Integrated histochemical, biochemical, and ultrastructural analyses elucidate synergistic virulence mechanisms of Curvularia lunata in maize

Abstract

Curvularia lunata is a destructive maize pathogen, but the interplay between its infection strategy and toxin production remains unresolved. We identified C. lunata using multilocus sequence analysis of ITS rDNA, GAPDH, and TEF1α regions and profiled its metabolites, revealing methyl-5-hydroxyfuran-2-carboxylate (M5HF2C) as the dominant toxin along with citrinin, endocrocin, and butyrolactone II. Maize plants (7–8 days old) exposed to pathogen inoculum, crude metabolite extract, or purified M5HF2C exhibited progressive necrotic and chlorotic lesions. Physiological assays demonstrated severe pigment loss (up to 79%), electrolyte leakage (88%), and lipid peroxidation (9.7-fold increase), while histochemical staining and ultrastructural imaging confirmed ROS accumulation and cellular collapse. Antioxidant and defense enzymes (SOD, CAT, APX, POX, GR, GPX, PPO, and PAL) were strongly induced but insufficient to prevent damage. Notably, the severity of effects followed the order pathogen > crude metabolite > purified toxin, underscoring the synergistic contribution of multiple virulence factors to pathogenesis. Together, these results establish oxidative stress and combined metabolite action as the central drivers of Curvularia virulence in maize.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1038/s41598-026-57936-x.

Introduction

Maize (Zea mays L.) is one of the most important cereal crops worldwide, serving as a staple food, livestock feed, and industrial raw material. Global maize production exceeded 1.2 billion tonnes in 2022, highlighting its pivotal role in food security and economic sustainability¹. In developing countries, maize contributes directly to human nutrition, while in industrialized nations, it is also a key biofuel and feedstock². However, its productivity is continually constrained by both abiotic and biotic stresses, of which fungal pathogens represent a major limiting factor³.

Among these pathogens, Curvularia lunata (Wakker) Boedijn is a significant causal agent of Curvularia leaf spot (CLS), a destructive foliar disease of maize. CLS is widely distributed across tropical and subtropical maize-growing regions, where warm and humid conditions promote disease outbreaks⁴. The disease is characterized by necrotic lesions with chlorotic halos, reduced photosynthetic capacity, and premature leaf senescence, ultimately leading to yield losses of up to 30–40% in severe cases⁵. The increasing frequency of C. lunata epidemics, exacerbated by climate change and intensive monoculture practices, underscores the pathogen’s rising threat to global maize production⁶.

The virulence of C. lunata is strongly associated with toxin production, which facilitates host colonization and symptom development. Several toxic metabolites, including furanoid derivatives, have been isolated, with methyl 5-(hydroxymethyl) furan-2-carboxylate (M5HF2C) identified as a major non-host-specific toxin⁷. M5HF2C induces necrosis, chlorosis, and growth inhibition in maize and other plants⁸. Its biosynthesis follows a pathway involving the conversion of xylose to furfural and, subsequently, to furoic acid, with the alcohol dehydrogenase gene (ClADH6) playing a crucial role⁸. Genetic disruption of ClADH6 impairs toxin accumulation and significantly reduces virulence, confirming M5HF2C as a key pathogenic determinant⁹. In addition to M5HF2C, polyketides such as curvularin have also been implicated in pathogenesis, although their precise roles remain less defined¹⁰.

Host plants counteract Curvularia infection through multifaceted defense responses. A primary event during pathogen attack is the overproduction of reactive oxygen species (ROS), including superoxide anion, hydrogen peroxide, and hydroxyl radicals. While ROS act as signalling molecules in defense, their uncontrolled accumulation leads to lipid peroxidation, protein oxidation, and programmed cell death^11,12. To mitigate ROS toxicity, plants activate both enzymatic antioxidants, such as superoxide dismutase (SOD), catalase (CAT), peroxidases (POD), and glutathione reductase (GR), and non-enzymatic molecules, such as ascorbate and glutathione^13,14. Enhanced antioxidant activity has been reported in maize infected with C. lunata, reflecting an adaptive mechanism to restore redox homeostasis¹⁵.

Another hallmark of pathogen-induced stress is the disruption of photosynthetic pigments. Infection reduces chlorophyll and carotenoid content, impairing light harvesting and photoprotection, which manifests as leaf chlorosis and reduced photosynthetic efficiency¹⁶. Toxin treatments produce similar pigment degradation patterns, implicating both direct colonization and metabolite activity in disease expression¹⁷.

Furthermore, maize plants subjected to Curvularia attack accumulate osmolytes such as proline, which function as compatible solutes to maintain osmotic balance, protect cellular structures, and scavenge ROS¹⁸. Elevated proline levels have been consistently associated with stress tolerance in maize and other crops under fungal infection. In parallel, infection disrupts membrane integrity, leading to increased electrolyte leakage and malondialdehyde (MDA) accumulation, both of which indicate oxidative damage and lipid peroxidation¹⁹.

Despite advances in characterizing C. lunata toxins and host responses, there remains a paucity of studies that directly compare maize responses to (i) whole pathogen inoculation, (ii) crude metabolite mixtures, and (iii) purified toxins. Such comparative analyses are critical to disentangle the synergistic effects of multiple virulence factors from the independent roles of single toxins. Addressing this gap will provide new insights into maize-Curvularia interactions and inform breeding programs aimed at developing resistant cultivars.

Therefore, the present study aimed to investigate the time-course physiological and biochemical responses of maize (cv. Pratap Chari Makka-6) when challenged with C. lunata spore suspension, crude metabolite extracts, and purified M5HF2C toxin. By monitoring oxidative stress markers, antioxidant activities, pigment content, osmolyte accumulation, and electrolyte leakage over 0–120 h, this work provides an integrative perspective on the relative contributions of pathogen invasion, complex metabolite cocktails, and individual toxins in disease progression.

Results

Isolation and identification of pathogen

Preliminary microscopic observations of morphological features suggested the pathogen as C. lunata. Infected maize leaves displayed typical leaf spot symptoms, appearing as small, circular to oval, brown lesions with dark margins that often coalesced, resulting in blight under severe infection. In culture, the fungus produced fast-growing, dark olivaceous to black colonies. Microscopic examination revealed septate, branched mycelium and geniculate conidiophores. Conidia were brown, curved (lunulate), and 3–4 septate, with an enlarged, darker central cell and tapering ends. The conidial dimensions ranged from 19.4 ± 2.2 µM in length and 9.9 ± 1.0 µM in width (mean ± SD), consistent with the diagnostic features of C. lunata (Fig. 1a-c). This identification was confirmed using pathogen-specific primers targeting the ITS (including 5.8 S rDNA region), GAPDH, and TEF1α regions. Amplification of the ITS region yielded an amplicon of approximately 500–600 bp, and the obtained sequences were deposited in GenBank under accession numbers ITS (PQ035148), GAPDH (PX965981), and TEF1α (PZ051146) (Fig. 1d & Supplementary Fig. S1).

Fig. 1.

Isolation and identification of Curvularia lunata from infected maize plant, (a). Infected maize plant leaf, (b). Fungal colony on PDA culture media, (c). Microscopic view of fungus (40 µM scale), (d). Gel electrophoresis of the PCR product with primers ITS1 and ITS4 of DNA from the fungal isolate. Lane 1: molecular weight marker (100 bp ladder), lane 2: Curvularia lunata (500 bp to 600 bp).

