peptides offer advantages for large-scale production (Bechaux et al., 2019). Studies on plant-derived antimicrobial peptides have primarily focused on prominent food crops, including soybeans and peanuts (Rutherfurd-Markwick, 2012). However, there is a significant potential in the comprehensive exploration of by-products from alternative oil crops, including high-protein resources such as walnut meal.

Walnut meal, a by-product of walnut oil extraction, contains a protein content surpassing 40% (Zhao et al., 2023). However, its utilization remains largely confined to low-value applications (e.g., simple processing or feed use), resulting in the underutilization of this protein-rich by-product. Recent studies have demonstrated that hydrolysates derived from walnut protease can release peptide fragments with biological activities, including antioxidant, anti-inflammatory, and antibacterial effects (Li et al., 2020). Hu et al. (2024) identified peptide sequences, including FGGDSTHP and ALGGGGY from the walnut fermentation broth, that demonstrated inhibitory effects against the spoilage bacterium Rosa roxburghii Tratt, thereby validating the antibacterial potential of walnut-derived peptides. Nevertheless, studies focusing on active peptides aimed at foodborne Gram-positive pathogens, including Staphylococcus aureus, are rare. Staphylococcus aureus is a significant pathogen that causes food spoilage and foodborne illnesses, presenting substantial challenges for conventional antibacterial agents due to its ability to form biofilms and its multidrug resistance (Argudín et al., 2010). Therefore, there is an urgent need to develop new targeted antibacterial strategies to address this issue. Our team successfully prepared walnut glutelin antibacterial peptides (WGAP) using bacterial-enzyme synergistic fermentation technology beng treated by Bacillus subtilis and alkaline protease at the same time in previous studies (Ma et al., 2024). However, owing to the ambiguity surrounding its mechanism of action, its practical application encounters two significant obstacles: (1) The dynamic response patterns of bacterial metabolic networks during the antibacterial process lack systematic interpretation; (2) the composition of the principal walnut antimicrobial peptides in the antibacterial enzyme hydrolysate is unclear.

This study aimed to systematically clarify the antibacterial mechanism of WGAP against Staphylococcus aureus and identify essential bioactive components using an integrated approach involving metabolomics, peptidomics, and computational biology. We revealed its antibacterial mechanism against Staphylococcus aureus by examining changes in cell hydrophobicity and associated metabolites. Furthermore, the composition of these antimicrobial peptides was analyzed using ultrafiltration, purification, peptidomics, and molecular docking techniques. This research will provide a theoretical basis for developing and applying new food preservatives and antibiotic alternatives.

2. Materials and methods

2.1. Materials

Staphylococcus aureus (China Center of Industrial Culture Collection, 10384) and Bacillus subtilis (China Center of Industrial Culture Collection, 10732) were acquired from the Guangdong Institute of Microbiology, while alkaline protease (200,000 U/g) was procured from Shanghai Yuanye Biotechnology Co., Ltd. Walnut meal (protein content of 58.3%) purchased from Shangshanyuan Technology Co., Ltd. in Urumqi, Xinjiang, China. Walnut glutelin was extracted from a defatted walnut meal in our laboratory. The Luria-Bertani (LB) broth culture medium and nutrient agar were obtained from Qingdao High-tech Industrial Park Haibo Biotechnology Co., Ltd. Chromatographic-grade methanol, acetonitrile, and 2-propanol were acquired from CNW Technologies. Chromatographic-grade ammonium acetate and acetic acid were sourced from Sigma-Aldrich, while ammonium hydroxide was obtained from Fisher Chemical. All other reagents employed were of analytical grade or higher unless otherwise specified.

2.2. Preparation of WGAP

The preparation of walnut glutelin followed the method developed by previous method for the separation and extraction of walnut protein components (Sze-Tao and Sathe, 2000). This process utilizes defatted walnut meal as the starting material. The extraction sequence involves the use of deionized water, 1 mol/L NaCl, 70% ethanol (v/v), and 0.1 mol/L NaOH solution to sequentially extract albumin, globulin, gliadin, and glutelin. Subsequently, each protein component was mixed and stirred at a ratio of 1:10 for two hours at 4 °C, followed by centrifugation. The precipitate was discarded, and the supernatant was collected. To ensure comprehensive extraction of each protein component, the entire procedure was repeated three times. The resulting gluten is then vacuum freeze-dried and stored at −20 °C.

The synthesis of WGAP relies on methodologies established in previous studies (Ma et al., 2024). Walnut glutelin is subjected to sterilization at 121 °C for 20 min utilizing a high-pressure steam sterilization device. Under aseptic conditions on a laminar flow workbench, Bacillus subtilis (1.5*107 CFU/g protein) and alkaline protease (400 U/g protein) are added. The mixture is subsequently homogenized with a glass rod and sealed with a film for synergistic fermentation involving bacterial and enzymatic activity at a fermentation temperature of 43 °C for 3 days with the initial pH of 8. After fermentation, the enzyme is inactivated at 95 °C for 15 min and subsequently dried at 55 °C. The sample was combined with distilled water and subjected to magnetic stirring for 30 min. The supernatant was collected and mixed with an equal volume of 10% trichloroacetic acid solution. Centrifugation was performed at 4000 rpm for 15 min, after which the precipitate was discarded. The supernatant was filtered through a 0.45 μm microporous membrane to eliminate macromolecular proteins and bacteria. The product was vacuum freeze-dried and stored at 4 °C for subsequent use.

