Mitigating High-Temperature Stress in Peppers: The Role of Exogenous NO in Antioxidant Enzyme Activities and Nitrogen Metabolism

Abstract

This study investigated the effects of exogenous nitric oxide (NO) on growth, antioxidant enzymes, and key nitrogen metabolism enzymes in pepper seedlings under high-temperature stress. In addition, targeted metabolomics was used to study the differential accumulation of amino acid metabolites, thereby providing theoretical support for the use of exogenous substances to mitigate high-temperature stress damage in plants. The results showed that high-temperature stress increased soluble sugar, soluble protein, amino acids, proline, malondialdehyde (MDA), and hydrogen peroxide (H₂O₂) content, electrolyte leakage, and superoxide anion (O₂^·-) production rate while altering the activities of antioxidant enzymes [superoxide dismutase (SOD), catalase (CAT), peroxidase (POD) and ascorbate peroxidase (APX)] and key nitrogen metabolism enzymes [nitrate reductase (NR), glutamine synthetase (GS), glutamate dehydrogenase (GDH), and nitric oxide synthase (NOS)]. c-PTIO (2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-oxide, an NO scavenger) exacerbates oxidative stress and further reduces NO content and enzyme activities. However, exogenous SNP (sodium nitroprusside, an NO donor) effectively alleviated these adverse effects by enhancing antioxidant defense mechanisms, increasing NO content, and normalizing amino acid metabolite levels (kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine), thereby maintaining normal plant growth. These findings suggest that SNP can enhance stress tolerance in pepper seedlings by improving osmotic regulation, antioxidant capacity, and nitrogen metabolism, effectively mitigating the damage caused by high-temperature stress.

1. Introduction

Peppers (Capsicum annuum L.) are the second most widely cultivated vegetable crop in China and are rich in vitamins A, C, and B6, folic acid, dietary fiber, and antioxidants. With global climate change, temperature has become a crucial environmental factor affecting plant physiology, metabolism, growth, development, and productivity [1]. Increasing evidence indicates that high-temperature (HT) stress is a significant abiotic factor that limits the growth and yield of pepper seedlings and often leads to substantial agricultural losses [2]. The physiological and biochemical responses of plants to HT include alterations in carbohydrate metabolism, disruption of photosynthesis, changes in signal transduction, and increased oxidative damage [3]. Additionally, HT stress causes fluctuations in compatible solutes, such as sugars, amino acids, and proline (Pro), which play critical roles in maintaining cellular homeostasis [4]. Studies have consistently shown that HT stress can also lead to fluctuations in sugar levels and the accumulation of certain amino acids, such as proline, which act as osmoprotectants to mitigate stress damage [5]. Plants have developed complex antioxidant defense systems comprising both enzymatic and non-enzymatic components in response to oxidative stress. Antioxidant enzymes, such as superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD), play crucial roles in scavenging reactive oxygen species (ROS) and mitigating their harmful effects [6]. Additionally, non-enzymatic antioxidants, including ascorbic acid and glutathione, contribute to the redox balance and protect plants from oxidative damage [7].

Under abiotic stress, significant changes occur in various amino acid metabolites within plants, reflecting their response and adaptation mechanisms [8]. Drought, HT, and salt stress lead to increased levels of kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatinine. These changes are typically associated with antioxidant responses and energy metabolism, aiding in the adaptation to adverse environments [9]. Specifically, under HT stress, the level of kynurenine increases significantly, which is linked to the activation of the tryptophan metabolism pathway that may help regulate ROS production and antioxidant responses in Arabidopsis [10]. Additionally, the level of N-acetyl-L-tyrosine reflects protein degradation and changes in amino acid metabolism, which help maintain cellular homeostasis in rice under drought stress [11]. Low-temperature stress leads to an increase in L-methionine levels, as L-methionine, a precursor of antioxidants, participates in glutathione synthesis, enhances antioxidant capacity, and reduces the oxidative damage caused by HT stress in peppers [12]. Moreover, drought stress in maize led to increased urea levels, indicating enhanced protein degradation and amino acid metabolism [13]. Similarly, creatine levels also increase under abiotic stress (e.g., salt stress), which is associated with its role in energy metabolism. For instance, exogenous NO treatment significantly increases creatine levels, providing additional energy to support the stress response of cucumbers [14]. In summary, increased levels of kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine under abiotic stress reflect enhanced antioxidant capacity and energy metabolism in plants. This adjustment helps the plants adapt and resist adverse environmental conditions.