Extraction of the crude toxic metabolites

Crude toxic metabolites were successfully obtained from 20-day-old C. lunata cultures. The extracts appeared as a concentrated brown residue that dissolved readily in methanol and were used for further pathogenicity and toxicity studies.

Pathogenicity test and toxicity assessment

By the third day of treatment, symptoms began to appear, with leaves developing pale brown to grayish spots surrounded by yellow margins. In addition, necrotic and chlorotic patches were observed, while the control plants remained healthy. These observations confirmed the pathogenicity, virulence, and toxicity of the pathogen and its metabolites.

Characterization of crude metabolite

HPLC analysis

Quantitative HPLC analysis confirmed the presence of methyl-5-hydroxyfuran-2-carboxylate (M5HF2C) in crude extracts of Curvularia. The compound was detected at a retention time of 5.987 min, matching the standard profile. The compound was identified based on retention time matching with an authentic standard analyzed under identical conditions, and quantification was performed using a calibration curve. The chromatogram showed a single sharp peak with an area of 24,200,064 (100% area) and a height of 3,146,437 (100% height), indicating high purity of the eluted compound and confirmed that M5HF2C was the predominant metabolite under the applied extraction and separation conditions (Fig. 2a).

Fig. 2.

(a). HPLC chromatogram of crude metabolite showing peak of M5HF2C at RT 5.987, (b). LC-HRMS Chromatogram (ES+ mode, BPI), (c). LC-HRMS Chromatogram (ES- mode, BPI).

Metabolic profiling using LC-HRMS analysis

LC-HRMS chromatograms of C. lunata extracts were performed in an untargeted mode using both positive (ESI+, BPI) and negative (ESI-, BPI) electrospray ionization modes. The ESI+ chromatogram (Fig. 2b) revealed a complex profile of secondary metabolites detected within a retention time range of 8.9–22.5 min and precursor ions spanning m/z 401–522. Most compounds showed high spectral similarity (> 95%), indicating reliable identification. Metabolites were putatively annotated based on accurate mass measurements, isotopic distribution, and MS/MS fragmentation patterns, supported by database searches and literature comparison. The detected metabolites included the dominant toxin M5HF2C along with citrinin, endocrocin, butyrolactone II, benzomalvin B, deferoxamine, dethiobiotin, atranol, axinyssimide A, and hapalindole D, highlighting the toxigenic and metabolically diverse nature of the pathogen (Supplementary Table 1). In contrast, the ESI- chromatogram (Fig. 2C) displayed a comparatively simpler profile with fewer but relatively intense peaks, representing compounds preferentially ionized under negative mode conditions, with peak intensity reflecting their relative abundance.

Treatment of pathogen, crude metabolite and toxin to pot-cultured maize plants

Maize seedlings treated with C. lunata spores, crude metabolites, and the standard toxin (M5HF2C) developed pale brown to grayish spots with yellow margins, along with necrotic and chlorotic patches within 3–4 days. Control plants remained symptom-free. Comparable responses across treatments confirmed the pathogenicity of C. lunata and the toxicity of its metabolites.

Qualitative analysis of histochemical changes

Cell death assay

Cell death was assessed using Evans blue staining, which selectively labels non-viable cells. Pathogen-infected tissues exhibited intense blue coloration, indicating maximum cell death, followed by crude metabolite-treated tissues, and then M5HF2C-treated tissues, while control samples remained unstained. The progressive reduction in staining intensity across treatments reflects a gradient in cytotoxic effects.

These observations suggest that the intact pathogen induces more severe cellular damage compared to its derived metabolites and toxin (Fig. 3I a-h).

Fig. 3.

(3I). Cell death assay in maize leaves by Evans blue staining, (3II). Hydrogen peroxide production in maize leaves visualized by DAB staining, (3III). Superoxide ion production in maize leaves visualized by NBT staining; (a). control leaf, (b). microscopic view (scale = 40 µM), (c). M5HF2C treated leaf, (d). microscopic view (scale = 40 µM), (e). crude metabolite treated leaf, (f). microscopic view (scale = 40 µM), (g). pathogen treated leaf, (h). microscopic view (scale = 40 µM).

Detection of hydrogen peroxide (H₂O₂) accumulation

Hydrogen peroxide (H₂O₂) production, visualized by 3,3′-diaminobenzidine (DAB) staining, appeared as reddish-brown deposits indicating reactive oxygen species accumulation. A clear gradient in staining intensity was observed among treatments. Pathogen-infected tissues showed the highest H₂O₂ accumulation, with intense and widespread deposition, reflecting a strong oxidative burst. This was followed by crude metabolite-treated tissues, which exhibited moderate staining, indicating a reduced yet noticeable response. In contrast, toxin-treated tissues displayed faint to mild staining, suggesting minimal H₂O₂ accumulation. Control tissues showed negligible staining.

Overall, the results indicate that the complete pathogen elicits a stronger oxidative response than its isolated components (Fig. 3II a-h).

Detection of superoxide (O₂^·-) radicals

Superoxide (O₂·⁻) radical generation was visualized by NBT staining, where dark blue formazan deposits indicated superoxide presence. Pathogen-infected leaves showed the strongest staining, followed by crude metabolite and M5HF2C treatments, while control leaves exhibited negligible coloration.

The observed gradient in staining intensity reflects a corresponding increase in oxidative stress across treatments. This suggests that pathogen infection triggers a more pronounced superoxide burst compared to its derived metabolites and toxins (Fig. 3III a-h).

Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) analysis

Scanning electron microscopy (SEM) images showed that pathogen-infected leaves suffered the most visible damage, with collapsed cells and disrupted tissue surfaces. Crude metabolite treatment also caused noticeable surface injury, while M5HF2C led to only mild changes. In contrast, control leaves remained intact (Fig. 4I a-d). Transmission electron microscopy (TEM) observations supported these findings: pathogen infection severely distorted cellular ultrastructure, with broken walls, plasmolysis, and disorganized organelles. Crude metabolites produced moderate changes, whereas M5HF2C caused relatively minor alterations. Control cells displayed healthy structures with intact walls, membranes, and organelles (4II a-d).

Fig. 4.

Electron microscopic images of control and treated maize leaves; (4I). Surface view of plant samples in SEM images, (4II). TEM images showing damage in internal tissue in the treated maize plant leaf sample as compared to the control leaf, (a). Control leaf, (b). M5HF2C treated leaf, (c). Crude metabolite treated leaf, (d). Pathogen treated leaf.

Effect on photosynthetic machinery

Plant pigment levels were monitored from 0 to 120 h post-infection to evaluate the impact of pathogen, crude metabolite, and M5HF2C treatments on maize photosynthetic machinery. A gradual decline in chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids was observed over time, with pathogen infection causing the most severe losses. Chlorophyll a decreased by 77.73% in pathogen-infected plants, 68.61% with crude metabolites, and 44.32% with M5HF2C (Fig. 5a). Similarly, chlorophyll b declined by 82.18%, 70.82%, and 54.36%, respectively (Fig. 5b). Total chlorophyll dropped by 79.23% under pathogen infection, 69.49% with crude metabolites, and 48.33% with M5HF2C (Fig. 5c). Carotenoids followed the same trend, decreasing by 77.32%, 64.99%, and 41.88%, respectively. In contrast, control plants maintained stable pigment levels (Fig. 5d).

