Synergistic mechanisms of ultrasound and slightly acidic electrolyzed water in peanut germination revealed by multi-omics analysis

Abstract

Peanut sprouts are recognized as a nutrient-dense functional food, rich in protein, soluble sugars, resveratrol, and bioactive compounds. Slightly acidic electrolyzed water (SAEW) and ultrasound treatments have emerged as promising technologies for enhancing the efficiency and uniformity of peanut seed germination, which is critical for improving sprout yield and quality. However, the molecular mechanisms underlying their synergistic effects remain elusive. This study investigated the combined effects of SAEW and ultrasound on peanut germination using integrated metabolomics and proteomics. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to identify and quantify treatment-altered metabolites and proteins during germination. The results indicated that SAEW promoted the initiation of peanut seed germination primarily through the induction of oxidative stress and inhibition of abscisic acid (ABA), while ultrasound primarily activates energy metabolism. The synergistic effect of SAEW and ultrasound was found to enhance oxidative stress and inhibit ABA expression, leading to suppression of energy metabolism pathways, including the citric acid cycle and glycerophospholipid metabolism. This study provided insights into the synergistic mechanism of SAEW-ultrasound treatment in enhancing peanut germination.

1. Introduction

Peanut sprouts are rich in resveratrol and other natural polyphenols, which are powerful antioxidants [1].Owing to their high anxiodant activity, these sprouts have gained increasing attention as functional ingredients in the food industry. Studies demonstrated that peanut sprout consumption confers health benefits, including enhanced immune function, reduced blood lipid levels, and delayed aging processes [2]. As functional foods derived from germinated peanut seeds, peanut sprouts are traditionally designated as “longevity sprouts” in Chinese dietary culture. Renowned for their distinctive flavor profile and exceptional nutritional composition, they are also esteemed as “immortal fruit sprouts” in culinary heritage. Ultrasound and slightly acidic electrolyzed watre (SAEW) are both non-thermal processing technologies, each with distinct mechanisms that enhance seed germination and promote the accumulation of bioactive compounds. Ultrasound treatment primarily exerts its effects through mechanical and cavitation forces, which can disrupt cell walls, increase membrane permeability, and stimulate biochemical processes [3]. When applied in combination with germination treatments, ultrasound significantly improves the functional properties of crops, particularly in the development of barley-based functional foods [4]. In addition to ultrasound, SAEW is widely recognized for its bactericidal activity, which reduces microbial contamination and promotes seedling development. At a concentration of 30 ppm, SAEW has demonstrated antimicrobial efficacy without negatively affecting the growth of buckwheat sprouts, making it an effective non-invasive disinfection method for sprout production [5]. Moreover, SAEW has been shown to promote the accumulation of bioactive compounds in broccoli sprouts [6]. Our results indicate that combining ultrasound with 70 ppm SAEW synergistically enhanced peanut germination, achieving an impressive germination rate of 90% [7].

Seed germination is a crucial biological process (BP), precisely regulated by both internal and external factors to ensure successful seedling establishment under diverse environmental conditions [8]. It typically begins with the water uptake (seed imbibition) and ends with the emergence of the radicle [9]. Ultrasound treatment has been shown to enhance germination by regulating energy metabolism and increasing seed vigor, and activating key metabolic pathways [10]. In brown rice, its promotive effects are closely associated with enhanced energy metabolism [11]. Furthermore, ultrasound modulates endogenous hormonal levels within plant tissue and cells, contributing to improved seedling development [12]. Transcriptomics studies indicate that ultrasound promotes mung bean sprouting by regulating hormone signaling pathways, which modulate germination and enhance seedling development [13]. Moreover, integrated transcriptome and lipidome analyses demonstrate that ultrasound alters seed lipid metabolism during seed germination [8]. Additionally, ultrasound enhances antioxidant defense mechanisms by stimulating the activity of antioxidant enzymes, thereby mitigating oxidative stress through the elimination of reactive oxygen species (ROS) [14]. For instance, in barely, the combination of ultrasound and germination has been shown to significantly increase the activities of peroxidase (POD) and polyphenol oxidase (PPO), indicating strengthened defense mechanisms and stress tolerance [4]. Similarly, SAEW also contributes to plant metabolic regulation by modulating enzyme activities and enhancing the synthesis of secondary metabolites. In broccoli sprouts, SAEW enhances sulforaphane accumulation by increasing glucoraphanin levels through methionine metabolism and elevated myrosinase activity [6].

Our previous study demonstrated that the combined application of ultrasound and SAEW synergistically improved peanut seed germination efficiency while effectively inhibiting microbial growth [7]. Seed germination is a critical stage in the plant life cycle and is highly sensitive to abiotic stress [10]. Understanding the molecular mechanisms mediating these responses is essential for optimizing germination. Proteomics provides insights into biomolecular interactions and functional protein dynamics, while metabolomics reveals the roles of small molecule metabolites in regulating key cellular processes such as signal transduction and energy metabolism. In this study, we employed label free quantitative proteomics and untargeted metabolomics with the aim of elucidating the molecular mechanisms by which SAEW and ultrasound influence peanut seed germination.