Nitric oxide (NO) is a small bioactive molecule that acts as a signaling mediator in various physiological processes in plants, including abiotic stress responses. Exogenous NO significantly affects the antioxidant capacity of plants under various abiotic stress conditions, thereby enhancing stress tolerance. NO treatment significantly increases the activity of SOD, POD, and CAT, effectively reducing oxidative damage in tomatoes [15]. Exogenous NO increases the activities of SOD, CAT, and POD, eliminating ROS generated at HT in cucumbers [16]. Exogenous NO enhances the activities of nitrate reductase (NR) and nitrite reductase (NiR) in Arabidopsis under HT stress, leading to increased NO synthesis and improved resistance to oxidative damage [17]. Exogenous NO plays a crucial role in promoting amino acid metabolism and maintaining maize growth under drought conditions [18]. This is achieved by increasing the activities of NR and NiR, which in turn boosts the activities of glutamine synthetase (GS) and glutamate dehydrogenase (GDH) [19]. Similarly, exogenous NO enhances NR and NiR activity in rice, increases NO synthesis, regulates GS and GDH activity, improves amino acid metabolism, and enhances salt-stress tolerance [20].

In this study, we investigated the effects of exogenous NO on antioxidant capacity and amino acid metabolites in pepper seedlings under HT stress. We aimed to elucidate the mechanisms by which NO alleviates heat tolerance in pepper seedlings and identify potential strategies to enhance crop stress resistance through NO application. Understanding these mechanisms will provide insights into the physiological and biochemical pathways involved in plant stress responses and will aid in the development of heat-resistant crop varieties.

2. Materials and Methods

2.1. Plant Materials and Treatments

Peppers (Capsicum annuum L. Zhengda 119) are a variety known for their susceptibility to high-temperature conditions. Seeds were sown after germination in a substrate mixture of vermiculite, perlite, and peat soil (1:1:1, v/v). When the second leaf was fully expanded, seedlings with uniform growth were selected and transplanted into pots containing the same mixed substrate. During the entire growth period, plants were irrigated with Hoagland’s nutrient solution every three days to ensure adequate nutrient supply. When the fourth leaf was fully expanded, the seedlings were randomly divided into four treatment groups. Four treatments were set up: (1) Control: normal temperature conditions and leaf spraying with distilled water; (2) HT_Control: HT conditions and leaf spraying with distilled water; (3) HT_SNP: HT conditions and leaf spraying with 0.1 mmol·L⁻¹ SNP (sodium nitroprusside; a donor of NO); (4) HT_c-PTIO: HT conditions and leaf spraying with 0.3 mmol·L⁻¹ c-PTIO (2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-oxide; a scavenger of NO). For each 1 L of the treatment solution, 0.2 mL of Tween was added. The temperature conditions for normal temperature were day/night: 25 °C/20 °C, and for HT were day/night: 38 °C/30 °C. The relative humidity for cultivation was maintained at 70–80%, and the light intensity was day/night: 30,000 Lx/0 Lx. The solution was sprayed daily at 9:00. The experiment used a randomized block design with three biological replicates. Samples were taken at 0, 5, 10, and 15 d after treatment to determine the relevant indicators (Figure 1).

2.2. Determination of Growth and Electrolyte Leakage

Growth indices were measured using a ruler, and increments were calculated based on the values recorded on each sampling day, starting from day 0 of the treatment. The electrolyte leakage was assessed using the conductivity method. Briefly, leaf discs (0.5 cm in diameter) were collected and rinsed with deionized water to remove surface contaminants. The discs were then immersed in 10 mL of deionized water and incubated at room temperature for 24 h. After incubation, the initial conductivity (C1) of the solution was measured using a conductivity meter. The samples were then boiled at 100 °C for 15 min to release all electrolytes, cooled to room temperature, and the final conductivity (C2) was measured. Electrolyte leakage was calculated as a percentage of the initial conductivity to the final conductivity (C1/C2 × 100%).

2.3. Determination of Physiological Indexes

The soluble sugar, soluble protein, amino acid, and proline contents were determined according to methods described in previous studies [21,22,23]. Specifically, soluble sugar was quantified using the anthrone method, while soluble protein content was measured using the Bradford assay. Amino acid content was determined by ninhydrin colorimetry, and proline content was measured using the acid-ninhydrin method. Malondialdehyde (MDA) content, an indicator of lipid peroxidation, was determined using the thiobarbituric acid (TBA) method, which forms a pink chromogen with MDA [24]. Hydrogen peroxide (H₂O₂) content was quantified spectrophotometrically by reacting with potassium iodide, and the superoxide anion (O₂^·−) formation rate was measured by the reduction of nitro blue tetrazolium (NBT) [23]. The activities of antioxidant enzymes, including superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX), were assayed using standard spectrophotometric methods [25]. Nitric oxide (NO) content was measured using the Griess reagent method [26]. Glutamine synthetase (GS) activity was determined using the ferric chloride colorimetric method, which quantifies the γ-glutamyl transferase activity of GS [27]. Glutamate dehydrogenase (GDH) activity was assessed through the reduction of NAD⁺ to NADH, as monitored by spectrophotometry [28]. Nitrate reductase (NR) activity was measured using a colorimetric assay following the instructions provided in the reagent kit from Suzhou Koming Biotechnology Co., Ltd. (Suzhou, China). Nitric oxide synthase (NOS) activity was determined according to the instructions provided in the reagent kit from the Nanjing Jiancheng Bioengineering Institute (Nanjing, China).