Fig. 5.

Effect on plant pigments of control and treated maize plants, (a). Chlorophyll a, (b). Chlorophyll b, (c). Total chlorophyll, (d). Carotenoids, Bars are means of three replicates ± SE. Different letters on bars showed significant changes at p ≤ 0.0001 compared using Tukey’s test.

Assessment of quantification of histochemical changes, membrane damage, lipid peroxidation and proline accumulation

Quantification of Evans blue stain

Quantification of dye uptake revealed a time-dependent increase, initiating at 12 h, significantly rising by 72 h (3-8-fold), and reaching maximum accumulation at 120 h (5-9-fold) compared to controls. Among treatments, pathogen infection caused the highest cell death (9.24-fold), followed by crude metabolites (7.48-fold) and M5HF2C toxin (5-fold).

This progressive increase indicates a sustained and intensifying cellular damage over time. The observed trend further confirms that the intact pathogen exerts a stronger cytotoxic effect than its derived components (Fig. 6a).

Fig. 6.

Quantification of histochemical parameters and evaluation of stress markers, (a). Cell death assay by Evans blue dye quantification, (b). Quantification of H₂O₂ production, (c). Superoxide ion production by formazan quantification, (d). Cell membrane damage by evaluating electrolyte leakage, (e). Lipid peroxidation by estimating MDA content, (f). Proline content. Bars are means of three replicates ± SE. Different letters on bars showed significant changes at p ≤ 0.0001 compared using Tukey’s test.

Quantification of hydrogen peroxide (H₂O₂)

Quantitative analysis revealed a rapid increase in H₂O₂ accumulation as early as 12 h post-inoculation, reaching a peak at 72 h, followed by a gradual decline across all treatments. Pathogen infection induced the highest level of H₂O₂ accumulation (14.65-fold), followed by crude metabolites (11.84-fold) and M5HF2C toxin (7.56-fold) compared with control leaves. The early surge in H₂O₂ levels indicates the activation of an oxidative burst as an immediate defense response. The subsequent decline may reflect the activation of antioxidant systems or cellular adaptation to oxidative stress. Overall, the trend confirms that the intact pathogen elicits a stronger oxidative response than its derived components (Fig. 6b).

Quantification of superoxide (O₂⁻) ions

Quantitative analysis of superoxide ions was done indirectly by quantifying formazan content, which revealed a sharp rise up to 72 h, with maximum accumulation in pathogen-infected samples (8.86-fold), followed by crude metabolites (6.28-fold) and M5HF2C toxin (3.43-fold). Thereafter, O₂⁻ levels declined gradually in all treatments. This trend indicates a transient oxidative burst, with the highest intensity observed in pathogen-infected tissues compared to its derived components (Fig. 6c).

Determination of electrolyte leakage

Electrolyte leakage increased progressively from 12 h post-infection, rising sharply between 48 and 72 h and continuing to increase up to 120 h. Pathogen-infected leaves exhibited the highest leakage (87.78%), followed by crude metabolite (77.96%) and M5HF2C treatments (66.37%), whereas control samples maintained stable levels. Overall, EL% showed a clear time-dependent increase, with maximum damage recorded in pathogen-infected plants (Fig. 6d).

Lipid peroxidation (LPO)

Lipid peroxidation, measured as malondialdehyde (MDA) content, increased steadily in infected leaves, peaking at 72 h post-inoculation before declining by 120 h (Fig. 6e). At 72 h, the highest activity was recorded in pathogen-infected samples (9.75-fold), followed by crude metabolite (7.92-fold) and M5HF2C treatments (5.32-fold), compared with control plants.

Proline content

Proline content increased progressively with time, beginning at 24 h, rising sharply until 96 h, and stabilizing thereafter (Fig. 6f). The highest accumulation was recorded in pathogen-infected plants (9.60-fold), followed by crude metabolite (6.97-fold) and M5HF2C treatments (5.37-fold), while control samples showed no significant change.

Antioxidant and defense enzyme activities

Superoxide dismutase (SOD) activity

Superoxide dismutase (SOD) is the primary defense enzyme against superoxide radicals, converting them into less harmful products. In the present study, SOD activity was first detected at 12 h post-infection and increased markedly by 72 h. At this time point, pathogen-infected plants exhibited the highest activity, with a 16.77-fold increase compared to the control, followed by crude extract-treated plants (14.17-fold) and M5HF2C-treated plants (11.31-fold). Beyond 72 h, enzyme activity declined gradually at 96 and 120 h, indicating that early SOD induction plays a vital role in mitigating oxidative stress triggered by fungal infection (Fig. 7a).

Fig. 7.

Antioxidant enzyme activities in treated and control maize leaves, (a). Superoxide dismutase (SOD) activity, (b). Catalase (CAT) activity, (c). Ascorbate peroxidase (APX) activity, (d). Peroxidase (POX) activity. Bars are means of three replicates ± SE. Different letters on bars showed significant changes at p ≤ 0.0001 compared using Tukey’s test.

Catalase (CAT) activity

Catalase activity in maize plants increased steadily from 0 to 72 h in all treated samples, followed by a gradual decline up to 120 h. The highest activity was recorded in pathogen-infected plants (8.93-fold increase), followed by crude extract-treated plants (7.35-fold), and M5HF2C-treated plants (5.21-fold), when compared with the control (Fig. 7b).

Ascorbate peroxidase (APX) activity

Ascorbate peroxidase (APX) has a much higher affinity for H₂O₂ than catalase, making it an efficient scavenger of hydrogen peroxide under stress conditions. In this study, APx activity increased from 0 to 72 h after pathogen inoculation and metabolite treatment, followed by a gradual decline up to 120 h. The highest activity was observed in pathogen-infected plants (5.60-fold increase), followed by crude extract-treated plants (4.60-fold) and M5HF2C-treated plants (3.46-fold), when compared with the control (Fig. 7c).

Peroxidase (POX) activity

Peroxidase (POX) activity showed a similar trend, showing a steady increase from 0 to 72 h, followed by a gradual decline up to 120 h in all treated samples. The highest activity was recorded in pathogen-infected plants (19.34-fold increase), followed by crude extract-treated plants (14.53-fold) and M5HF2C-treated plants (9.66-fold), compared with the control (Fig. 7d).

Glutathione reductase (GR) activity

Glutathione reductase (GR) activity peaked at 72 h in all treated samples, with the highest increase in pathogen-infected plants (9.68-fold), followed by crude extract-treated (7.9-fold) and M5HF2C-treated plants (4.46-fold), compared to the control. Activity then declined and stabilized at 120 h. This elevated GR activity underscores the role of glutathione-mediated ROS detoxification in strengthening the plant’s antioxidant defense system (Fig. 8a).

Fig. 8.

Activities of plant defense enzymes, (a). Glutathione reductase (GR) activity, (b). Guaiacol peroxidase (GPX) activity, (c). Polyphenol oxidase (PPO) activity, (d). Phenylalanine ammonia-lyase (PAL) activity. Bars are means of three replicates ± SE. Different letters on bars showed significant changes at p ≤ 0.0001 compared using Tukey’s test.