2. Material and methods

2.1. Materials and reagents

Organic red peanuts (Arachis hypogaea L.; Lot: 981107762) were purchased from Sam’s Club and sourced from Mishan City, Jixi, Heilongjiang Province, China. Peanut seeds of uniform size and color, free from physical damage, were selected for the experiment. SAEW was obtained from Shanghai Weyhill Environmental Technology Co., Ltd. Acetonitrile, methanol, and 2-chloro-L-phenylalanine were purchased from Aladdin. Among these, acetonitrile and methanol were of mass spectrometry grade, while 2-chloro-L-phenylalanine was of HPLC grade.

2.2. Peanut germination

The available chlorine concentration (ACC) of SAEW and ultrasound parameters were optimized based on our established protocol [7]. Under optimal conditions, seeds were treated with 70 ppm SAEW and subjected to ultrasonic treatment for 10 mins, followed by an 8-hour soaking period. The ratio of immersion liquid to peanut was maintained at 3:1 (w/w). Four experimental groups were established: (1) Group C (Control): soaking in pure water for 8 h; (2) Group U (Ultrasonication): ultrasonication in pure water for 10 mins followed by soaking for 8 h; (3) Group S (SAEW): soaking in 70 ppm SAEW for 8 h; and (4) Group SU (SAEW + Ultrasonication): ultrasonication in 70 ppm SAEW for 10 mins followed by soaking for 8 h. Samples were collected at day 0 (immediately post-soaking) and day 2 (after 2 days of sprouting) for subsequent analysis.

2.3. Sample collection

Collected samples were immediately flash-frozen in liquid nitrogen to quench metabolic activity and stored at −80°C. All samples were subsequently lyophilized to constant weight using a freeze dryer. The freeze-dried material was ground into a fine powder and stored at − 80°C pending further analysis.

2.4. Metabolomics

2.4.1. Sample pretreatment

Sample pretreatment followed the method of Yang et al. [15] with modifications. Briefly, A total of 50 mg of peanut powder was weighed into a centrifuge tube and mixed with 300 µL of extraction solution (methanol: acetonitrile: water = 2:2:1) containing 2 µg/mL 2-chloro-L-phenylalanine as an internal standard. The mixture was ground in a steel ball mill (four cycles of 30 s at1800 rpm each). After grinding, the sample was vortexed to resuspend and incubated at −20°C for 1 h. The sample was then centrifuged (4°C, 1200 rpm, 10 min), and 200 µL of the supernatant was transferred to a clean centrifuge tube. An additional 200 µL of extraction solution was added to the precipitate, vortexed, incubated at −20°C for 1 h, and centrifuged again under the same conditions. This second supernatant (200 µL) was combined with the first. The combined supernatant mixture was centrifuged again (4°C, 1200 rpm, 10 min) to obtain a final volume of 350 µL, which was concentrated using centrifugal evaporation.

The concentrated sample was re-dissolved in 100 µL of a 30% (v/v) methanol/water solution, vortexed for 1 min, and centrifuged (4°C, 1200 rpm, 10 min). The resulting clear supernatant was transferred to an injection vial equipped with an internal cannula for subsequent analysis.

2.4.2. Liquid chromatography-mass spectrometry analysis

Metabolomic analysis was performed using a Vanquish UHPLC system (Thermo Fisher) coupled to a Q Exactive Plus mass spectrometer (Thermo Fisher). Chromatographic separation was achieved on an ACQUITY UPLC HSS T3 column (100 × 2.1 mm, 1.7 µm, Waters) maintained at 45°C. The mobile phase consisted of (A) water with 0.1% formic acid (FA) and (B) methanol with 0.1% FA. The gradient elution program was: 99%A/1%B to 0%A/100%B linearly over 12 min, held at 0%A/100%B from 12 to 13 min. The flow rate was 0.4 mL/min and the injection volume was 1 µL.

Mass spectrometric data were acquired using a HESI source operating in both positive and negative ion modes, with data-dependent acquisition (DDA). Each cycle comprised one full MS scan followed by 10 MS/MS scans. Collision energies of 15 and 30 eV were applied for fragmentation, using nitrogen (99.999%) as the collision gas. Full MS scan parameters: range 67 to 1000 Da, resolution 70,000, AGC target 1e6, injection time (IT) 100 ms. dd-MS/MS scan parameters: resolution 17,500, AGC target 5e5, IT 50 ms. Spray voltage were 3.2 kV (positive mode) and 2.8 kV (negative mode). The capillary temperature was 320°C, and the S-lens RF was 50 V.

2.4.3. Metabolite identification

Data were acquired using Xcalibur 3.0 software (Thermo Fisher) and processed with Progenesis QI v2.3 data analysis software (Waters, UK) for peak picking, alignment, and normalization. Metabolites were identified based on precise mass (mass error < 5 ppm), MS/MS spectra, and comparison with the HMDB 5.0 database. Data from both ionization modes were combined. Compounds were sorted by identification score, duplicate were removed, and those with a score ＞ 35 were selected for differential compound analysis. A metabolites was considered differentially abundant if it met all the following criteria: ANOVA p-value < 0.05, fold change (FC) ＞ 1 or FC ＜ 1, OPLS-DA model variable importance in projection (VIP) > 1, and coefficient of variation (CV) < 30%. Data removal, calculation, and OPLS-DA analysis were performed using OMICS SOLUTION (https://www.omicsolution.com/wkomics/wkold/), while CV value analysis was conducted with QI software.