2.4. Sample Preparation and Extraction

After the sample was thawed and smashed, 0.05 g of the sample was mixed with 500 µL of 70% methanol/water. The sample was vortexed for 3 min at 2500 r/min and centrifuged at 12,000 r/min for 10 min at 4 °C. The supernatant (300 μL) was placed into a new centrifuge tube and stored at −20 °C for 30 min, Then, the supernatant was centrifuged again at 12,000 r/min for 10 min at 4 °C. After centrifugation, the supernatant (200 μL) was transferred to a Protein Precipitation Plate for further LC-MS analysis.

2.5. UPLC and ESI-MS/MS Conditions

The sample extracts were analyzed using an LC-ESI-MS/MS system [UPLC, ExionLC AD, https://sciex.com.cn/ (accessed on 23 July 2023); MS, QTRAP^® 6500+ System, https://sciex.com/(accessed on 23 July 2023)]. The analytical conditions were as follows, HPLC: column, ACQUITY BEH Amide (i.d.2.1 × 100 mm, 1.7 μm); solvent system, water with 2 mM ammonium acetate and 0.04% formic acid (A), acetonitrile with 2 mM ammonium acetate and 0.04% formic acid (B). The gradient was started at 90% B (0–1.2 min), decreased to 60% B (9 min), 40% B (10–11 min), and finally ramped back to 90% B (11.01–15 min). The flow rate was 0.4 mL/min, temperature 40 °C, and injection volume was 2 μL. An AB 6500+ QTRAP^® LC-MS/MS System, equipped with an ESI Turbo Ion-Spray interface, operating in both positive and negative ion modes and controlled by Analyst 1.6 software (AB Sciex) was used. The ESI source operation parameters were as follows: ion source, turbo spray; source temperature 550 °C; ion spray voltage (IS) 5500 V (positive), −4500 V (negative); and curtain gas (CUR) 35.0 psi. DP and CE for individual MRM transitions were determined with further optimization. The analysis specifically targeted amino acid metabolites, and a specific set of MRM transitions was monitored during each period based on the amino acids eluted within this period.

2.6. Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Pearson Correlation Coefficients (PCC)

Unsupervised PCA was performed using the statistics function prcomp within R [www.r-project.org (accessed on 1 August 2023)]. The data were the unit variance scaled before unsupervised PCA. HCA results of samples and metabolites are presented as heatmaps with dendrograms, whereas PCC between samples was calculated using the cor function in R and presented only as heatmaps. Both HCA and PCC were performed using the R package pheatmap. For the HCA, the normalized signal intensities of the metabolites (unit variance scaling) were visualized as a color spectrum.

2.7. Differential Metabolite Selection, KEGG Annotation, and Enrichment Analysis

Significantly regulated metabolites between groups were determined by absolute Log₂FC (fold change) ≥ 2 and fold change ≤ 0.5. The identified metabolites were annotated using the KEGG compound database [http://www.kegg.jp/kegg/compound/ (accessed on 3 August 2023)], and the annotated metabolites were mapped to the KEGG pathway database [http://www.kegg.jp/kegg/pathway.html (accessed on 3 August 2023)]. Pathways mapped for significantly regulated metabolites were then fed into the metabolite set enrichment analysis (MSEA), and their significance was determined by the hypergeometric test at p < 0.05.

2.8. Statistical Analysis

Statistical analyses were conducted using SPSS software (version 19.0; SPSS, Inc., Chicago, IL, USA). Differences between treatments were evaluated using a t-test, with p < 0.05 considered statistically significant.

3. Results

3.1. Growth Parameters

Compared with the control, plant height and stem diameter increments were significantly decreased by 44.65–63.63% and 48.08–66.21% during the entire treatment period. The leaf length increment was decreased by 46.25% on day 5 and 46.34% on day 10, and the leaf width increment was decreased by 45.46% on day 10 in pepper seedlings under HT stress (Table 1). Fresh leaf, fresh root, dry leaf, and dry root weights significantly decreased by 26.45–43.16%, 12.20–42.87%, 22.39–43.16%, and 20.67–42.87%, respectively, during the entire treatment period for pepper seedlings under HT stress compared with the control. Compared with the HT Control, exogenous SNP significantly increased plant height and stem diameter by 29.55–150.00% and 70.37–142.86%, respectively, during the entire treatment period, and leaf length increased by 30.23% on day 5 and 22.73% on day 10 of pepper seedlings under HT stress. Compared to HT fresh, fresh root, dry leaf, and dry root weights were significantly increased by 19.74–41.67%, 8.27–44.65%, 21.85–41.67%, and 18.49–44.65%, respectively, during the entire treatment period of pepper seedlings induced by exogenous SNP under high HT. Compared with the HT Control, exogenous c-PTIO significantly decreased plant height by 25.00% on day 5 and 62.50% on day 15 and stem diameter by 51.39% on day 10 in pepper seedlings under HT stress. Fresh leaf, fresh root, dry leaf, and dry root weights significantly decreased by 12.06–25.46%, 5.70–30.82%, 10.64–25.46%, and 13.45–30.82%, respectively, during the entire treatment period of pepper seedlings treated with exogenous c-PTIO under HT stress, compared with the HT Control.