Guaiacol peroxidase (GPX) activity

Guaiacol peroxidase (GPX) activity increased gradually, peaked at 72 h post-infection, and then declined up to 120 h. The highest activity was recorded in pathogen-infected plants (8.09-fold increase), followed by crude extract-treated plants (6.06-fold) and M5HF2C-treated plants (3.61-fold), compared to the control (Fig. 8b).

Polyphenol oxidase (PPO) activity

Polyphenol oxidase (PPO) activity showed a similar pattern, with treated plants exhibiting a 5.0- to 9.43-fold increase at 72 h compared to the control. The highest activity was observed in pathogen-infected plants, followed by crude extract- and M5HF2C-treated plants. This marked rise in PPO activity suggests enhanced lignification and structural reinforcement of plant tissues, highlighting the role of phenolic metabolism in strengthening defenses against fungal infection (Fig. 8c).

Phenylalanine ammonia-lyase (PAL) activity

Phenylalanine ammonia-lyase (PAL) activity was significantly elevated in treated plants at 72 h post-infection. The highest induction was observed in pathogen-infected plants (7.11-fold), followed by crude extract-treated (5.82-fold) and M5HF2C-treated plants (4.51-fold), compared to the control. This increase indicates that fungal infection activated a strong defense response, further amplified by the treatments, leading to enhanced synthesis of phenolic compounds associated with disease resistance. The induction of PAL activity thus underscores the importance of secondary metabolites in reinforcing plant defences against pathogen attack (Fig. 8d).

Pearson’s correlation analysis

Pearson’s correlation analysis (Fig. 9) showed a strong positive relationship among chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids (r = 0.99-1.00). These pigments were highly negatively correlated with oxidative stress markers (MDA, EL%, Evans blue, superoxide anion, H₂O₂) and proline content (r = -0.85 to -0.99). In contrast, oxidative stress indices and proline showed strong positive correlations with antioxidant enzyme activities (APX, GR, GPX, PAL, PPO, POX, SOD, CAT; r = 0.91–0.99). This suggests that pigment loss was closely associated with oxidative damage, while proline accumulation and antioxidant defense were strongly linked to ROS generation.

Fig. 9.

Pearson’s correlation matrix of physiological, biochemical, and antioxidant traits in maize. Green indicates positive and brown negative correlations (r = − 1 to + 1). Pigments correlated positively with each other but negatively with stress markers and antioxidant enzymes.

Principal component analysis (PCA)

Principal component analysis (PCA) revealed clear separation of treatments and time points, explaining 98.15% of the total variance through the first two components (PC1 = 93.27%, PC2 = 4.88%). PC1 primarily distinguished stressed from non-stressed plants, with control samples clustering on the negative axis, associated with chlorophylls and carotenoids, while treated samples shifted along the positive axis due to stress-related traits. Pathogen-infected plants showed the strongest separation, with early time points (24–72 h) clustering with oxidative stress markers (H₂O₂, superoxide ions, MDA) and antioxidant enzymes (APX, GPX, GR, SOD, CAT, PAL, PPO, POX), and late stages (96–120 h) aligning with electrolyte leakage, proline accumulation, and cell death, indicating severe and irreversible damage. Crude extract–treated plants followed a similar but less pronounced trajectory, while M5HF2C-treated plants remained closer to controls at early stages and only shifted towards stress traits at 96–120 h, suggesting a delayed and milder response. Overall, the PCA highlights pathogen infection as the most potent inducer of stress, followed by crude extract, with M5HF2C exerting the weakest effect (Fig. 10).

Fig. 10.

PCA of physiological and biochemical traits in maize explained 93.27% variation by PC1, separating controls (linked with chlorophylls and carotenoids) from treated plants (aligned with stress traits). Pathogen infection caused the strongest shift, followed by crude extract, while M5HF2C showed a milder, delayed response.

Discussion

The study demonstrates that C. lunata and its metabolites exert strong pathogenic effects on maize, inducing a cascade of physiological and biochemical alterations. The severity of these effects followed the order pathogen > crude metabolite > purified toxin (M5HF2C), highlighting the synergistic role of multiple virulence factors in disease development. A similar gradient was observed in tomato challenged with Alternaria alternata and its toxins (TeA, AOH, AME), where pathogen infection produced the strongest necrosis and biochemical disruption compared to individual metabolites, confirming that full virulence requires the combined action of multiple pathogenic determinants²⁰.

The identification of C. lunata via ITS sequencing is consistent with reports that ribosomal markers reliably distinguish Curvularia species infecting cereals. The inclusion of GAPDH and TEF1α alongside ITS improved species resolution and phylogenetic reliability. The concordant multilocus data strongly support the identification of C. lunata and emphasize the robustness of this approach^21,22. Detection of the metabolite M5HF2C further supports earlier findings that C. lunata synthesizes diverse secondary metabolites, including curvularin, lunatin, and M5HF2C, which contribute to pathogenicity²³. However, our results confirm that while M5HF2C reproduces some symptoms, complete virulence requires additional metabolites and enzymes, aligning with the necrotroph strategy²⁴. This parallels the A. alternata study, where although TeA, AOH, and AME individually caused chlorosis and necrosis, only the pathogen produced extensive lesions covering ~ 75% of the leaf area²⁰.

Symptom development in maize was most severe under whole-pathogen infection, leading to necrosis, chlorosis, and progressive leaf collapse. Similar field-level symptomology of Curvularia leaf spot in maize has been reported^25,26. The milder effects of crude extracts and pure toxin indicate that the pathogen’s complexity, including the combined action of toxins, cell wall-degrading enzymes, and effectors, is critical for disease establishment²⁷. The tomato-A. alternata system echoes this observation, where pathogen inoculation led to maximum chlorophyll degradation (42–43%) and extensive necrosis compared to purified toxins²⁰.

An early and pronounced ROS burst was observed in maize, with peaks between 24 and 72 h. This is consistent with the oxidative burst being a hallmark of plant-pathogen interaction, functioning as both a defense signal and a mediator of cellular injury²⁸. Similar findings of ROS surges during C. lunata infection in maize and rice were reported by Kaur et al.²⁹ and Fu et al.³⁰. Our results align with A. alternata in tomato, where H₂O₂ accumulation peaked at 24 h (22.2-fold in pathogen-infected tissues), followed by toxin treatments (TeA, 18.2-fold; AOH, 15.9-fold; AME, 14.1-fold), confirming ROS as an early pathogenic hallmark²⁰. Although NBT staining is widely used to indicate superoxide (O₂⁻) production, it may undergo non-specific reduction. In this study, its interpretation was supported by consistent trends in antioxidant enzyme activities and other ROS markers. However, incorporating scavenger-based controls (e.g., SOD or ascorbate) would further validate specificity in future studies. Electrolyte leakage (EL%) and malondialdehyde (MDA) levels in maize increased progressively, reflecting oxidative membrane damage. Comparable increases have been documented in maize under Exserohilum turcicum infection³¹ and in wheat under necrotrophic stress³². MDA accumulation indicates lipid peroxidation of polyunsaturated fatty acids, marking oxidative deterioration of cell membranes³³. These findings closely correspond to A. alternata-tomato, where MDA levels peaked at 48 h (15.8-fold increase in pathogen-treated tissues), reflecting massive lipid peroxidation²⁰.