2.4.4. Data analysis

Metabolite pathway analysis was performed using MetaboAnalyst 6.0. HMDB IDs of the differential metabolites were input, and the Arachis hypogaea (peanut) pathway library from KEGG was selected. The top 10 pathway were visualized using the Wei Sheng Xin platform (https://113.44.3.163/). All experiments were performed with four biological replicates. Results were expressed as mean ± standard deviation. Significant differences were determined by ANOVA (p < 0.05), and comparisons between groups were analyzed by Tukey’s test.

2.5. Proteomics

2.5.1. Sample pretreatment

Proteins were extracted using phenol extraction followed by methanol precipitation. The precipitated proteins were then resuspended in RIPA buffer for further analysis. Protein concentration was determined using the BCA assay. For the proteomics sample preparation, SP3 magnetic beads were utilized as described in Hughes [16]. To begin, 20 µL of SP3 magnetic bead suspension was added to the reaction plate, followed by 100 µL of water and 100 µL of SP3 magnetic bead wash buffer. The mixture was incubated at 800 rpm for 1 min, after which a magnetic field was applied for 1 min to separate the supernatant, which was then removed. Next, an aliquot of 20 µL of 50 mM TCEP and 20 µg of the protein sample were added to the beads. The mixture was vortexed for 1 min to ensure thorough mixing, followed by incubation at 1200 rpm and 95°C for 5 min. After incubation, 180 µL of 100 mM IAA was added, and the mixture was incubated at 1200 rpm and 37°C for another 5 min. The supernatant was removed, and the magnetic beads were washed by adding SP3 magnetic bead wash buffer, incubating at 1200 rpm and 37°C for 1 min, and removing the supernatant. This wash step was repeated once more. Finally, 120 µL of 0.01 µg/µL trypsin in 50 mM ammonium bicarbonate was added to the beads, and the mixture was incubated at 1200 rpm and 37°C for 2.5 h. The reaction was terminated by adding 100 µL of 2% FA to the reaction plate, then apply a magnetic field for 1 min to pellet the beads. Collect the supernatant containing digested peptides for subsequent desalting. The peptide digest was desalted using a 96-well salt-removal microplate (H38-00501SK, Tuplabs, https://www.tuplabs.com). The experiment was repeated three times.

2.5.2. Detection method for proteomics

For each sample, 500 ng of total peptides were separated and analyzed using a nano­UPLC (Vanquish neo) coupled to an Astral mass spectrometer (Thermo Scientific) equipped with a nano­electrospray ion source. Peptide separation was performed on a reversed-phase column (EASY­Spray™ HPLC (150 μ × 15 cm), Thermo Scientific, USA). The mobile phases consisted of (A) 0.1% FA in water and (B) 80% acetonitrile (ACN) with 0.1% FA. Data-independent acquisition (DIA) was conducted in positive-ion profile mode using an Orbitrap analyzer at a resolution of 240 K. The MS1 scan covered an m/z range of 380­980, while the MS2 scan spanned m/z 150­2000. Higher energy collisional dissociation (HCD) was applied with a normalized collision energy (NCE) of 25% and isolation window of 2 m/z.

2.5.3. Identification

Raw mass spectrometry data were processed using DIA­NN software (version 1.8.1). MS spectra were searched against the species-level UniProt FASTA databases (Arachis_hypogaea_TaxonID_3818_2025_04_16. fasta). Carbamidomethyl of cysteine residues was set as a fixed modification, while oxidation of methionine and N­termimal acetylation of proteins were specified as variable modifications. Trypsin was used as proteolytic enzyme, allowing up to 2 missed cleavages. The false discovery rate (FDR) was set to 0.01 for both peptide-spectrum match (PSM) and peptide levels. Peptide identification was performed with a precursor mass tolerance of ± 20 ppm and a fragment mass tolerance of ± 20 ppm. All the other parameters were set as default values.

2.5.4. Data analysis

Proteins were filtered to retain only those supported by ≥ 1 unique peptide. Missing values were imputed using the “minimum value divided by two” method. Differentially expressed proteins were defined by a significant result (p < 0.05; Student’s t-test or Chi-square test), combined with FC ≤ 0.83 or FC ≥ 1.2. The genes corresponding to the differentially expressed proteins were mapped to nodes in the Gene Ontology (GO) database specific to Arachis hypogaea (peanut). Functional enrichment analysis was performed using GO (https://www.geneontology.org/) [17], [18].

3. Results

3.1. Differential metabolite analysis

Differential metabolites were identified by integrating data from both positive and negative ion modes. Metabolites were selected based on a score ≥ 35, CV ≤ 30%, and VIP > 1. Statistically significant upregulated and downregulated metabolites were then analyzed. As shown in Fig. 1A, C, and E, on day 0, the ultrasound, SAEW, and combined SAEW and ultrasound groups exhibited 39, 21, and 25 upregulated metabolites, respectively. The corresponding numbers of downregulated compounds were 23, 26, and 37. Venn diagrams (Fig. 1G, H) illustrated the overlap among the treatment groups. Notably, three metabolites were commonly upregulated and three were consistently downregulated across all treatments. By day 2 (Fig. 1B, D, F), the number of upregulated metabolites decreased to 33 in the ultrasound group and to 10 in both the SAEW and combined treatment groups. Conversely, the number of downregulated metabolites increased to 35, 61, and 64, respectively. Venn diagrams (Fig. 1I, J) highlight shared metabolic responses, with 3 metabolites consistently upregulated and 20 commonly downregulated across all three groups.