3.2. Physiological Parameters

3.2.1. Osmotic Adjustment Substances

Compared with the control, soluble sugar and proline contents were significantly increased by 6.44–34.89% and 11.91–206.11%, respectively, during the entire treatment period, and soluble protein and amino acid contents were decreased by 76.85% and 21.64%, and 25.98%, and 72.88% on days 10 and 15, respectively, in pepper seedlings under HT stress (Figure 2b,c). Compared with the HT Control, exogenous SNP significantly decreased soluble sugar, soluble protein, and proline content by 5.80–23.21%, 13.50–45.55%, and 15.47–40.30%, respectively, during the entire treatment period, and amino acid content decreased by 20.81% and 8.77% on days 5 and 15, respectively, in pepper seedlings under HT stress. Compared with the HT Control, exogenous c-PTIO significantly increased soluble sugar content by 2.97% on day 5 and 5.12% on day 10, soluble protein content increased by 10.43–17.81% during the entire treatment period, and proline content increased by 10.12% and 15.84% on days 5 and 15, respectively, in pepper seedlings under HT stress.

3.2.2. Lipid Peroxidation

HT stress significantly increased electrolytic leakage by 34.37% and 123.63% on days 5 and 15, respectively. MDA content, H₂O₂ content, and O₂^.− formation rate increased by 13.31–85.07%, 16.30–32.93%, and 24.45–82.13% during the entire pepper seedling treatment period, respectively, compared with the control (Figure 3). Compared with the HT Control, exogenous SNP significantly decreased electrolytic leakage by 13.51% and 50.35% at 5 and 15 days, MDA content, H₂O₂ content, and O₂^.− formation decreased rate by 11.81–18.30%, 9.04–16.36%, and 19.80–42.76%, respectively, during the entire pepper seedling treatment period under HT stress. Electrolytic leakage increased by 26.59% on day 5, and the MDA, H₂O₂, and O₂⁻ formation rate increased by 11.20–20.43%, 5.50–14.79%, and 1.92–8.80%, respectively, during the entire pepper seedling treatment period of exogenous c-PTIO under HT stress, compared with that of the HT Control.

3.2.3. Antioxidant Enzyme Activities

HT stress significantly increased SOD and APX activities by 34.06–102.41% and 35.02–71.89% and decreased POD and CAT activities by 28.15–71.64% and 48.23–65.90%, respectively, during the entire pepper seedling treatment, compared with the control (Figure 4). Compared with the HT Control, exogenous SNP significantly decreased SOD and APX activities by 19.01% and 18.61% on day 5 and 34.06% and 37.78% on day 10, respectively, and increased POD and CAT activities by 17.00–104.39% and 73.38–152.52% during the entire pepper seedling treatment period under HT stress. Exogenous c-PTIO decreased SOD activity by 10.49% on day 5, and POD activity by 14.62% and 10.04% on days 5 and 15, respectively, CAT activity decreased by 24.82% on day 10, and APX activity increased by 9.32% on day 10 in pepper seedlings under HT stress compared with the HT Control.

3.2.4. Nitrogen Synthesis and Metabolism-Related Parameters

NO content and NR, GS, GDH, and NOS activities were significantly decreased by 14.44–42.77%, 21.34–39.59%, 6.29–46.13%, 11.47–27.77%, and 19.22–55.50%, respectively, during the entire pepper seedling treatment period under HT stress compared with the control (Figure 5). Compared with HT Control, exogenous SNP significantly increased NO content, and NR, GDH, and NOS activities by 110.44–221.29%, 43.16–86.60%, 20.73–65.77%, and 30.48–133.64%, respectively, during the entire pepper seeding treatment period, and GS increased activity by 95.84% and 101.36% at 10 d and 15 d under HT stress, respectively. Exogenous c-PTIO decreased NO content by 23.62% and 26.18% at 5 and 15 d, respectively, NR activity decreased by 35.74% on day 15, and GDH and NOS activities decreased by 7.49–38.92% and 11.96–29.00%, respectively, during the entire pepper seedling treatment period under HT stress compared with the HT Control.

3.3. Quality Control (QC) of LC-MS Data

Overlapping display analysis was performed on the total ion chromatogram (TIC), and the same QC samples were analyzed using mass spectrometry. The analysis showed that the TIC curves of metabolite detection highly overlapped, indicating consistent retention times across the samples. The peak intensity remained consistent, further confirming the reliability of the MS data and demonstrating the strong signal stability of the MS platform used in the experiment. This consistency suggests that the error introduced by the instrument was minimal when the same sample was evaluated at different time points (Figure S1). Pearson’s correlation analysis of the QC samples indicated high data quality and stability throughout the detection process (Figure S2a). Moreover, the coefficient of variation (CV) highlights the degree of data dispersion, with a CV of 80% for the QC samples being less than 0.2. This further supported the integrity and reliability of the experimental design and results (Figure S2b). PCA demonstrated distinct differentiation patterns in the metabolic profiles among the groups, indicating significant differences between the various treatments and time points (Figure S2c).