Photosynthetic pigments declined drastically in maize, with total chlorophyll reduced by nearly 70–80% under pathogen infection. This agrees with previous reports of pigment degradation during C. lunata infection^16,26 and in rice and sorghum under necrotrophic stress^34,35. Similarly, A. alternata reduced chlorophyll a, b, and total chlorophyll by ~ 40–43%, further highlighting the centrality of ROS-driven pigment breakdown in necrotrophic pathogenesis²⁰.

Proline accumulation was another notable response in maize, with maximum levels in pathogen-inoculated plants (~ 9.6-fold). Proline functions as an osmoprotectant, ROS scavenger, and stabilizer of proteins and membranes¹⁸. Its accumulation has been widely reported under both abiotic and biotic stress in cereals^12,36. In our study, proline plateaued beyond 96 h, suggesting saturation of its protective effect, similar to that observed in cereals under combined stress^37,38. In tomato, A. alternata infection also triggered the accumulation of osmolytes and non-enzymatic antioxidants²⁰, reinforcing the conserved stress-mitigation strategy across pathosystems. Despite a marked increase in proline, superoxide levels remained elevated, suggesting that antioxidant defenses were unable to fully mitigate the oxidative burst. This likely reflects excessive ROS production, spatial separation between ROS-generating sites and proline accumulation, and differences in their timing. The rise in SOD activity indicates that O₂⁻ is being actively converted to H₂O₂ rather than completely removed. Together, these results suggest that antioxidant mechanisms were insufficient during severe infection, leading to oxidative damage.

Antioxidant and defense enzymes (SOD, CAT, APX, POX, GR, GPX, PPO, and PAL) increased significantly during the early phase (24–72 h) in maize, reflecting induced defense against ROS. Comparable induction was reported in A. alternata-tomato: SOD (5.9-fold), CAT (23-fold), APX (13.1-fold), and GR (33.4-fold), which peaked early but declined after 48–72 h, demonstrating defense suppression by necrotrophs²⁰. In both systems, isoenzyme profiling revealed stronger expression under pathogen infection than toxin treatment, supporting the view that complete pathogen challenge elicits a broader, though transient, antioxidant response^39,40.

Pearson’s correlation showed that chlorophylls and carotenoids were tightly associated, but strongly declined with oxidative stress markers and proline, confirming that pigment loss is a hallmark of ROS injury^13,18,41. In contrast, oxidative indices were positively linked to antioxidant enzymes, reflecting an adaptive defense mechanism, as also observed in pathogen-stressed Brassica juncea and maize plants^42,43. PCA further separated stressed from non-stressed plants, with early infection stages clustering with ROS and enzymatic defenses, and later stages aligning with proline, electrolyte leakage, and cell death, indicating irreversible damage²⁹. M5HF2C-treated plants remained closer to controls, showing a delayed and weaker stress response, consistent with reports that bioactive metabolites reduce ROS injury⁴⁴.

Integrating these observations, we propose a four-phase model of maize-C. lunata interaction: (i) recognition and ROS burst, (ii) transient defense via antioxidant induction and proline accumulation, (iii) sustained oxidative stress causing membrane lipid peroxidation, pigment degradation, and leakage, and (iv) defense collapse and necrosis. A nearly identical trajectory was described in tomato-A. alternata, where early ROS and antioxidant activation gave way to membrane damage, pigment loss, and eventual defense breakdown²⁰. Together, these comparative insights confirm that while single metabolites (M5HF2C, TeA, AOH, AME) reproduce partial symptoms, full pathogenesis depends on the synergistic action of multiple virulence factors, highlighting the complex necrotrophic infection strategies of cereal and horticultural pathogens⁴⁵.

Materials and methods

Experimental setup and design

We investigated how maize plants (cv. Pratap chari makka-6) respond when challenged with Curvularia spore suspension, crude metabolites, and purified toxins over a 0–120 h period. To set up the experiment, the fungus was first isolated from infected maize leaves, identified as C. lunata based on multilocus sequence analysis of the internal transcribed spacer (ITS rDNA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and translation elongation factor 1-alpha (TEF1α) loci sequencing, and its toxic metabolites were extracted and characterized by HPLC and LC-HRMS. The plants’ responses were then monitored using a combination of approaches: histochemical staining (Evans blue for cell death, DAB for H₂O₂, NBT for O₂·⁻), microscopy (SEM/TEM) to examine cellular damage, and biochemical assays for pigments, stress markers (electrolyte leakage, MDA, proline), and defense enzymes (SOD, CAT, APX, POX, GR, GPX, PPO, PAL). Each experiment was performed in triplicate, and results were expressed as mean ± SD. Statistical analysis was carried out using two-way ANOVA with Tukey’s test (p < 0.0001), and both error bar graphs and correlation and PCA plots were created in OriginPro 2025 to visualize treatment effects and highlight overall variation among groups.

Collection of infected leaf samples and culture of fungal isolates

Infected leaf samples were collected from maize plants in the field and surface sterilized with 0.1% sodium hypochlorite (NaOCl) solution for 1–2 min. The samples were then rinsed 2–3 times with sterile distilled water (SDW). Following sterilization, the samples were placed on PDA culture medium amended with streptomycin and incubated at 28 °C under either dark or light conditions, with a 12-hour light/dark photoperiod, for 6–10 days. Single sporulated conidia were isolated and transferred onto fresh PDA medium, where they were incubated for 5–6 days to obtain a pure culture of the fungus⁴⁶.

Identification of the pathogen

The pathogen was initially identified based on its morphological characteristics, including the size, shape, and conidial structure. The identification was further validated by Sanger sequencing using universal primers ITS1 (5-TCCGTAGGTGAACCTGCGG 3) and ITS4 (5-TCCTCCGCTTATTGATATGC-3) for the ITS region, together with gene-specific primers for GAPDH: gpd1 (5-ATACACTGCCACCCAGAAGG-3) and gpd2 (5-TCGATGCGAACAGTCAAGTC-3); TEF1α: TEF1-983 F (5-GCYCCYGGHCAYCGTGAYTTYAT), and TEF1-2218R (5-CCRAACRGCRACRGTYYGTCTCAT) loci²². DNA extraction was performed using the CTAB method, as described by Doyle and Doyle⁴⁷. A 1 g sample of lyophilized mycelial mats was ground in a mortar and pestle with 10 ml of CTAB extraction buffer, then incubated at 65 °C in a water bath for 30 min. The sample was then cooled and mixed with an equal volume of chilled chloroform and isoamyl alcohol (24:1 ratio), followed by gentle mixing. RNAse was added to the supernatant, and the sample was incubated at 37 °C for 60 to 90 min. The sample was then centrifuged at 10,000 rpm for 10 min at 4 °C, with chilled absolute ethanol added. The resulting supernatant was decanted, and the sample was centrifuged again at 10,000 rpm for 10 min at 4 °C. The pellet was washed with 70% ethanol and air-dried for 4 h to remove any residual alcohol.

PCR amplification of the ITS rDNA region was performed in a 25 µL reaction mixture containing 2.5 µL of 10X reaction buffer, 1 µL of each deoxyribonucleotide triphosphate (dNTP), 1.0 µL of both the forward primer and reverse primer of all the three loci targeting the ITS-5.8 S, GAPDH and TEF1α regions, 1.5 µL of Taq DNA polymerase, 10–100 ng of DNA, and 1.5 µL of MgCl₂. The optimized thermal cycling conditions were as follows: initial denaturation at 95 °C for 3 min, followed by 40 cycles of denaturation at 95 °C for 30 s, annealing at 70 °C for 30 s, and a final extension at 72 °C for 1 min. The amplification products were confirmed by running them on a 1.5% agarose gel in 1X TBE buffer and visualizing the bands under a UV transilluminator.