2.3. Preparation of Staphylococcus aureus seed solution

Staphylococcus aureus was inoculated onto an LB solid medium and incubated at 37 °C for 24 h. Bacterial cells were subsequently harvested using an inoculation loop and inoculated into 100 mL of sterilized liquid medium for shaking incubation at 37 °C and 180 rpm for 12 h. Subsequently, 1 mL of the activated liquid culture was inoculated into 100 mL of LB liquid medium for further cultivation to obtain the Staphylococcus aureus seed solution. The bacterial solution concentration was adjusted to 107 CFU/mL.

2.4. Measurement of MIC

The MIC was evaluated utilizing a modified version of the double dilution method as described by Kong et al. (2016). We prepared 17 sterile test tubes, each containing 5 mL of LB broth. In tube 1, 5 mL of the WGAP was added and thoroughly mixed. Subsequently, 5 mL from tube 1 was transferred to tube 2, and this serial dilution process continued through tube 15. The contents of tube 15 were discarded after the transfer. After that, 0.5 mL of a bacterial suspension, with a concentration of 107 CFU/mL, was introduced into each of the 15 test tubes. Tube 16 served as the positive control, comprising solely the bacterial suspension without WGAP, while tube 17 served as the negative control, containing neither the bacterial suspension nor WGAP. All tubes were thoroughly mixed and incubated at 37 °C for 12 h in a constant temperature shaking incubator. The MIC was defined as the lowest concentration of the antibacterial agent at which no visible bacterial growth occurred.

2.5. Measurement of hemolytic toxicity

The hemolytic activity of WGAP was evaluated utilizing a modified protocol developed by Ghosh et al. (2022). Blood samples were collected from 2-week-old mice through retro-orbital bleeding and promptly transferred into 0.85% (w/v) physiological saline to prevent coagulation. Erythrocytes were isolated through centrifugation at 8000 ×g for 15 min at 4 °C using a Centrifuge 5817R, followed by three washes with physiological saline. The erythrocytes were subsequently resuspended in saline to form a 2% (v/v) homogeneous suspension. Serial dilutions of WGAP were formulated in physiological saline at concentrations equivalent to 0.5×, 1×, 2×, 4×, and 8× MIC. Aliquots of 0.3 mL of the erythrocyte suspension were mixed with equal volumes of WGAP solutions and incubated at 37 °C for 1 h. Negative and positive controls were established using physiological saline and 1% (v/v) Triton X-100, respectively. Following incubation, the mixtures were centrifuged at 3000 ×g for 5 min, and the absorbance of the supernatants was measured at 540 nm utilizing a microplate reader. The percentage of hemolysis was calculated according to previous method: Hemolysis (%) = (AWGAP - ANegative Control)/(ATriton X-100 - ANegative Control) × 100, where AWGAP, ANegative Control, ATriton X-100 represent the absorbance values of test samples, saline-treated erythrocytes, and Triton X-100-treated erythrocytes, respectively (Ye et al., 2023).

2.6. Measurement of cell surface hydrophobicity (CSH)

The impact of WGAP on the CSH of Staphylococcus aureus was assessed utilizing a modified protocol based on Derkacz and Krasowska (2023). Staphylococcus aureus in the logarithmic growth phase underwent centrifugation at 6500 rpm for 10 min, followed by three washes with phosphate-buffered saline (PBS). The resulting bacterial pellet was resuspended in a 0.1 mol/L KNO₃ solution (pH 6.2) to obtain an optical density of 0.5 at 600 nm. WGAP was implemented to achieve final concentrations of 0.5×, 1×, and 2× MIC. The control group comprised bacterial suspensions lacking WGAP. The initial absorbance (A₀) of each suspension was measured at 600 nm. Subsequently, 4.8 mL of the Staphylococcus aureus-WGAP suspension was combined with 0.2 mL of n-hexadecane and thoroughly mixed. The mixture was incubated at room temperature for 30 min to ensure complete phase separation, after which the aqueous phase was carefully aspirated with a sterile micropipette. The absorbance (A₁) of the aqueous phase was subsequently measured at 600 nm. CSH was quantified as the hydrophobicity (%) using the formula: hydrophobicity (%) = (A₀ - A₁)/A₀ × 100, where A₁ and A₀ denote the sample absorbance and the initial absorbance, respectively.