3.4. Quantification and Classification of Identified Metabolites

A total of 47 metabolites related to nitrogen metabolism were identified in the 12 samples, of which 44 were in the positive ion mode and three were in the negative ion mode (Table S1). According to the chemical classification of these metabolites, 76.60% were amino acid metabolites, and 20.21% were organic acids and their derivatives (Figure S3). These metabolites were more abundant in the leaves of fresh pepper seedlings. After normalizing the sample data, these trends became more pronounced (Figure 6).

3.5. Differential Metabolite Screening, Categorization, and Correlation

PCA results revealed differences in the metabolomes among the four sample groups (Figure S4). According to the dynamic distribution map of the differential metabolite content, the five metabolites that exhibited the largest increase in the HT Control vs. Control comparison group were N-acetylaspartate, N-acetylneuraminic acid, L-cysteine, L-lysine, and glycine. Conversely, the five metabolites showing the largest decrease in the same comparison group were L-cysteine, γ-glutamic-cysteine, N′-formylkynurenine, 5-hydroxy-tryptophan, and succinic acid (Figure 7a). In the HT SNP vs. HT Control comparison group, the most upregulated metabolites were beta-alanine, γ-glutamate-cysteine, O-phospho-L-serine, ethanolamine, and phosphorylethanolamine. Conversely, the most downregulated metabolites were L-cysteine, creatine, urea, kynurenine, and creatine phosphate (Figure 7b). In the HT c-PTIO vs. HT Control comparison, the five most highly upregulated metabolites were α-glutamate-cysteine, N′-formylkynurenine, L-asparagine anhydrous, L-asparagine anhydrous, and α-aminoadipic acid, whereas the five most highly downregulated metabolites were L-cystine, 5-hydroxy-tryptamine, creatine phosphate, D-alanyl-D-alanine, and N-acetylneuraminic acid (Figure 7c).

Metabolites with VIP > 1, FC ≥ 2, and FC ≤ 0.5 were selected to obtain metabolites with significant differences between different comparison groups. Qualitative and quantitative analyses of the detected metabolites identified 20 metabolites with the greatest significant differences between the groups (Figure 7d–f). In the HT Control vs. Control comparison group, the levels of L-lysine, glycine, N6-acetyl-L-lysine, L-arginine, and L-asparagine anhydrous were significantly increased, and the levels of γ-glutamate-cysteine and N′-formylkynurenine were significantly decreased (Figure 7d). In the HT SNP vs. HT Control comparison group, the levels of creatine, urea, kynurenine, creatine phosphate, and L-methionine were significantly decreased (Figure 7e). In the HT c-PTIO vs. HT Control comparison group, the levels of γ-glutamate-cysteine, N′-formylkynurenine, L-asparagine anhydrous, and 2-aminobutyric acid were significantly increased, and the content of 5-hydroxy-tryptamine was significantly decreased (Figure 7f). Pearson’s correlation analysis revealed that metabolites belonging to the same class exhibited a positive correlation and a similar accumulation trend, whereas metabolites with opposite trends in concentration belonged to distinct classes (Figure 7g–i). The urea content in the HT SNP vs. HT Control comparison negatively correlated with creatine phosphate and positively correlated with L-methionine, N-acetyl-L-tyrosine, 5-hydroxy-tryptamine, creatine, kinurenine, and L-cystine.

3.6. KEGG Analysis of Differentially Accumulated Metabolites

In the HT Control vs. Control, HT SNP vs. HT Control, and HT c-PTIO vs. HT Control comparisons, 44, 8, and 5 differentially accumulated metabolites were identified, respectively (Figure 8a). Venn diagram analysis revealed that in the HT Control vs. Control comparison, 36 metabolites differentially accumulated during the treatment. Two metabolites exhibited differential accumulation owing to SNP treatment, whereas only one metabolite was induced by c-PTIO treatment under HT stress (Figure 8b). Based on the KEGG pathway analysis, the metabolic pathways that were significantly enriched in the HT Control vs. Control, HT SNP vs. HT Control, and HT c-PTIO vs. HT Control comparisons were cyanoamino acid, biotin, and biotin metabolism, respectively (Figure 9a–c). Cluster analysis indicated that SNP treatment resulted in significant differential accumulation of various metabolites during the treatment period, including organic acids and their derivatives (creatine phosphate, kinurenine, and creatine) and amino acid metabolomics (L-cysteine, 5-hydroxy-tryptamine, L-methionine, urea, and N-acetyl-L-tyrosine) (Figure 10a–c).