Fig. 1.

Differential compound analysis of ultrasound (U), SAEW (S), and their combination (SU) at day0 and day2. (A) Volcano plot of U0 vs. C0, (B) Volcano plot of U2 vs. C2, (C) Volcano plot of S0 vs. C0, (D) Volcano plot of S2 vs. C2, (E) Volcano plot of SU0 vs. C0, (F) Volcano plot of SU2 vs. C2, (G) Venn diagram of upregulated compounds at day 0, (H) Venn diagram of downregulated compounds at day 0, (I) Venn diagram of upregulated compounds at day 2, (J) Venn diagram of downregulated compounds at day 2.

3.2. Metabolic pathway analysis

Ultrasound treatment induced dynamic changes in metabolic pathways during early peanut germination (Fig. 2A, B), demonstrating clear stage-specific regulatory patterns. At the initial stage (day 0), ultrasound primarily altered lipid metabolism networks, specifically activating glycerophospholipid metabolism, linoleic acid metabolism, and arachidonic acid metabolism. By day 2, metabolic regulation become more complex. Linoleic acid and arachidonic acid metabolism were downregulated, while the citrate cycle (TCA cycle) and carbon fixation via the Calvin cycle emerged as the dominant energy-producing pathways. SAEW treatment also revealed dynamic regulatory effects on early peanut germination (Fig. 2C, D). At day 0, significant changes occurred in glycerophospholipid metabolism, glutathione (GSH) metabolism, linoleic acid metabolism, and arachidonic acid metabolism pathways, indicating SAEW induces oxidative stress and membrane lipid remodeling early in germination. By day 2, suppression of glycerophospholipid, linoleic acid, and arachidonic acid metabolism pathways occurred alongside upregulated GSH metabolism. The combined ultrasound and SAEW treatment exhibited distinct regulatory mechanism (Fig. 2E, F). During early germination, the combined treatment upregulated GSH metabolism while significantly downregulating flavone and flavonol biosynthesis, evidenced by inhibited synthesis of rutin and 6′'-O-Malonyldaidzin. Compared to SAEW alone, the combined treatment induced earlier ROS accumulation, thereby promoting seed germination. This suggests that the treatment facilitated dormancy breaking by triggering oxidative signaling and suppressing flavonoid antioxidants biosynthesis. By day 2, key pathways including glycerophospholipid metabolism, linoleic acid metabolism, indole alkaloid biosynthesis, arachidonic acid metabolism, and butanoate metabolism were significantly downregulated.

Fig. 2.

Top 10 enriched metabolic pathways identified through KEGG pathways based on differential metabolites between treatment groups and controls at day 0 and day 2. (A) U0 vs. C0: Pathways enriched in the ultrasound group on day 0, (B) U2 vs. C2: Pathways enriched in the ultrasound group on day 2, (C) S0 vs. C0: Pathways enriched in the SAEW group on day 0, (D) S2 vs. C2: Pathways enriched in the SAEW treatment on day 2, (E) SU0 vs. C0: Pathways enriched in the combined treatment on day 0, (F) SU2 vs. C2: Pathways enriched in the combined treatment on day 2.

3.3. Analysis of key metabolic compounds

The abundance of metabolites associated with the top 10 pathways in the comparisons of U vs. C, S vs. C, and SU vs. C at day 0 and day 2 is presented in Fig. 3A. These metabolites exhibited dynamic changes during early peanut germination, reflecting distinct physiological responses to different treatments. On day0, ultrasound treatment led to the upregulation of PC (16:0/18:3(6Z,9Z,12Z)), oxoglutaric acid, and 9,10-epoxyoctadecanoic acid, accompanied by the downregulation of glycerophosphocholine. By day 2, malic acid, uridine, and LysoPC (18:3(9Z,12Z,15Z)/0:0) were significantly upregulated, while PE (18:1(11Z)/18:3(9Z,12Z,15Z)) and PC (16:0/18:3(6Z,9Z,12Z)) were downregulated, indicating a physiological shift from stress response to growth regulation. On day 0, SAEW treatment resulted in the upregulation of 9,10-epoxyoctadecanoic acid, LysoPC (18:2(9Z,12Z)/0:0), LysoPA (0:0/18:2(9Z,12Z)), oxoglutaric acid, and oxidized glutathione (GSSG), while PC (18:1(9Z)/18:2(9Z,12Z)) and GSH were downregulated. By day 2, GSH was upregulated, while LysoPC (18:2(9Z,12Z)/0:0), PC (18:2(9Z,12Z)/18:3(9Z,12Z,15Z)), oxoglutaric acid, and LysoPA (0:0/18:2(9Z,12Z)) were downregulated. In the combined ultrasound and SAEW treatment, early germination (day 0) was marked by the suppression of rutin and 6′'-O-malonyldaidzin biosynthesis. In addition, GSSG was upregulated, indicating the presence of oxidative stress, while LysoPC (18:1(11Z)/0:0) was downregulated. By day 2, LysoPC (18:2(9Z,12Z)/0:0), PC (18:2(9Z,12Z)/18:3(9Z,12Z,15Z)), vindoline, and oxoglutaric acid were all downregulated in the combined treatment group.