2.7. Metabolomics analysis

An overnight culture of Staphylococcus aureus was diluted 1:100 into fresh LB broth and incubated at 37 °C with shaking (200 rpm) for approximately 2–3 h until reaching the mid-logarithmic phase (OD600 = 0.5). Subsequently, the bacterial cells were harvested through centrifugation at 5000 rpm for 10 min and resuspended in an LB medium. WGAP was implemented to achieve final concentrations of MIC, with an equal volume of sterile ultrapure water serving as the control group. The cultures were subsequently incubated at 37 °C for an additional 3 h, followed by a second centrifugation at 5000 rpm for 10 min to harvest the cells. The bacterial pellets were washed thrice with PBS, flash-frozen in liquid nitrogen, and stored at −80 °C until analysis.

For metabolite extraction, 25 mg of bacterial samples were mixed with 500 μL of extraction solution (methanol: acetonitrile: water = 2:2:1, v/v) containing isotopically labeled internal standards, vortexed for 30 s, and homogenized in a bead mill for 4 min. The samples were subsequently subjected to ultrasonication in an ice-water bath for 5 min. Subsequently, the samples were centrifuged at 12,000 rpm for 15 min at 4 °C. The supernatant was transferred to a vial for liquid chromatography-mass spectrometry analysis.

Metabolite profiling was conducted utilizing a vanquish ultra-high-performance liquid chromatography (UHPLC) system (Thermo Fisher Scientific), integrated with a Waters ACQUITY UPLC BEH Amide column (dimensions: 2.1 × 50 mm, particle size: 1.7 μm). The mobile phase A comprised water containing 25 mmol/L ammonium acetate and 25 mmol/L ammonia, while mobile phase B comprised acetonitrile. The sample tray was maintained at 4 °C, and the injection volume was set at 2 μL. Mass spectrometric analysis was performed using Orbitrap Exploris 120 (Thermo Fisher Scientific), managed by Xcalibur software (version 4.4). The mass spectrometer parameters were configured as follows: sheath gas flow rate at 50 Arb, auxiliary gas flow rate at 15 Arb, capillary temperature at 320 °C, full MS resolution at 60,000, MS/MS resolution at 15,000, collision energy at stepped normalized collision energy (SNCE) levels of 20/30/40, and spray voltage at +3.8 kV for positive ion mode or − 3.4 kV for negative ion mode.

The raw data were analyzed using an R-based package to perform principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The Student's t-test and differential multiple analysis were performed to identify metabolites that exhibit significant differences. Metabolic pathways and their associated regulatory proteins were subsequently visualized using the Kyoto encyclopedia of genes and genomes (KEGG) pathway database (http://www.kegg.jp/kegg/pathway.html).

2.8. Ultrafiltration and purification of WGAP

In the ultrafiltration phase, WGAP was formulated as a peptide solution at 20 mg/mL. This solution was first filtered through a 0.45 μm microporous membrane and subsequently subjected to a series of ultrafiltration processes using membranes with molecular weight cut-offs of 30, 10, and 3 kDa. The process was performed with a peristaltic pump operating at a speed of 60 rpm while the outlet pressure of the ultrafiltration membrane was maintained between 2 and 5 bar. The filtrates from each ultrafiltration stage were collected and lyophilized for future use. During the purification phase, components exhibiting significant antibacterial activity, as determined by the ultrafiltration process, were dissolved in ultrapure water at 20 mg/mL. These solutions were filtered through a 0.22 μm membrane and subsequently loaded onto a Sephadex G-25 gel column. Each 1 mL sample was eluted with ultrapure water at a constant flow rate of 15 rpm. The absorbance of the elution profile was measured at a wavelength of 280 nm utilizing a nucleic acid protein detector, and elution peak fractions were collected at 2-min intervals. The collected fractions were freeze-dried, and their antibacterial efficacy was assessed by measuring the inhibition zone diameter against Staphylococcus aureus, identifying the fraction with the highest antibacterial activity.

2.9. Measurement of inhibition zone

We poured 15 mL of LB solid culture medium into a sterile Petri dish. After the medium had solidified, we pipetted 150 μL of various Staphylococcus aureus bacterial solutions (107 CFU/mL) onto the medium and utilized a spreader to evenly distribute the bacteria across the surface. An Oxford cup (inner diameter 6 mm) was subsequently placed on each culture dish, and 100 μL (20 mg/mL) of WGAP ultrafiltration (20 mg/mL) or gel chromatography component (10 mg/mL) was introduced into each dish. We used an equal volume of sterile physiological saline as a blank control. We incubated the cultures at 37 °C for 12–18 h. Upon completion of the incubation period, we measured the diameter of the inhibition zone using a vernier caliper and calculated the average value.