Extraction of the toxic metabolites from isolated Curvularia species

Toxic metabolites were extracted from 20-day-old Curvularia cultures grown in PDB, following the methods of Andersen et al.⁴⁸ and Suthiphasilp et al.⁴⁹, with modifications. Culture filtrates were mixed with methanol, evaporated under reduced pressure, and partitioned with ethyl acetate. The ethyl acetate layer was concentrated to obtain crude metabolites, which were dissolved in methanol.

Pathogenicity test and toxicity assessment of pathogen and toxic metabolites

Pathogenicity test was performed using Koch’s postulates and performed according to the modified method described by Meena et al.²⁰.

On pot cultured plants leaves

Maize seeds were surface-sterilized with sodium hypochlorite, rinsed with tap water, and air-dried. The plants were grown in separate pots under controlled conditions, with a temperature range of 28 to 32 °C and relative humidity maintained between 40% and 60%. Optimal inoculum concentrations of 0.5 × 10⁶, 1 × 10⁶, 1.5 × 10⁶, and 2 × 10⁶ spores/mL were prepared and sprayed on the leaf area. The plants were kept in dew chambers at 25 °C for 8 h. Disease and symptom development were monitored regularly for 2 to 3 days compared with the control.

On detached plant leaves

The leaves of maize plants were detached, washed with water, and placed in a moist tray. Spore suspensions of Curvularia isolate, obtained from infected leaves, were prepared. To assess pathogenicity, the maize leaves, along with a control leaf, were arranged in a line and placed in a dew chamber at 25 °C for 8 h. An inoculum concentration of 2 × 10⁶ spores/mL was sprayed on each of the detached leaves. Crude metabolites and standard toxins were also separately sprayed on the leaves. A solvent control (methanol diluted in sterile distilled water at the same concentration used for metabolite application) was included to rule out solvent effects. The leaves were regularly monitored for symptom appearance, infection severity, and disease progression.

Characterization of crude metabolites

Characterization was performed using HPLC and LC-HRMS.

HPLC analysis

Quantification of the standard toxin methyl-5-hydroxyfuran-2-carboxylate (M5HF2C) in the extracted crude metabolite was performed by quantitative HPLC using the protocol described in the guideline, I. H. T⁵⁰. M5HF2C was analyzed using HPLC (Agilent 1220 Infinity II Gradient LC System) with a TC-C18(2) column (4.6 × 250 mm, 5 µM). The mobile phase consisted of methanol + 1% formic acid and acetonitrile + 1% formic acid (30:70, v/v), degassed for 15 min, at a flow rate of 1 mL/min. Detection was performed at 210 nm with an injection volume of 10 µL under ambient temperature. A stock solution (1 mg/mL in methanol) was serially diluted to prepare calibration standards (75–300 µg/mL). Samples were extracted from crude metabolite (50 mg) with ethanol: water (40:60, v/v), incubated overnight at 4 °C, centrifuged (14,000 × g for 5 min), diluted to 100 µg/mL, sonicated (10 min), and filtered (0.2 µM nylon) prior to injection.

LC-HRMS analysis

LC-HRMS analysis was performed using a Waters Alliance 2695 HPLC system with MassLynx 4.1 software as described in the manufacturer’s guidelines⁵¹. Chromatographic conditions were adapted from Graham, T. L., with modifications⁵². LC-HRMS was carried out on a Waters Alliance 2695 HPLC system coupled with a mass spectrometer, controlled by MassLynx 4.1 software. Separation was achieved on an ACCUCORE C18 column (150 × 4.6 mm, 2.6 µM) using a 40-min gradient with mobile phase A (5 mM ammonium acetate in 5% acetonitrile/water) and B (acetonitrile), increasing B from 5% to 80% over 32 min before re-equilibration. The flow rate was 1.0 mL/min, the injection volume was 10 µL, and the autosampler temperature was 20 °C. Mass detection was performed in positive and negative electrospray ionization (ESI) modes over m/z 100–750 in enhanced scan mode, with desolvation at 350 °C (650 L/h desolvation gas; 50 L/h cone gas). A diode-array detector (Waters 2998) recorded absorbance between 200 and 450 nm (channels at 220, 240, 280, 350, and 410 nm) at 20 points/sec.

Treatment of pathogen, crude metabolite and toxin to pot cultured maize plants

Maize seeds (Variety: Pratap Chari Makkah-6) were obtained from the Rajasthan College of Agriculture (MPUAT, Udaipur, Rajasthan). Methyl 5-(hydroxymethyl) furan-2-carboxylate (M5HF2C), a standard toxin of C. lunata, was purchased from BLD Pharmaceutical (India) Private Limited (Cat. No. BD196578). The seeds were first washed with sterile distilled water, then surface-sterilized with 0.1% sodium hypochlorite, washed with sterile distilled water 2–3 times, and left to dry. The seeds were then sown in pots for the experiment. After 7–10 days, a spore suspension (2 × 10⁶ spores/mL) of the pathogen, extracted crude metabolite (100 µg/mL), and toxin (100 µg/mL) were sprayed, and symptoms were observed daily for 4–5 days. The experiment was conducted in triplicate. The temperature was maintained between 28 °C and 32 °C, and the relative humidity ranged from 40% to 60%.

Evaluation of physiological and biochemical changes

A time-course study was conducted to evaluate physiological and biochemical changes in maize leaves by assessing the following parameters at time points ranging from 0 to 120 h of treatment.

Qualitative analysis of histochemical changes

Cell death assay by Evans blue staining

Cell death was assessed according to the protocols of Baker & Mock⁵³ and Meena et al.²⁰, with minor modifications. Maize plants were infected with the pathogen and its toxic metabolites, and leaves were collected at each time point (0–120 h). The affected tissues were boiled for 1–2 min in a freshly prepared solution of phenol: lactic acid: glycerol: distilled water (1:1:1:1) containing Evans blue (20 mg/mL). The tissues were then clarified overnight in 2.5 g/mL chloral hydrate solution, and cell death was visualized under a light microscope.

Detection of hydrogen peroxide (H₂O₂) accumulation by DAB staining

Histochemical detection of H₂O₂ was performed by 3,3′-diaminobenzidine (DAB) staining following Thordal-Christensen et al.⁵⁴. Infected maize leaves were excised at each time point (0–120 h) post-inoculation and incubated in 1 mg/mL DAB-HCl (pH 5.6) for 12 h in the dark under humid conditions. After staining, chlorophyll was removed by boiling the tissues in 96% ethanol, and reddish-brown precipitates indicating H₂O₂ accumulation were observed under a light microscope.

Detection of superoxide (O₂^·−) radicals by NBT staining

O₂⁻ accumulation was assessed by nitroblue tetrazolium (NBT) staining following Kumar et al.⁵⁵. Treated leaves were incubated in 0.2% NBT solution prepared in 50 mM potassium phosphate buffer (pH 7.5) overnight at room temperature in the dark. Chlorophyll was removed by heating the samples in absolute ethanol for 10 min, and the leaves were mounted in 70% glycerol for microscopic observation (Olympus BX51TF). Dark blue formazan deposition indicated O₂⁻ presence.