Fig. 3.

Key compounds involved in the TOP10 pathways. (A) Heatmap of key compounds, (B) Oxoglutaric acid, (C) Glutathione, (D) Sums of PCs (including PC(18:2(9Z,12Z)/18:3(9Z,12Z,15Z)), PC(18:1(9Z)/18:2(9Z,12Z)), PC(16:0/18:3(6Z,9Z,12Z))), (E) Sums of LysoPCs (including LysoPC(18:3(9Z,12Z,15Z)/0:0), LysoPC(18:2(9Z,12Z)/0:0), LysoPC(18:1(11Z)/0:0)).

As shown in Fig. 3B, oxoglutaric acid was significantly upregulated in both the ultrasound and SAEW treatment groups on day 0. By day 2, however, it was significantly downregulated in the SAEW group and the combined ultrasound-SAEW group. Oxoglutaric acid as a key intermediate in the TCA cycle, was responsive to ultrasound and SAEW treatment, indicating a potential shift in energy metabolism during seed germination. Fig. 3C illustrated changes in GSH levels throughout germination. Fig. 3D exhibited a significant decrease in PC content for the SAEW group on day 0 and for the combined ultrasound-SAEW group on day 2. Additionally, Fig. 3F indicated significantly decreased LysoPC levels in both the SAEW-only and combined groups at day 2, noting that LysoPC and PC can undergo dynamic interconversion.

3.4. Differential protein analysis

To further elucidate the mechanisms underlying the effects of different treatments on peanut germination at the protein level, proteomics analysis was employed (Fig. 4). Using screening criteria of FC ≥ 1.2 and p-value < 0.05, the numbers of differentially expressed proteins in each treatment group relative to the control were determined. On day 0 (Fig. 4A, C, E), the numbers of upregulated proteins in the ultrasound (U vs. C), SAEW (S vs. C), and combined ultrasound-SAEW (SU vs. C) treatment groups were 27, 68, and 58, respectively. The corresponding numbers of downregulated proteins were 32, 31, and 79. On day 2 (Fig. 4B, D, F), the number of upregulated proteins increased to 39, 51, and 84 in the U vs. C, S vs. C, and SU vs. C comparisons, respectively, while the number of downregulated proteins rose to 38, 37, and 102. Notably, SAEW treatment exhibited a substantially higher number of upregulated proteins than the ultrasound group at day 0, suggesting that SAEW treatment may more effectively activate specific protein expression at the early stage of germination. In contrast, the combined treatment group showed the greatest number of downregulated proteins at both time points, indicating a potential synergistic effect that enhances suppression of protein expression. By day 2, increases in both upregulated and downregulated proteins were observed across all groups, reflecting a time-dependent response to treatment, with more pronounced changes in protein expression as germination progressed.

Fig. 4.

The differential protein analysis of ultrasound, SAEW, and their combination. (A) Volcano plot U0 vs. C0, (B) Volcano plot U2 vs. C2, (C) Volcano plot S0 vs. C0, (D) Volcano plot S2 vs. C2, (E) Volcano plot SU0 vs. C0, (F) Volcano plot SU2 vs. C2, (G) Downregulated venn diagram at day 0, (H) Upregulated venn diagram at day 0, (I) Downregulated venn diagram at day 2, (J) Upregulated venn diagram at day 2.

Venn diagram analysis identified proteins commonly regulated across treatment groups, indicating shared molecular response. On day 0 (Fig. 4H), four proteins (A0A444WVS5, A0A444Y895, A0A444YLH8, and A0A7U3PHA2) were commonly downregulated. In contrast, only one protein (A0A445DCV9) was commonly upregulated at this time point. By day 2, no proteins were commonly upregulated across all treatments (Fig. 4J), while two proteins (A0A444XBR5 and A0A444Y8I6) were consistently downregulated (Fig. 4I).

3.5. GO analysis of differentially expressed proteins

To explore the molecular regulatory effects of different treatments on peanut seed germination, GO enrichment analysis was performed on differentially expressed proteins identified in the SAEW group, ultrasound group, and combined treatment groups at day 0 and day 2.

In the ultrasound treatment group at day 0 (Fig. 5A), BP related to “response to oxygen-containing compound” and “cellular response to oxygen-containing compound” were significantly enriched, indicating initiation of an oxidative stress response. Cellular components (CC) including “cytoplasm”, “intracellular anatomical structure”, and “clathrin-coated vesicle” suggested active cellular remodeling and material transport. Molecular functions (MF) involving “abscisic acid (ABA) binding”, “isoprenoid binding”, and “hormone binding” highlighted key roles in hormone signaling. On day 2 (Fig. 5B), key metabolic BPs such as vesicle fusion, S-adenosylmethionine metabolic process, organelle membrane fusion, and organelle fusion were primarily activated. CC enrichment in the cytoplasm, ribosome, and protein-containing complexes indicated active intracellular sites of protein synthesis. Enhanced MFs included RNA binding, protein modification, and signaling molecule recognition capabilities. Collectively, these changes reflect an adaptive cellular response to ultrasound treatment, which may provide molecular support for the transition of peanut seeds from dormancy to germination.