2.10. Identification and virtual screening of peptides

We determined the amino acid sequence of WGAP through liquid chromatography-tandem mass spectrometry (LC-MS/MS), implementing modifications to the method of Lu et al. (2024). Chromatographic parameters were as follows: Mobile phase A comprised a 0.1% formic acid aqueous solution, while mobile phase B was a 0.1% formic acid acetonitrile solution with an acetonitrile volume fraction of 84%. The RP-C18 liquid chromatography column (0.15 × 150 mm, 5 μm) was equilibrated using 95% mobile phase A. The WGAP fractions were introduced into a Zorbax 300SB-C18 peptide trap (Agilent Technologies, Wilmington, DE) through an automated sampler and subsequently separated using a liquid chromatography column. The product was separated through liquid chromatography and analyzed using a QExactive HF-X mass spectrometer for 60 min for mass spectrometry identification. The employed detection method was positive ion mode, with 10 fragment spectra (MS2 scans) acquired subsequent to each full scan. The identified peptide sequences were submitted to the Antimicrobial Peptide Database (APD) for evaluating their potential antimicrobial properties. The NovoPro online tool was utilized to predict the hydrophobicity and net charge of peptides with potential antibacterial activity. Considering the significant role of hydrophobicity and positively charged amino acid residues on the antibacterial efficacy of antimicrobial peptides, segments demonstrating advantageous hydrophobicity and net charge were selected for subsequent experimentation.

2.11. Molecular docking of peptides

The crystal structures of endonuclease IV (Nfo) (PDB ID: 8AXY) from Staphylococcus aureus, an apurinic/apyrimidinic (AP) endonuclease involved in base excision DNA repair, were selected as molecular docking receptors. The resolution of Nfo was 1.05 Å. PyMOL software was utilized to remove receptor protein crystal water, original ligands, and other extraneous elements. The Discovery Studio 2019 software was employed to predict the binding site between antibacterial peptides identified through mass spectrometry and the Nfo structure. The three-dimensional structure of the peptide was created using ChemDraw 21.0 and Chem3D. The AutoDockTools 1.5.6 software was employed to simulate the interactions and binding modes between gluten antimicrobial peptides and the Nfo structure. The parameters for the Nfo target were established as follows: center_x = 4.479, center_y = 7.922, center_z = 16.011; the grid box dimensions were set to size_x = 100, size_y = 100, size_z = 100, with a grid point separation of 0.581 Å. The docking results were imported into PyMOL and Discovery Studio 2019 for visual analysis.

2.12. Statistical analysis

Data are presented as the mean ± standard deviation, with each experiment conducted in triplicate unless otherwise specified. The Statistical Package for the Social Sciences software was used for statistical analysis, followed by one-way analysis of variance and Duncan's test. A P < 0.05 was considered statistically significant.

3. Results and discussion

3.1. Hemolysis toxicity of WGAP

Hemolytic toxicity is one of the primary indicators for evaluating the safety of antimicrobial peptides. Hemolytic toxicity was considered present when the hemolysis rate exceeded 10% (Amin & Dannenfelser, 2006). Fig. 1A depicts the hemolytic toxicity results for various concentrations of WGAP. A thorough analysis can be performed using the hemolysis rate data in Fig. 1B. The findings indicated significant hemolysis in the experimental group tubes compared to the Triton X-100 positive control group. WGAP exhibited significant efficacy against Staphylococcus aureus, and its minimum inhibitory concentration (MIC) was 53.5 μg/mL. The observed activity against Staphylococcus aureus was particularly noteworthy when compared to existing natural extracts. For instance, studies on C. flexuosa extracts, including its most effective butanol and aqueous fractions, reported a higher MIC of 156.25 μg/mL against the same strain (Parvez et al., 2022). This comparison underscores WGAP's comparatively stronger inhibitory effect on Staphylococcus aureus growth. As the concentration of WGAP increased from 0.5 × MIC to 4 × MIC, the hemolysis rate of erythrocytes remained below 5%. At a concentration of 8 × MIC, the hemolysis rate peaks at 8.54% yet remains below the 10% threshold. The hemolysis rate of red blood cells induced by WGAP is concentration-dependent, indicating that low concentrations of WGAP might be safe. Hemolytic toxicity assessments are essential for the advancement of antimicrobial peptides. For instance, peptide HP (4–16), which exhibits significantly enhanced antibacterial and antitumor activities due to the introduction of tryptophan at the second amino acid position of HP (4–16), exhibits no hemolytic activity against human red blood cells (Park & Hahm, 2012). These findings indicated that WGAP exhibited negligible hemolytic activity under experimental conditions, warranting further investigation of WGAP-derived antibacterial agents.

Fig. 1.

Fig. 1

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Effects of WGAP on the hemolytic toxicity and antibacterial properties. (A) Representative images of hemolytic toxicity of WGAP at different MIC concentrations; (B) Hemolytic toxicity statistics of WGAP at different MIC concentrations; (C) The surface hydrophobicity of WGAP at different MIC concentrations. The data marked by different letters between groups are significantly different (P < 0.05).