Cellular destruction and ultrastructural study by SEM and TEM analysis

Infected and control maize leaves were collected at 72 h post-treatment. Small pieces of leaves (≤ 5 mm for SEM, ≤ 1 mm³ for TEM) were fixed in 2.5% glutaraldehyde prepared in 0.1 M phosphate buffer (pH 7.2–7.4) overnight at 4 °C, then rinsed thoroughly in buffer and post-fixed in 1% osmium tetroxide. For SEM, the tissues were dehydrated through a graded ethanol series, replaced with t-butanol, freeze-dried, mounted on aluminum stubs, sputter-coated with gold, and visualized under a tabletop SEM (Thermo Scientific Apreo 2 S) at 5–15 kV. For TEM, the samples were dehydrated in ethanol or acetone, embedded in epoxy resin, sectioned into ultrathin slices (60–90 nm), stained with uranyl acetate and lead citrate, and examined under a transmission electron microscope (CRYO-TEM (TALOS S) at 60–120 kV⁵⁶.

Effect on photosynthetic machinery

Photosynthetic pigments, including chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids, were quantified in both treated and control leaf samples at different time points (0–120 h). For pigment extraction, one gram of leaf tissue was homogenized in 80% acetone, and the extract volume was made up to 100 mL⁵⁷. The method was followed with slight modifications to assess photosynthetic attributes. After filtration, absorbance was recorded at 663, 645, and 470 nm using a Shimadzu UV-1900i UV-VIS spectrophotometer. Then chlorophyll a, b, total chlorophyll and carotenoid content were calculated according to the Lichtenthaler and Wellburn formulae⁵⁸.

A = Absorbance of chlorophyll extract on specific induced wavelength; V = Final volume of extract in a mixture of 80% acetone; FW = Fresh weight of tissue (mg).

Assessment of quantification of histochemical changes, membrane damage, lipid peroxidation and proline accumulation

Treated and control maize leaf samples were collected at different time points (0–120 h) post-treatment. Quantification of Evans blue stain, hydrogen peroxide (H₂O₂), and superoxide (O₂⁻) ions was carried out, percent electrolyte leakage (EL%) was estimated to assess damage to the plant membrane system, lipid peroxidation was determined by quantifying malondialdehyde (MDA) content, and proline content, a stress marker, was also estimated spectrophotometrically.

Quantification of Evans blue stain in dead tissue

For quantification of Evans blue stain in dead tissue, stained leaves were rinsed with distilled water, incubated in 1% (w/v) SDS solution, and homogenized using a mortar and pestle. The homogenate was centrifuged at 9000 rpm for 3 min, and 0.8 mL of the supernatant was collected. Absorbance was measured at 600 nm, and the amount of stain accumulation was determined using a standard curve prepared with known concentrations of Evans blue²⁰.

Quantification of hydrogen peroxide (H₂O₂)

For quantification of H₂O₂ in the treated sample, 0.1 g of leaf tissue was homogenized in 2 mL of 0.1% (w/v) TCA on ice, and the extract was centrifuged at 12,000 g for 15 min. The supernatant (0.5 mL) was mixed with 0.5 mL of 10 mM potassium phosphate buffer (pH 7.0) and 1 mL of KI solution, incubated for 5 min, and absorbance was measured at 390 nm⁵⁹. H₂O₂ concentration was calculated from a standard curve prepared with known concentrations of H₂O₂ and expressed as nmol g⁻¹ FW.

Quantification of superoxide (O₂⁻) ions

Formazan, formed during NBT staining, was extracted from 20 mg dried leaf tissue using 2 M potassium hydroxide: chloroform (1:1, v/v) at 4 °C in the dark. Extracts were pooled, dried under nitrogen, and the residue dissolved in DMSO and 2 M potassium hydroxide. Absorbance was measured at 630 nm for formazan quantification⁶⁰.

Determination of electrolyte leakage

Leaf discs (6 mm diameter, ~ 0.1 g fresh weight) from control and treated plants were rinsed with deionized water, blotted dry, and incubated in 10 mL deionized water at 25 °C with gentle shaking for 4 h. The initial conductivity (C1) of the bathing solution was measured using a calibrated digital conductivity meter (Model 215-R). Samples were then autoclaved at 121 °C for 20 min to release total electrolytes, cooled to room temperature, and the final conductivity (C2) was recorded. Percent electrolyte leakage was calculated as (C1/C2) × 100 after subtracting blank values⁶¹.

Lipid peroxidation (LPO)

Malondialdehyde (MDA) content, an indicator of total lipid peroxidation, was determined using the thiobarbituric acid (TBA) reaction as described by Ohkawa et al.⁶². Leaf tissue (0.1 g) from each treatment was homogenized and incubated with 2.0 mL of 20% (w/v) trichloroacetic acid (TCA) containing 1% (w/v) TBA at 95 °C for 30 min. The reaction was terminated by placing the samples on ice for 10 min, followed by centrifugation at 10,000 rpm for 15 min. The absorbance of the supernatant was recorded at 532 nm, and MDA content was expressed as mol g⁻¹ fresh weight.

Proline content

Leaf tissue (0.1 g) from each treatment was homogenized in 3% sulphosalicylic acid and centrifuged at 10,000 × g for 15 min. The supernatant, glacial acetic acid, and 140 mM ninhydrin reagent (ratio 1:1:1) were mixed. The mixture was incubated in a water bath at 95 °C for 45 min, and 1 mL toluene was added to the mixture after cooling. The proline content was measured by absorbance at 520 nm. A standard curve was generated for L-proline. The proline content in rice roots was determined from absorbance and standard curve⁶³.

Assessment of activity of antioxidant and defense enzymes

Superoxide dismutase (SOD, EC 1.15.1.1) activity

Superoxide dismutase (SOD) activity was assayed following Beauchamp and Fridovich⁶⁴ by measuring its ability to inhibit the photochemical reduction of nitro blue tetrazolium (NBT). Leaf tissue (0.1 g) was homogenized in 5 mL of ice-cold extraction buffer (0.1 M phosphate buffer, pH 7.5, containing 0.5 mM EDTA), and the supernatant obtained after centrifugation at 15,000 rpm for 15 min was used as the enzyme extract. The reaction mixture (3 mL) contained 50 mM phosphate buffer (pH 7.8), 13 mM methionine, 75 µM NBT, 2 µM riboflavin, 0.1 mM EDTA, and 100 µL enzyme extract. The mixture was illuminated at 25 °C for 10 min, and absorbance was recorded at 560 nm. One unit of SOD activity was defined as the amount of enzyme required to inhibit 50% of NBT reduction.

Catalase (CAT, EC 1.11.1.6) activity

Catalase (CAT) activity was assayed following Aebi⁶⁵. Leaf tissue (0.1 g) was homogenized in 50 mM Tris-HCl buffer (pH 8.0) containing 0.5 mM EDTA, 2% (w/v) polyvinylpyrrolidone, and 0.5% (v/v) Triton X-100, and the homogenate was centrifuged at 15,000 × g for 10 min at 4 °C. The reaction mixture consisted of 1 mL enzyme extract in 300 mM phosphate buffer (pH 7.2) supplemented with 100 mM H₂O₂. CAT activity was determined by monitoring the decrease in H₂O₂ absorbance at 240 nm for 1 min and expressed as unit min^{− 1} mg^{− 1} protein.