Fig. 5.

GO analysis of differentially expressed proteins between different treatment groups and the control group. (A) U0 vs. C0, (B) S0 vs. C0, (C) SU0 vs. C0, (D) U2 vs. C2, (E) S2 vs. C2, (F) SU2 vs. C2.

In the SAEW treatment group at day 0 (Fig. 5C), intracellular metabolism exhibited a negative regulatory trend, with significant BPs enrichment in processes such as negative regulation of macromolecule metabolic process, negative regulation of metabolic process, and negative regulation of cellular metabolic process. Significantly enriched CCs included cytoplasm, cytosol, vesicle, and chromatin. MFs prominently enriched were structural constituent of chromatin, enzyme/molecular regulator activity, and lipid binding. By day 2 (Fig. 5D), multiple BPs related to ABA signaling—such as ABA-activated signaling pathway, cellular response to ABA stimulus, and response to ABA—were significantly enriched, with all proteins involved in these processes being downregulated. SAEW may weaken the inhibitory effect of ABA on seed germination by suppressing the activation of the ABA signaling, thereby facilitating favorable conditions for subsequent hypocotyl development and germination. In terms of CCs, significant enrichment was observed in cytoplasm, ribonucleoprotein complex, and nucleolus. MFs enrichment included enzyme regulator activity, molecular function regulator activity, and ABA binding.

In the combined treatment group, at day 0 (Fig. 5E), significantly enriched BPs were primarily related to “protein translation”, “energy metabolism”, and “stress response”. For CCs, significant enrichment was observed in the “cytoplasm”, “respiratory chain complex IV”, “catalytic complex”, and “protein-containing complex”. Significantly enriched MFs included “cysteine-type endopeptidase inhibitor activity”, “enzyme inhibitor activity”, and “molecular function inhibitor activity”. At day 2 (Fig. 5F), BPs such as “response to ABA” and “ABA-activated signaling pathway” were significantly enriched, with all involved proteins being downregulated. This further indicates that the combined SAEW and ultrasound inhibit the ABA signaling pathway, thereby promoting seed germination. CCs were mainly enriched in the “cytoplasm”, “intracellular anatomical structure”, and “protein-containing complex”. MFs were predominantly enriched in signal transduction related to “ABA binding”, “isoprenoid binding”, and “hormone binding”.

3.6. Analysis of key regulatory proteins related to ABA

GO analysis identified and characterized 13 ABA-related proteins. The expression patterns of these 13 proteins, visualized in the heatmap (Fig. 6A), revealed a distinct downward trend in their relative abundance on day 2 following ultrasound treatment, SAEW treatment, and the combined treatment. Compared to the control group, FCs progressively increased under ultrasound, SAEW, and their combined treatment. This further demonstrates that the combined application of ultrasound and SAEW synergistically inhibits the ABA pathway, thereby promoting peanut seed germination. Detailed relative abundance data for these proteins are shown in Fig. 6C-F. Notably, protein abundance in the combined treatment group was significantly lower than in the control group and further reduced compared to either ultrasound or SAEW treatment alone, indicating a synergistic inhibitory effect.

Fig. 6.

Proteins annotated with GO terms related to abscisic acid. (A) Heatmap showing differential expression patterns, (B) Fold change variations among conditions, (C-F) Expression profiles of representative proteins A0A445EM52 (C), A0A444ZFF7 (D), A0A445AWB9 (E), and A0A445AWN3(F), with statistical significance determined by t-test or Chi-square test with a p-value < 0.05.

Upon treatment with SAEW, proteomic analysis revealed that several ABA related proteins, including members of the Bet v I/Major latex protein family, were significantly downregulated at day 2, suggesting that SAEW and their combination modulates ABA signaling pathways by suppressing key ABA responsive components. The MF of Bet v I/Major latex protein domain-containing protein (A0A445EM52, A0A444ZFF7, A0A445AWB9, A0A445AWN3) was ABA binding. This suggests their potential involvement in ABA mediated signal transduction pathways. Under the combined treatment conditions, the expression levels of all four proteins were significantly downregulated, indicating repression or negative regulation of ABA-related regulatory networks.

3.7. Synergistic effects based on metabolomics and proteomics analysis

To further analyze the synergistic mechanism between ultrasound and SAEW, Fig. 7A–D presented the top 10 enriched pathways of differential metabolites in the SU vs. S and SU vs. U comparisons at day 0 and day 2. In the SU0 vs. U0 comparison, the GSH metabolism pathway was upregulated, with elevated levels of GSSG. This indicates significant oxidative stress under these conditions, leading to an increased oxidation of GSH to GSSG. Additionally, a prominent synergistic effect was observed in energy metabolism pathways at the early stage of germination (day 0), primarily involving the citrate cycle (TCA cycle) and glyoxylate and dicarboxylate metabolism. By day 2 (the later stage of germination), synergistic effects shifted to pathways related to glycerophospholipid metabolism, linoleic acid metabolism, and indole alkaloid biosynthesis. Differential metabolites within the glycerophospholipid metabolism pathway are detailed in Fig. 7E–H. On day 2, levels of LysoPCs, PCs, PE, and LysoPA in the combined treatment group were significantly lower than in the SAEW group. Similarly, the SU group exhibited significantly reduced levels of LysoPCs, PCs, and LysoPA compared to the ultrasound group. These results demonstrate that the combined ultrasound and SAEW treatment synergistically downregulated the glycerophospholipid metabolism pathway. The specific regulatory mechanism is shown in Fig. 7I, showing that the combined SAEW and ultrasound treatment synergistically promoted the downregulation of LysoPCs, PCs, and LysoPA.