3.2. Effects of WGAP on cell surface hydrophobicity (CSH) of Staphylococcus aureus

The amphipathicity of peptides, defined by the charge-to-hydrophobicity ratio, is an essential factor influencing their membrane interaction dynamics and subsequent bactericidal efficacy (Li et al., 2021). Fig. 1C illustrates that untreated control cells demonstrated high CSH (85.2%), a characteristic strongly associated with biofilm formation and host cell adhesion capabilities. WGAP treatment resulted in a concentration-dependent decrease in CSH, with values decreasing from 84.3% (control) to 77.8% at 0.5× MIC, 39.3% at MIC, and 18.3% at 2 × MIC. The hydrophobicity decrease is consistent with those of previous findings that demonstrated that diminished surface hydrophobicity impairs microbial adhesion and biofilm development. Stincone et al. (2022) reported that the antibacterial activity of a lipopeptide from Bacillus velezensis against Listeria monocytogenes was associated with a 62% reduction in CSH, thereby disrupting biofilm architecture. The mechanistic parallels extend beyond fungal systems; our data are consistent with those of studies on the bovine casein-derived peptide BCp12, which similarly reduced the CSH of Staphylococcus aureus through charge-mediated membrane destabilization (Shi et al., 2021). WGAP diminishes the CSH of Staphylococcus aureus, thereby inhibiting colony growth. Therefore, its antibacterial mechanism is elucidated through metabolomics.

3.3. Metabolite analysis of Staphylococcus aureus

3.3.1. Multivariate statistical analysis of metabolic data

PCA, an unsupervised multivariate statistical method, was utilized to reduce the dimensionality of metabolomic datasets while maintaining maximal variance (Ljujić et al., 2024). The PCA model revealed specific metabolic disruptions in Staphylococcus aureus after WGAP treatment, with the first principal component accounting for 69.7% of the total variance and the second principal component contributing an additional 13.2% (Fig. 2A). This indicates significant treatment-induced metabolic reprogramming. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was utilized to improve the specificity in identifying differential metabolites. The OPLS-DA score plot (Fig. 2B) exhibited significant intergroup separation (R2 = 1.00, Q2 = 0.97), approaching 1.0 after a seven-round permutation test, with tight intragroup clustering, confirming experimental reproducibility (Zhang et al., 2012). It was important to clarify that this observed distinction from PCA and OPLS-DA reflected a statistically significant difference in the overall metabolic fingerprint between the two groups. However, these multivariate analyses alone did not directly identify or confirm specific metabolic pathway disruptions or assign biological causality. Overall, these findings indicate that differential metabolites were produced after treating Staphylococcus aureus with WGAP, which can be utilized for subsequent analyses.

Fig. 2.

Fig. 2

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Multivariate statistical analysis and differential metabolite analysis of Staphylococcus aureus. (A) Score scatter plot of PCA in model group and WGAP group; (B) Score scatter plot of OPLS-DA in model group and WGAP group; (C) Volcanic diagram analysis of differential metabolites in which the red and blue points are significantly up-regulated and down-regulated metabolite, respectively; (D) Matchstick chart of the top 10 metabolites exhibiting the highest and lowest differential multiples among the differential metabolite. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.3.2. Differential metabolite analysis

We constructed a volcano plot utilizing the variable importance in projection (VIP) values from the OPLS-DA model alongside the p-values obtained from a student's t-test, applying the criteria set at VIP > 1 and P < 0.05. This plot illustrates the results of the differential metabolite screening outcomes. Metabolites exhibiting significant upregulation are depicted in red, those with significant downregulation in blue, and metabolites with non-significant differences are indicated in gray. Fig. 2C demonstrates that 2909 differentially expressed metabolites were identified, including 1454 upregulated and 1455 downregulated metabolites, when comparing the group treated with gluten antimicrobial peptide to the control group. In the metabolite analysis of antimicrobial peptides, the selection of differential metabolites often involved setting specific fold change (FC) thresholds, such as FC > 1.2 and FC < 0.833 (de Prisco et al., 2023). These thresholds were chosen to identify metabolites that exhibit significant changes in concentration, which might indicate biological relevance or a response to antimicrobial peptide activity. By refining the selection criteria to a FC threshold of 1.2, where FC > 1.2 denotes upregulation and FC < 0.833 denotes downregulation, 272 differential metabolites were identified. Of these, 84 metabolites were significantly upregulated, while 188 were significantly downregulated (Appendix 1).