3.7. Correlation Analysis of Biochemical Indicators and Metabolomic Data

Based on the biochemical indicator-metabolite correlation heat map, chlorophyll content, electrolytic leakage, O₂^.−, MDA, soluble sugar, proline, soluble protein, and H₂O₂ content exhibited significant positive correlations with kinurenine, N-acetyl-L-tyrosine, L-methionine, and urea (Figure 11). Conversely, CAT, GS, POD, NR, GDH, and NOS activities were significantly negatively correlated with kinurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine levels. NO content was significantly negatively correlated with kinurenine, L-methionine, urea, and creatinine.

4. Discussion

High-temperature stress significantly affects various physiological and biochemical processes in plants, resulting in reduced growth and altered metabolic profiles. Consistent with previous studies, our research demonstrated that HT stress significantly decreased plant height, stem thickness, leaf length, leaf width, and biomass accumulation in pepper plants, indicating impaired growth and development under HT conditions. For instance, similar reductions in plant height due to inhibited cell elongation and division have been observed in rice [29], while wheat showed decreased stem thickness associated with inhibited lignification and secondary growth under HT stress [30]. Our findings align with these observations, suggesting that the growth reduction in pepper plants under HT stress is a common physiological response across different crops. Moreover, HT stress led to increased contents of soluble sugars, soluble proteins, amino acids, and proline in our study, suggesting an adaptive response to maintain osmotic balance and protect cellular structures. These findings agree with previous research, which also reported elevated levels of these osmoprotectants in wheat, rice, and maize under HT conditions [31,32,33,34,35,36]. The increase in osmoprotectants like soluble sugars and proline under HT stress is a well-documented defense mechanism that helps plants mitigate the adverse effects of heat [33,34]. The exogenous application of SNP, a NO donor, mitigated the adverse effects of HT stress in our study by enhancing growth parameters and improving metabolic profiles in pepper plants. Specifically, SNP-treated plants exhibited increased plant height, stem thickness, leaf length, leaf width, and biomass compared to untreated plants under HT stress, similar to how SNP has been reported to improve growth parameters in rice and enhance biomass accumulation by modulating antioxidant defense systems and reducing oxidative damage [37,38]. Our findings support the protective role of NO and its related pathways under HT stress, as demonstrated by previous studies. Conversely, the application of c-PTIO, an NO scavenger, exacerbated the negative effects of HT stress in our study. c-PTIO-treated plants showed further reductions in growth parameters and lower levels of soluble sugars, soluble proteins, amino acids, and proline than untreated plants, highlighting the detrimental effects of scavenging beneficial NO. This observation is consistent with previous research that underscores the importance of NO in maintaining plant stress responses [39].

Our study also observed that HT stress significantly increased oxidative stress markers such as electrolytic leakage, MDA content, H₂O₂ content, and the formation rate of O₂^.- in pepper plants, indicating severe oxidative stress and membrane damage. These results are consistent with previous findings that HT stress leads to increased electrolytic leakage, MDA content, and ROS accumulation in various crops [40,41,42]. Additionally, the activities of antioxidant enzymes such as SOD and APX were increased in response to elevated ROS levels, while CAT and POD activities were decreased, possibly due to enzyme denaturation or substrate depletion. These observations are in line with studies that report variable responses of antioxidant enzymes under HT stress, with some showing increased activity as a protective response and others indicating a decline [43]. The exogenous application of SNP reduced oxidative stress markers and enhanced the activities of antioxidant enzymes in our study, suggesting improved ROS scavenging and protection against oxidative damage. This is consistent with previous studies that have shown SNP application reduces oxidative damage and enhances antioxidant defenses in crops such as rice and tomatoes under HT stress [26,44]. Conversely, c-PTIO application increased oxidative stress markers and reduced antioxidant enzyme activities, further supporting the protective role of NO in plant stress responses [45].

Previous studies have shown that HT stress can alter NO content and the activities of NR, GS, GDH, and NOS in various plants [46]. For instance, HT has been reported to reduce NR and GS activities in wheat, negatively affecting nitrogen assimilation [27]. Similarly, GDH activity is altered under HT stress, which affects amino acid catabolism and nitrogen remobilization [47]. NOS activity, which is critical for NO production, can be influenced by environmental stressors, including heat, which affect NO-mediated signaling pathways [48]. Metabolomic studies have identified significant changes in the amino acid metabolism under HT stress. Increased levels of kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine have been observed in various crops, indicating stress-induced alterations in metabolic pathways [49]. These metabolites are associated with stress responses and provide insights into the physiological state of plants under adverse conditions. In the present study, HT stress significantly decreased the NO content and activity of NR, GS, GDH, and NOS in pepper plants. This reduction indicates impaired nitrogen metabolism and NO synthesis under HT conditions. Metabolomic analysis revealed increased levels of kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine, suggesting significant alterations in amino acid metabolism pathways caused by HT stress. Exogenous application of SNP mitigated these adverse effects by enhancing NO content and increasing the activities of NR, GS, GDH, and NOS in pepper plants under HT stress. SNP treatment also normalized the levels of amino acid metabolites and reduced stress-induced accumulation of kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine. Conversely, the application of c-PTIO further exacerbated the negative effects of HT stress, significantly reducing NO content and enzyme activities and leading to higher levels of stress-related amino acid metabolites. Our findings are consistent with those of previous studies, indicating the protective role of NO and its associated metabolic pathways under HT stress. For example, SNP has been shown to enhance NO levels and improve nitrogen metabolism and stress tolerance in various crops [50,51]. The reduction in stress-related amino acid metabolites following SNP treatment aligns with studies demonstrating the role of NO in regulating amino acid metabolism and mitigating stress-induced metabolic imbalances [52]. The detrimental effects of c-PTIO on NO content, enzyme activity, and amino acid metabolites further underscore the importance of NO in plant stress responses [53].