Fig. 7.

The top 10 pathways of the differential compounds in the combined treatment and the relative quantification of differential compounds based on the glycerophospholipid metabolism pathway. (A) SU0 vs. U0, (B) SU0 vs. S0, (C) SU2 vs. U2, (D) SU2 vs. S2. (E) Sum of LysoPCs (including LysoPC(18:3(9Z,12Z,15Z)/0:0), LysoPC(18:2(9Z,12Z)/0:0), LysoPC(18:1(9Z)/0:0)), (F) Sum of PCs (including PC(18:2(9Z,12Z)/18:3(9Z,12Z,15Z)), PC(16:0/18:2(9Z,12Z))), (G) PE (PE(16:0/18:2(9Z,12Z))), (H) LysoPA (including LysoPA(0:0/18:2(9Z,12Z))), (I) Schematic diagram of the differential compound pathway.

To investigate the synergistic effects of SAEW and ultrasound on protein expression, comparative analyses were performed for SU vs. U and SU vs. S. Fig. 8A–D presented the GO enrichment results of differentially expressed proteins from these comparisons at days 0 and 2. In the SU2 vs. S2 comparison (Fig. 8C), the top three enriched BPs were citrate metabolic process, tricarboxylic acid metabolic process, and lipid storage. Fig. 8E-F showed the changes in representative proteins. Aconitate hydratase (A0A444WUR2) catalyzes the isomerization of citrate to isocitrate via cis-aconitate. Oleosin (A0A445BU36) provides recognition signals for the specific anchorage of lipase during lipolysis in seedling growth. In oleaginous seeds, lipids stored in organelles called oil bodies are degraded post-germination to supply carbon and energy for seedling development [19]. Similarly, in the SU2 vs. U2 comparison (Fig. 8D), BPs related to ABA were enriched, including response to ABA and ABA-activated signaling pathway.

Fig. 8.

The top 10 GO categories of differentially expressed proteins in response to the combined treatment of SAEW and ultrasound. (A) SU0 vs. S0, (B) SU0 vs. U0, (C) SU2 vs. S2, (D) SU2 vs. U2, (E-F) the representative protein of A0A444WUR2, (E) and A0A445BU36 (F).

To elaborate on the interactions between the pathways by integrating metabolism-protein network analysis, a Mantel correlation network diagram of metabolites from the top 10 metabolomics-based pathways and key regulatory proteins related to ABA was presented in Fig. 9. The network analysis clearly demonstrates a positive correlation between the proteomic and metabolomic datasets, where the thickness of the connecting lines is proportional to the magnitude of the correlation coefficients. Among the 13 analyzed proteins, 9 exhibited a strong correlation coefficient greater than 0.75 with the corresponding metabolites. For the sake of rigor, only the statistically significant results (p < 0.05) are visualized in the diagram.

Fig. 9.

Mantel correlation network diagram of metabolites from the top 10 pathways based on metabolomics and key regulatory proteins related to ABA.

4. Discussion

Ultrasound initiates germination by modulating membrane lipid remodeling and energy supply at day 0. This aligns with findings that ultrasound enhances lipid metabolism during germination, improving germination rates in Pinus tabuliformis seeds [8]. Lipid metabolism typically involves lipase-catalyzed hydrolysis of triacylglycerols producing free fatty acids, which are degraded via β-oxidation and the glyoxylate cycle to provide energy and carbon sources as sugars [11]. SAEW treatment triggers early changes in GSH and lipid metabolism pathways, indicating induction of oxidative stress and membrane lipid remodeling. The subsequent suppression of lipid pathways with concurrent GSH metabolism upregulation suggests a metabolic transition toward redox regulation. This shift, potentially linked to ROS accumulation, is supported by elevated GSH levels in SAEW-treated litchis [20] and the recognized role of ROS as non-enzymatic regulators of radicle elongation and endosperm weakening [21], ultimately restoring redox balance and membrane homeostasis. The combined treatment primarily regulates later germination stages through adjustments in membrane lipid metabolism and energy distribution.

To clarify the dynamic metabolic changes during germination, two key times points were selected for metabolic analysis. SAEW treatment group exhibited a decrease in GSH in the oxidative stress pathway and an increase in 2-oxoglutaric acid in the TCA cycle pathway, as well as a decrease in PC in the glycerophospholipid metabolism pathway on day 0. By day 2, GSH levels increased while 2-oxoglutaric acid levels decreased. In the ultrasound treatment group, 2-oxoglutaric acid increased on day 0, and malic acid increased on day 2. In the combined treatment group, GSH increased while both 2-oxoglutaric acid and LysoPC decreased on day 2.