Subsequently, the 10 metabolites exhibiting the highest and lowest differential multiples were selected, and their differential multiples were log-transformed to base 2 to create a matchstick chart (Fig. 2D), which included octanoic acid 4-[(1-oxo-7-phenylheptyl) amino]-(4R), 17α-hydroxyprogesterone, N-acetyl-L-alanine, fipronil LPE (P-16:0), 2-acetyl furan, N-[3-(dimethylamino)-2,2-dimethylpropyl]-4-piperidine carbamide, methyl gingerol, 6H-dibenzo[b,d]pyran, 3-(1,1-dimethyl heptyl)- 6a,7,10,10a-tetrahydro-1-methoxy-6,6,9- trimethyl-, (6aR,10aR), and benzyl ammonium salt cation. The downregulated metabolites include alanyl-leucine, glycine-isoleucine, glycyl-leucine, N6-acetyllysine, allyl isoprobarbital, sunitinib, and 4-amino-1-methyl-5H-benzo[3,4-c]-pyridin-5-one, benzimidazole, prochlorpernone, and erythrolide. Several metabolites are associated with anti-inflammatory effects, including LPE (P-16:0), which is involved in the anti-inflammatory response during lipopolysaccharide-induced macrophage polarization (Park & Im, 2021). Following treatment with WGAP, LPE was significantly upregulated. Additionally, the differential metabolites alanyl-leucine, glycine-isoleucine, glycyl-leucine, and N6-acetyllysine exhibit significant downregulation (P < 0.05), indicating a strong association between changes in amino acid levels and the antibacterial efficacy of WGAP (Yu et al., 2024). Therefore, further analysis of metabolic pathways is beneficial for revealing the antibacterial mechanism of WGAP.

3.3.3. Antibacterial pathway

Differential metabolites were mapped to KEGG-enriched pathways. This analysis allowed us to identify the key pathways most closely associated with the observed metabolite changes. Figs. 3A depict that 42 differential metabolites (P < 0.05) were enriched, including nicotinamide adenine dinucleotide phosphate, xanthine, L-phenylalanine, 5-methyluracil, nicotinamide adenine dinucleotide, niacin, uridine, and α-ketoglutarate; and 38 of these 42 metabolites were significantly downregulated in the WGAP-treated group. Furthermore, the pathway enrichment bubble plot (Fig. 3B) showed that key pathways were involved in nicotine and nicotinamide metabolism, purine metabolism, TCA cycle, peptidoglycan biosynthesis, and amino sugar and nucleotide sugar metabolism.

Fig. 3.

Fig. 3

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Effect of WGAP on the KEGG metabolic pathway analysis. (A) KEGG classification in model group and WGAP group, in which the horizontal axis represents the percentage of annotated differential metabolites in a certain KEGG pathway compared to all annotated differential metabolites, while the vertical axis represents the enriched KEGG metabolic pathway names; (B) Rectangular tree diagram for metabolic pathway analysis.

Nicotinic acid and nicotinamide exhibited the most significant enrichment within metabolic pathways. Niacin and nicotinamide, as constituents of the vitamin B family, are essential for the biosynthesis of nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP) (Minto et al., 2017). These molecules serve as coenzymes, facilitating various oxidative metabolic processes in the body (Montserrat-de la Paz et al., 2017). Additionally, the vitamin B complex is implicated in immune regulation. Research indicates that niacin and its metabolites possess antioxidant properties. Consequently, WGAP may exert antibacterial effects by modulating the metabolism of niacin and nicotinamide, thereby inhibiting the physiological functions of Staphylococcus aureus and engaging in lipid metabolism. Purines are predominantly purine nucleotides in biological systems, essential for energy supply, metabolic regulation, and coenzyme composition (Allegrini et al., 2024; Cicero et al., 2023; Frenguelli & Dale, 2020). Accordingly, WGAP may inhibit Staphylococcus aureus by influencing energy regulation, coenzyme composition, and related pathways.

The tricarboxylic acid (TCA) cycle is the main metabolic pathway for breaking down carbohydrates, fats, and proteins, supplying vital energy to the body. The cycle commences with synthesizing citric acid from acetyl CoA, derived from carbohydrate metabolism and as an intermediate from lipid and protein metabolism. Consequently, the catabolic products of carbohydrates, lipids, and proteins are predominantly converted into carbon dioxide, water, and adenosine triphosphate (ATP) through the TCA cycle (Arnold & Finley, 2023). This cycle represents a convergent pathway for the oxidative degradation of the body's three primary macronutrients. The inhibitory effect of WGAP on Staphylococcus aureus is attributed to its impact on the synthesis and metabolism of carbohydrates, lipids, and proteins within the TCA cycle.

In a word, WGAP was primarily involved in the metabolic pathways of nicotine and nicotinamide, purine metabolism, and the TCA cycle in Staphylococcus aureus, demonstrating antibacterial properties. The detailed regulatory metabolic molecules are shown in Appendix 2. However, further exploration is needed to determine how effective antimicrobial peptide sequences can act on the surface of Staphylococcus aureus and inhibit its related metabolic analysis in the future.