5. Conclusions

HT stress significantly reduced plant height, stem thickness, leaf length, leaf width, and biomass in pepper plants, while increasing soluble sugar, soluble protein, amino acid, and proline content as adaptive responses. HT also induces oxidative damage, as evidenced by increased electrolytic leakage, MDA content, H₂O₂ content, and O₂^.− formation rate, along with altered antioxidant enzyme (SOD, POD, CAT, and APX) activity. Additionally, HT stress reduced NO content and the activities of NR, GS, GDH, and NOS, leading to changes in amino acid metabolism. Exogenous SNP effectively mitigated the adverse effects of HT stress by enhancing growth parameters, improving osmotic and metabolic adjustments (kynurenine, N-acetyl-L-tyrosine, L-methionine, urea, and creatine), and boosting antioxidant defense mechanisms (Figure 12). Conversely, c-PTIO exacerbated the negative effects of HT stress by reducing the beneficial NO levels and impairing stress responses. Based on the findings, it is recommended that exogenous SNP be strategically used as a protective agent in pepper cultivation to enhance crop resilience under high-temperature conditions. The ability of SNP to mitigate the adverse effects of HT stress by improving growth parameters, osmotic and metabolic adjustments, and boosting antioxidant defense mechanisms suggests its potential for broader application in agricultural practices. Future research should focus on elucidating the molecular mechanisms underlying SNP’s protective effects and determining optimal application strategies for different environmental conditions. Additionally, the impact of SNP on other crops under various stress conditions warrants further investigation to expand its utility in enhancing crop tolerance in diverse agricultural systems.

Author Contributions

Conceptualization, Y.Z. and K.L.; methodology, Y.Z.; software, Y.Z.; validation, Y.Z., Q.L., and X.Y.; formal analysis, L.W.; investigation, X.L.; resources, Y.Z.; data curation, Y.Z.; writing—original draft preparation, Y.Z.; writing—review and editing, Y.Z.; visualization, Y.Z.; supervision, K.L.; project administration, K.L.; funding acquisition, K.L. and Y.Z. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

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

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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Figures and Table

Figure 1. Effects of NO on phenotype of pepper seedlings under high-temperature stress.

Figure 2. Effects of NO on soluble sugar content (a), soluble protein content (b), amino acid content (c), and proline content (d) of pepper seedlings under high-temperature stress. Each value is the mean ± standard error (n = 3), and the error bars represent the standard error. Bars with a different letter within a sampling date are significantly different (p [less than] 0.05).

Figure 3. Effects of NO on electrolytic leakage (a), MDA content (b), H2O2 content (c), and O2.− formation rate (d) of pepper seedlings under high-temperature stress. Each value is the mean ± standard error (n = 3), and the error bars represent the standard error. Bars with a different letter within a sampling date are significantly different (p [less than] 0.05).

Figure 4. Effects of NO on SOD (a), POD (b), CAT (c), and APX (d) of pepper seedlings under high-temperature stress. Each value is the mean ± standard error (n = 3), and the error bars represent the standard error. Bars with a different letter within a sampling date are significantly different (p [less than] 0.05).

Figure 5. Effects of NO on NO content (a), NR activity (b), GS activity (c), GDH activity (d), and NOS activity (e) of pepper seedlings under high-temperature stress. Each value is the mean ± standard error (n = 3), and the error bars represent the standard error. Bars with a different letter within a sampling date are significantly different (p [less than] 0.05).

Figure 6. Overall clustering map of the sample.

Figure 7. Differential metabolite screening. (a–c) show the dynamic distribution of differential metabolic content, (d–f) present the bar chart of differential multiples, (g–i) display the chord diagram of differential metabolites. (a,d,g) HT_Control_vs_Control, (b,g,h) HT_SNP_vs_HT_Control, (e,f,i) HT_c-PTIO_vs_HT_Control.

Figure 8. Differential metabolite counts (a) and Venn analysis between comparison groups (b).

Figure 9. KEGG and heat map analysis of differential metabolites between comparison groups: (a) HT_Control_vs_Control, (b) HT_SNP_vs_HT_Control, and (c) HT_c-PTIO_vs_HT_Control.