Seed germination involves oxidative phosphorylation and mobilization of storage reserves, producing ROS that can damage cells if not properly scavenged [22]. GSH, a critical redox molecule, plays a central role in ROS detoxification [23], and dry seeds are known to contain high levels of GSH as a protective mechanism [24]. At day 0, GSH levels in the SAEW-treated group were significantly different from those in the control group, suggesting that SAEW may promote the initiation of peanut seed germination through redox regulation in the early stage. By day 2, both the SAEW and the combined treatment groups exhibited markedly higher GSH levels compared to the control, indicating an enhanced antioxidant capacity to scavenge ROS produced during the germination and growth processes.

SAEW contains ROS that function not only as antimicrobial agents but also as signaling molecules mediating physiological responses. Moderate ROS level can promote seed germination [25]. The upregulation of GSSG and the downregulation of reduced GSH during the early germination stage indicated that SAEW induces oxidative stress, which may help break seed dormancy and initiate germination. Additionally, SAEW-treated watermelon seeds exhibited reduced H₂O₂ and O₂^– levels at 48 and 96 h, respectively [26], suggesting that the regulation of ROS levels contributes to the germination-promoting effect of SAEW. SAEW treatment caused a temporary decrease in GSH levels on day 0, indicating a transient shift toward a more oxidized cellular state. This likely facilitates the accumulation of ROS such as H₂O₂, which can act as signaling molecules to relieve ABA-mediated germination repression. By day 2, GSH levels rebounded, suggesting the reactivation of antioxidant defenses to restore redox balance and protect developing seedlings from oxidative damage. This recovery was accompanied by a reduction in glycerophospholipid metabolism and overall energy consumption, likely serving to prevent excessive metabolic activity that could lead to further oxidative stress.

PC is the most abundant phospholipid of all eukaryotic cell membrane and plays a crucial role in the maintaining membrane stability and intracellular phospholipid content [27]. PC also serves as an important precursor in lipid signaling pathways and can act as a regulatory protein ligand [28]. Phospholipase D (PLD) hydrolyzes PC to produce phosphatidic acid (PA), which functions as a key signal molecule involved in stress response signal transduction [29], [30]. PA acts as a vital metabolic intermediate and a second messenger regulates many cell activities, and is involved in numerous cell responses induced by hormones, stress inputs and developmental processes in plants [31]. Moreover, PA has been reported to promote seed germination [32]. Studies have shown that during germination and post-germination, over half of the detected PCs exhibit an initial increase followed by a decrease, suggesting that these lipids accumulate prior to germination and are subsequently consumed during post-germination, likely contributing to membrane formation [33].

Proteomic analysis further revealed the regulatory role of hormone signaling in this process. At day 2, the combined treatment lead to a significant downregulation of proteins involved in ABA signaling pathway, a critical hormonal pathway regulating seed dormancy, stress response, and germination. SAEW and ultrasound modulate peanut germination through distinct but complementary regulatory pathways. SAEW appears to initially induce oxidative stress, as evidenced by GSH depletion, but subsequently enhances redox defense, energy recovery, and membrane remodeling. Ultrasound predominantly affects the TCA cycle, enhancing energy production and potentially activating germination-associated pathways. Their combination may enhance metabolic efficiency and stress resilience by coordinating redox balance, membrane integrity, and hormone signaling suppression (particularly ABA) during germination.

The antagonistic interplay between ABA and ROS critically regulates seed germination. The plant hormone ABA plays a crucial regulatory in key physiological processes, including seed germination, development, and abiotic stress responses [34], [35]. In watermelon seeds, SAEW treatment was found to reduce ABA levels while simultaneously increasing gibberellin content, likely through the modulation of genes encoding metabolic enzymes [26]. In parallel, absorbed water swiftly interacts with the embryo, resulting in the release of the hormone gibberellic acid, which stimulates metabolic activity in the aleurone cells surrounding the endosperm [36]. In addition to regulating plant growth and development, ABA signaling is a key mediator of stress tolerance mechanisms. During drought or salt stress, endogenous ABA levels can increase dramatically—up to 40-fold—leading to physiological responses such as stomatal closure to minimize water loss [37]. However, elevated ABA levels are also known to inhibit seed germination and early seedling growth. In contrast, ROS—particularly hydrogen peroxide (H₂O₂)—have emerged as essential signaling molecules that promote seed germination [38]. The inhibitory effects of ABA on germination and seedling development are also overcome by H₂O₂ [39].

5. Conclusion

This study demonstrates that the combined application of SAEW and ultrasound during peanut seed germination modulates key metabolic and antioxidant pathways to enhance seedling resilience. The initial decline in GSH levels suggests a transient oxidative challenge, which is subsequently counteracted by the reactivation of antioxidant defenses by day 2, restoring redox homeostasis. Simultaneously, the observed downregulation of glycerophospholipid metabolism and reduced energy consumption likely represent strategic adjustments to minimize oxidative damage caused by excessive metabolic activity. Together, these coordinated responses underline the potential of SAEW and ultrasound treatments to optimize seed germination and early growth by balancing metabolic activity and oxidative stress.

CRediT authorship contribution statement

Liping Wang: Writing – review & editing, Writing – original draft, Visualization, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Lu Yu: Methodology, Investigation, Data curation. Yifeng Zhang: Visualization. Ziyun Wu: Writing – review & editing, Supervision, Resources, 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.

Data availability

Data will be made available on request.