Ascorbate peroxidase (APX, EC 1.1.11.1) activity

Ascorbate peroxidase (APX) activity was assayed following Nakano and Asada⁶⁶. The reaction mixture contained 0.2 mL enzyme extract, 25 mM phosphate buffer (pH 7.0), 0.1 mM EDTA, 0.25 mM ascorbic acid, and 1.0 mM H₂O₂. The decrease in absorbance at 290 nm was recorded for 60 s, and activity was expressed as unit min^-1 mg^-1 protein.

Peroxidase (POX, EC 1.11.1.7) activity

Peroxidase (POX) activity was determined following Assaha et al.⁶⁷. Fresh leaf tissue (0.1 g) was homogenized in 3 mL of 0.1 M phosphate buffer (pH 7.0), and the extract was centrifuged at 18,000 × g for 15 min at 4 °C. The reaction mixture contained phosphate buffer (0.1 M, pH 6.5), enzyme extract, and 0.2 mL of 0.2 M H₂O₂, and absorbance was recorded at 430 nm. POX activity was expressed as the rate of increase in absorbance per minute per milligram of protein.

Glutathione reductase (GR, EC 1.6.4.2) activity

Glutathione reductase (GR) activity was assayed as described by Anderson⁶⁸. Leaf tissue (0.1 g) was homogenized in 5 mL of 50 mM Tris-HCl buffer (pH 7.6), and the extract obtained after centrifugation at 15,000 × g for 30 min at 4 °C was used for enzyme analysis. The reaction mixture contained 50 mM Tris-HCl buffer (pH 7.6), 0.15 mM NADPH, 1 mM oxidized glutathione (GSSG), 3 mM MgCl₂, and 0.3 mL enzyme extract. GR activity was determined by monitoring the decrease in NADPH absorbance at 340 nm and expressed as unit min⁻¹ mg⁻¹ protein.

Guaiacol peroxidase (GPX, EC 1.11.1.7) activity

Guaiacol peroxidase (GPX) activity was determined by measuring the increase in absorbance at 470 nm due to tetraguaiacol formation. Fresh maize leaves (~ 0.1 g) were homogenized in ice-cold phosphate buffer (0.1 M, pH 6.5) containing 1% PVP, and the extract was centrifuged at 15,000 × g for 15 min at 4 °C. The reaction mixture contained phosphate buffer, guaiacol (20 mM), H₂O₂ (10 mM), and enzyme extract, with the reaction initiated by adding H₂O₂. Absorbance was monitored for 2–3 min and expressed as unit min⁻¹ mg⁻¹ protein⁶⁹.

Polyphenol oxidase (PPO, EC 1.14.18.1) activity

Polyphenol oxidase (PPO) activity was measured by recording the increase in absorbance at 410 nm during catechol oxidation. Leaf extracts were prepared in phosphate buffer (pH 6.5, with PVP) and used in a reaction mixture containing buffer, catechol, and enzyme extract. The change in absorbance at 410 nm was monitored for 2–3 min at 25 °C, and activity was expressed as U·min⁻¹·mg⁻¹ protein⁷⁰.

Phenylalanine ammonia-lyase (PAL, EC 4.3.1.24) activity

Phenylalanine ammonia-lyase (PAL) activity was assayed by monitoring trans-cinnamic acid formation from L-phenylalanine at 290 nm. Leaf extracts prepared in borate buffer (pH 8.8, with PVP) were incubated with substrate at 37 °C for 1 h. The increase in absorbance at 290 nm was measured, and activity was expressed as U·h⁻¹·mg⁻¹ protein^71,72.

Statistical analysis

All data were expressed as mean ± standard deviation (SD) from three independent biological replicates. Statistical differences between the control and treatments were evaluated using two-way ANOVA, followed by Tukey’s post hoc test for multiple comparisons. Significance was considered at p < 0.0001 for all biochemical and physiological parameters. The analyses included chlorophyll and carotenoid content, oxidative stress markers (O₂·⁻, H₂O₂, MDA), proline accumulation, electrolyte leakage, and the activities of antioxidant enzymes (SOD, CAT, APX, POX, GR, GPX, PPO, and PAL). Graphs with error bars representing SD were generated to visualize treatment effects over time. Pearson’s correlation analysis was conducted to determine relationships among physiological, biochemical, and antioxidant traits, and in addition, principal component analysis (PCA) was performed to assess overall variation and grouping among treatments.

All statistical analyses, visualizations, correlation, and PCA plots were carried out using OriginPro 2025. All experiments were performed in triplicate.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 ^{(206.9KB, docx)}

Supplementary Material 2 ^{(183.8KB, tif)}

Abbreviations

APX

Ascorbate peroxidase

CAT

Catalase

CLS

Curvularia leaf spot

DAB

3,3′-Diaminobenzidine

DMSO

Dimethyl sulfoxide

dNTP

Deoxyribonucleotide triphosphate

EDTA

Ethylenediaminetetraacetic acid

EL

Electrolyte leakage

FW

Fresh weight

GAPDH

Glyceraldehyde-3-phosphate dehydrogenase

GPX

Guaiacol peroxidase

GR

Glutathione reductase

H₂O₂

Hydrogen peroxide

HPLC

High performance liquid chromatography

ITS

Internal transcribed spacer

LC-HRMS

Liquid chromatography-high resolution mass spectrometry

LPO

Lipid peroxidation

M5HF2C

Methyl-5-hydroxyfuran-2-carboxylate

MDA

Malondialdehyde

NADPH

Nicotinamide adenine dinucleotide phosphate

NaOCl

Sodium hypochlorite

NBT

Nitro blue tetrazolium

O₂⁻

Superoxide

PAL

Phenylalanine ammonia-Lyase

PCA

Principal component analysis

PDA

Potato dextrose agar

POD

Peroxidases

POX

Peroxidase

PPO

Polyphenol oxidase

PVP

Polyvinylpyrrolidone

ROS

Reactive oxygen species

SD

Standard deviation

SDW

Sterile distilled water

SEM

Scanning electron microscopy

SOD

Superoxide dismutase

TBA

Thiobarbituric acid

TCA

Trichloroacetic acid

TEF1α

Translation elongation factor 1-alpha

TEM

Transmission electron microscopy

Author contributions

TM: Writing-review & editing, Writing-original draft, Validation, Methodology, Investigation, Data curation, Conceptualization. MM: Conceptualization, Writing-review & editing, Validation, Investigation, Formal analysis, Data curation, Resources, Project administration, Supervision.

Data availability

The final sequences were deposited in NCBI GenBank under accession numbers, ITS: PQ035148 or GenBank number PQ035148.1 (https://www.ncbi.nlm.nih.gov/nuccore/PQ035148.1/ or https://www.ncbi.nlm.nih.gov/nuccore/PQ035148.1?report=genbank&to=599), GAPDH: PX965981 or GenBank number PX965981.1 (https://www.ncbi.nlm.nih.gov/nuccore/PX965981 or https://www.ncbi.nlm.nih.gov/nuccore/PX965981.1?report=genbank&to=595) and TEF1α: PZ051146 or GenBank number PZ051146.1 (https://www.ncbi.nlm.nih.gov/nuccore/PZ051146 or https://www.ncbi.nlm.nih.gov/nuccore/PZ051146.1?report=genbank&to=800).

Declarations

Competing interests

The authors declare no competing interests.