3.4. Identification of the antibacterial peptide of WGAP

The isolation of four distinct molecular weight peptide fractions that were isolated from WGAP following ultrafiltration: WGAP-I (Mw < 3 kDa), WGAP-II (3 kDa < Mw < 10 kDa), WGAP-III (10 kDa < Mw < 30 kDa), and WGAP-IV (Mw > 30 kDa). Each of these fractions exhibited inhibitory effects against Staphylococcus aureus, with WGAP-III exhibiting a significantly larger inhibition zone diameter (18.51 mm) than the other fractions (P < 0.05) and demonstrating the most potent inhibitory activity. Subsequently, the WGAP-III fraction was further separated using gel filtration chromatography, resulting in the isolation of three components (Fig. 4A). Antibacterial assays revealed that the inhibition zone diameters of the three components WGAP-IIIA, WGAP-IIIB, and WGAP-IIIC were 15.92 mm, 12.00 mm, and 20.18 mm, respectively. The component WGAP-IIIC exhibited enhanced inhibition zone effects against Staphylococcus aureus. Consequently, this study selected the WGAP-IIIC component to further characterize its antimicrobial peptides. Ren et al. (2025) reported similar purification strategies for antimicrobial peptides derived from whole walnut meal, showing that low-molecular-weight fractions retained antibacterial activity against Staphylococcus aureus and that ODS-based separation improved potency. Here, we generated antibacterial peptides specifically from walnut meal glutelin, and our activity-guided fractionation similarly indicated enrichment of active components in small-peptide fractions. The identification of antimicrobial peptides within the WGAP-IIIC component was performed using LC-MS/MS. APD was used to screen the identified peptide sequence for potential antimicrobial activity. Subsequently, the predicted sequences were analyzed using the NovoPro online tool, where peptides demonstrating favorable hydrophobicity and net charge were selected for further investigation (Liu et al., 2019).

Fig. 4.

Fig. 4

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Identification of the antibacterial peptide of WGAP. (A) Analysis of WGAP-III fraction by gel filtration chromatography; (B—F) Secondary mass spectra of APQLVYIAR, SHSVIYVIR, APQLLYIVK, DVLINAYR, and SVIYVIRGN.

A comprehensive screening was performed based on peptide identification scores, length, and molecular weight. There were five antimicrobial peptides from the WGAP-IIIC component meeting the screening criteria. These peptides were APQLVYIAR, SHSVIYVIR, APQLLYIVK, DVLINAYR, and SVIYVIRGN (Figs. 4B-F). Notably, short antibacterial peptides with comparable chain length have also been reported in other systems. For example, an 8-residue peptide VFLENVLR identified by LC-MS/MS from Bacillus spp. exhibited direct inhibitory activity against Staphylococcus aureus (MIC = 64 μg/mL) (Zhang et al., 2023), which is in the same length range as our 8–9 amino acid peptides. This comparison suggests that short peptides terminating with a basic residue (Arg/Lys) can retain antistaphylococcal activity, consistent with our sequences (such as APQLVYIAR, SHSVIYVIR, and APQLLYIVK) and supporting the plausibility of these motifs as active antibacterial candidates. In contrast, longer antistaphylococcal peptides have also been identified from food protein hydrolysates; for instance, an egg-yolk-derived peptide KGGDLGLFEPTL showed activity toward Staphylococcus aureus (MIC = 2 mmol/L), indicating that effective sequences can span a wider length range, whereas our candidates fall within the short-peptide category (Pimchan et al., 2023). In this study, the potential peptide segments have chain lengths ranging from 8 to 9 amino acids, primarily nine peptides, with molecular weights ranging from 962.5185 to 1072.6029 Da. Each peptide attained an identification score exceeding 100 points. The antibacterial efficacy of antimicrobial peptides is closely associated with specific amino acid residues within their sequences. Peptides enriched with arginine and valine exhibit increased antibacterial activity due to their strong electrostatic interactions with the lipid bilayer of cell membranes (Ahmed & Hammami, 2019). Proline and glycine are essential for stabilizing peptide structure and enhancing antibacterial function (Edwards-Gayle et al., 2020). Among the identified peptides, APQLVYIAR comprises Val and Arg; SHSVIYVIR is abundant in Val and Arg; APQLLYIVK includes Pro and Val; DVLINAYR includes Val and Arg; and SVIYVIRGN is abundant in Val, Arg, and Gly. The antibacterial properties of WGAP-IIIC may be intricately associated with these five peptides, which are potential antimicrobial peptides.

3.5. Molecular docking of peptide and Nfo

Molecular docking is the preferred approach for predicting ligand binding patterns and their associated binding energies with target protein receptors. The intermolecular energy of docking molecules relates to the intrinsic tension within the active pocket complex during ligand-receptor binding, which influences the stability of the molecular interaction. A lower internal energy correlates with enhanced binding stability. Similarly, a reduced binding energy in molecular docking indicates a stronger interaction between peptides and ligands (Eshtiaghi et al., 2023). Staphylococcus aureus Nfo, an antibacterial target, belongs to the AP endonuclease family and can recognize and cleave apurinic/apyrimidinic (AP) sites by hydrolyzing the phosphodiester bond at the 5′ position of the abasic nucleotide (Senchurova et al., 2022; Turgimbayeva et al., 2022). Consistent with this functional role, Nfo has been experimentally characterized as the major AP endonuclease in Staphylococcus aureus, with its activity and in vivo functionality supporting an essential contribution to repairing DNA damage generated by endogenous and host-imposed factors (Turgimbayeva et al., 2022). Accordingly, molecular docking simulations were performed between five antimicrobial peptides and Nfo crystals derived from Staphylococcus aureus utilizing binding and intermolecular energy (Table 1 and Fig. 6).