Figure 10. Heat map analysis of differential metabolites between comparison groups: (a) HT_Control_vs_Control, (b) HT_SNP_vs_HT_Control, and (c) HT_c-PTIO_vs_HT_Control.

Figure 11. Correlation analysis of biochemical indexes and differential metabolites in NO-treated pepper seedlings at day 15 of treatment. Statistical significance is indicated by asterisks: * p [less than] 0.05, ** p [less than] 0.01, ** p < 0.001.

Figure 12. Patterns of exogenous NO on pepper under high-temperature stress.

Table 1

Effects of exogenous NO on growth indexes of pepper seedlings under high-temperature stress.

Treatment	Time	Plant Height Increment (cm)	Stem Diameter Increment(mm)	Leaf Length Increment(cm)	Leaf Width Increment(cm)	Leaf Fresh Weight (g)	Leaf Dry Weight (g)	Root Fresh Weight(g)	Root Dry Weight (g)
Control	5 d	2.65 ± 0.07 a	0.73 ± 0.02 a	2.00 ± 0.10 a	1.10 ± 0.10 a	12.67 ± 0.61 a	1.09 ± 0.05 a	2.78 ± 0.02 a	0.30 ± 0.00 a
HT_Control		1.47 ± 0.12 c	0.25 ± 0.01 c	1.08 ± 0.10 c	0.65 ± 0.07 bc	7.20 ± 0.10 c	0.62 ± 0.01 c	1.59 ± 0.01 c	0.17 ± 0.00 c
HT_SNP		1.90 ± 0.10 b	0.60 ± 0.06 b	1.40 ± 0.10 b	0.85 ± 0.07 ab	10.20 ± 0.10 b	0.88 ± 0.01 b	2.30 ± 0.10 b	0.25 ± 0.01 b
HT_c-PTIO		1.10 ± 0.00 d	0.26 ± 0.01 c	0.93 ± 0.15 c	0.45 ± 0.07 c	5.37 ± 0.15 d	0.46 ± 0.01 d	1.10 ± 0.10 d	0.12 ± 0.01 d
Control	10 d	2.20 ± 0.00 a	0.77 ± 0.04 a	1.37 ± 0.12 a	0.55 ± 0.07 a	20.67 ± 0.61 a	1.41 ± 0.02 a	4.78 ± 0.02 a	0.39 ± 0.01 a
HT_Control		0.80 ± 0.00 c	0.36 ± 0.03 c	0.73 ± 0.06 c	0.30 ± 0.00 b	15.20 ± 0.10 c	1.07 ± 0.01 c	3.59 ± 0.01 c	0.29 ± 0.02 c
HT_SNP		1.35 ± 0.07 b	0.63 ± 0.05 b	0.90 ± 0.00 b	0.40 ± 0.00 b	18.20 ± 0.10 b	1.33 ± 0.01 b	4.30 ± 0.10 b	0.36 ± 0.01 b
HT_c-PTIO		0.67 ± 0.06 c	0.18 ± 0.01 d	0.75 ± 0.06 bc	0.27 ± 0.06 b	13.37 ± 0.15 d	0.94 ± 0.03 d	3.10 ± 0.10 d	0.24 ± 0.02 d
Control	15 d	0.90 ± 0.00 a	0.26 ± 0.00 a	0.07 ± 0.06 a	0.30 ± 0.00 a	25.67 ± 0.61 a	1.53 ± 0.02 a	9.78 ± 0.02 a	0.50 ± 0.01 a
HT_Control		0.40 ± 0.00 b	0.14 ± 0.01 b	0.00 ± 0.00 a	0.00 ± 0.00 b	18.20 ± 0.10 c	1.19 ± 0.01 c	8.59 ± 0.01 c	0.40 ± 0.02 c
HT_SNP		1.00 ± 0.00 a	0.23 ± 0.04 a	0.08 ± 0.10 a	0.00 ± 0.00 b	23.20 ± 0.10 b	1.45 ± 0.01 b	9.30 ± 0.10 b	0.47 ± 0.01 b
HT_c-PTIO		0.15 ± 0.07 c	0.14 ± 0.01 b	0.02 ± 0.05 a	0.00 ± 0.00 b	15.37 ± 0.15 d	1.06 ± 0.03 d	8.10 ± 0.10 d	0.34 ± 0.02 d

Values are means ± SD (n = 3). Values with a different letter within a sampling date are significantly different (p < 0.05).

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae10090906/s1, Figure S1: TIC overlay map; Figure S2: Sample quality control analysis. (a) correlation analysis of QC samples, (b) plot of CV distribution in each group of samples and (c) PCA scores of mass spectrometry data for each group of samples; Figure S3: Biochemical classification and quantitative proportion of identified metabolites; Figure S4: Subgroup principal component analysis. (a) HT_Control and Control groups, (b) HT_SNP and HT_Control groups, and (c) HT_c-PTIO and HT_Control groups; Table S1: The detail of amino acid metabolites identified.

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