Among the five peptides evaluated, DVLINAYR and APQLLYIVK, components of WGAP-III-C, demonstrated low binding and intermolecular energies, indicating a robust binding affinity to Staphylococcus aureus. DVLINAYR established two hydrogen bonds with Lys267 (4.00 Å) and Lys266 (3.18 Å) of Nfo and participated in hydrophobic interactions with Tyr261 (4.70 Å), Pro271 (5.14 Å) and Lys269 (3.71 Å) (Fig. 5A). Furthermore, APQLLYIVK established seven conventional hydrogen bonds with Glu258 (2.04 Å), Thr259 (2.31 Å), Tyr273 (2.93 Å), His6 (2.36 Å), Gln38 (5.04 Å), Tyr71 (2.40 Å), and Lys266 (2.18 Å) of Nfo, and hydrophobic interactions with Lys269 (3.44 Å), Lys266 (4.46 Å), and Tyr71 (3.29 Å) (Fig. 5B). Recent high-realyses refined the metal composition and coordination geometry of the Nfo catalytic center, reporting two inner Fe2+ ions and one Zn2+ and providing a structural basis for interpreting ligand/peptide contacts near the catalytic pocket (Kirillov et al., 2024). This evidence supports that interactions proximal to metal-coordinating residues may plausibly affect substrate processing, although further biochemical validation would be required. Fe within the active site coordinates with a water molecule to create an octahedral coordination geometry and establishes hydrogen bonds with Tyr residues. This interaction may clarify the antibacterial mechanism of DVLINAYR and APQLLYIVK, which interact with the Tyr residues of the Nfo active site.

Fig. 5.

Fig. 5

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Molecular docking of peptide and Nfo. (A) The molecular docking interactions of DVLINAYR with Nfo; (B) The molecular docking interactions of APQLVYIAR with Nfo.

4. Conclusions

This study demonstrated the antibacterial efficacy and mechanisms of WGAP against Staphylococcus aureus through metabolomics and identified key antibacterial peptides by molecular docking. WGAP diminishes CSH to impede biofilm formation and disrupts bacterial metabolism by downregulating nicotinamide/NAD+ biosynthesis, purine synthesis, and TCA cycle intermediates. Peptidomic and molecular docking identified two key peptides (DVLINAYR and APQLLYIVK) that target Nfo through hydrogen bonding and hydrophobic interactions, inhibiting DNA repair. These findings establish WGAP as a dual-action antimicrobial agent suitable for food preservation and antibiotic alternatives. However, the antibacterial properties and antibacterial mechanisms of DVLINAYR and APQLLYIVK by structural analysis (such as NMR) and metabolite analysis (such as KEGG and enrichment analysis) need further research. This study highlights the potential of underutilized agro-byproducts in sustainable antimicrobial development, bridging the gap between bioactive peptide discovery and practical food safety solutions.

CRediT authorship contribution statement

Hui Ma: Validation, Methodology, Investigation, Data curation, Conceptualization. Zhiqiang Lu: Writing – original draft, Visualization, Validation, Methodology, Investigation, Conceptualization. Han Yang: Investigation, Data curation. Yansong Gao: Investigation, Data curation. Songyi Lin: Supervision, Conceptualization. Fang Li: Supervision, Conceptualization. Lingming Kong: Supervision, Project administration, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This work was supported by the The Key Research and Development Program Project of Xinjiang Uygur Autonomous Region (2024B04015), The Walnut Industry Expert Team Project for the Pilot Work (HTCYZJTD2020-04), and Tianchi Young Scholar from the Education Department of the Xinjiang Uygur Autonomous Region. Thank “Home for Researchers editorial team (www.home-for-researchers.com)” for the language polishing.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.fochx.2026.103698.

Contributor Information

Zhiqiang Lu, Email: lzq0215@xjau.edu.cn.

Lingming Kong, Email: Klingming@126.com.

Appendix A. Supplementary data

Appendix 1 The detail information of differential metabolite (84 metabolites were significantly upregulated in red, while 188 were significantly downregulated in blue). Appendix 2 The detailed regulatory metabolic molecules of WGAP in the TCA cycle (A), purine metabolism (B), and nicotinamide metabolism (C).

mmc1.docx (1MB, docx)

Data availability

Data will be made available on request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix 1 The detail information of differential metabolite (84 metabolites were significantly upregulated in red, while 188 were significantly downregulated in blue). Appendix 2 The detailed regulatory metabolic molecules of WGAP in the TCA cycle (A), purine metabolism (B), and nicotinamide metabolism (C).

mmc1.docx (1MB, docx)

Data Availability Statement

Data will be made available on request.

Articles from Food Chemistry: X are provided here courtesy of Elsevier

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