Coronatine-Induced Maize Defense against Gibberella Stalk Rot by Activating Antioxidants and Phytohormone Signaling

Abstract

One of the most destructive diseases, Gibberella stalk rot (GSR), caused by Fusarium graminearum, reduces maize yields significantly. An induced resistance response is a potent and cost-effective plant defense against pathogen attack. The functional counterpart of JAs, coronatine (COR), has attracted a lot of interest recently due to its ability to control plant growth and stimulate secondary metabolism. Although several studies have focused on COR as a plant immune elicitor to improve plant resistance to pathogens, the effectiveness and underlying mechanisms of the suppressive ability against COR to F. graminearum in maize have been limited. We investigated the potential physiological and molecular mechanisms of COR in modulating maize resistance to F. graminearum. COR treatment strongly enhanced disease resistance and promoted stomatal closure with H₂O₂ accumulation, and 10 μg/mL was confirmed as the best concentration. COR treatment increased defense-related enzyme activity and decreased the malondialdehyde content with enhanced antioxidant enzyme activity. To identify candidate resistance genes and gain insight into the molecular mechanism of GSR resistance associated with COR, we integrated transcriptomic and metabolomic data to systemically explore the defense mechanisms of COR, and multiple hub genes were pinpointed using weighted gene correlation network analysis (WGCNA). We discovered 6 significant modules containing 10 candidate genes: WRKY transcription factor (LOC100279570), calcium-binding protein (LOC100382070), NBR1-like protein (LOC100275089), amino acid permease (LOC100382244), glutathione S-transferase (LOC541830), HXXXD-type acyl-transferase (LOC100191608), prolin-rich extensin-like receptor protein kinase (LOC100501564), AP2-like ethylene-responsive transcription factor (LOC100384380), basic leucine zipper (LOC100275351), and glycosyltransferase (LOC606486), which are highly correlated with the jasmonic acid-ethylene signaling pathway and antioxidants. In addition, a core set of metabolites, including alpha-linolenic acid metabolism and flavonoids biosynthesis linked to the hub genes, were identified. Taken together, our research revealed differentially expressed key genes and metabolites, as well as co-expression networks, associated with COR treatment of maize stems after F. graminearum infection. In addition, COR-treated maize had higher JA (JA-Ile and Me-JA) levels. We postulated that COR plays a positive role in maize resistance to F. graminearum by regulating antioxidant levels and the JA signaling pathway, and the flavonoid biosynthesis pathway is also involved in the resistance response against GSR.

Keywords: Gibberella stalk rot; co-expression network; coronatine; flavonoid biosynthesis; maize; metabolomics; phytohormone signaling; transcriptome.

Figure 1

Exogenous COR enhances maize disease resistance against Fusarium graminearum. (A) GSR phenotype of Zhengdan 958 sprayed with COR and CK, infected with F. graminearum. (B) Quantification of the disease length on the plant stems from A. Mock represents the treatment with the same amount of 0.1% acetone. Significant differences between treatments are denoted by the use of lowercase letters of a different case above each bar (p < 0.05). Treatments include the untreated control (CK), treatment with 1 μg/mL COR (COR1), treatment with 10 μg/mL COR (COR10), and treatment with 50 μg/mL COR (COR50). The black arrow delineates the area of disease.

Figure 2

GMS and PAS staining of diseased maize stem tissues observable by their black-brown and magenta colors, respectively. (A) GMS staining of CK-treated maize stems. (B) PAS staining of CK-treated maize stems. (C) GMS staining of COR1-treated maize stems. (D) PAS staining of COR1-treated maize stems. (E) GMS staining of COR10-treated maize stems. (F) PAS staining of COR10-treated maize stems. Treatments include the administration of CK, 1 μg/mL COR (COR1), and 10 μg/mL COR (COR10).

Figure 3

Accumulation of MDA and the activities of antioxidant enzymes. (A) MDA content. (B) SOD activity. (C) POD activity. (D) CAT activity. Significant differences between the control group and the 1 μg/mL and 10 μg/mL COR-treated groups were compared using Duncan’s multiple range test. Significant differences at p < 0.01 were marked as double (**) the control group. The data (mean ± SD) were calculated using three replicates.

Figure 4

Activities of defense enzymes. (A) PPO activity, (B) PAL activity, and (C) LOX activity. Significant differences between the control group and the COR-treated group were compared using Duncan’s multiple range test. Significant differences at p < 0.01 were marked as double (**) the control group. The data (mean ± SD) were calculated using three replicates.

Figure 5

COR positively regulates stomatal closure by inducing the accumulation of hydrogen peroxide (H₂O₂). (A) H₂O₂ content. (B) Images of H₂O₂−based fluorescence signal in guard cells of maize stem under normal conditions. (C) Images of H₂O₂−based fluorescence signal in guard cells of maize stem treated with 10 μg/mL COR. Bars, 5 μm. The data are the averages of three independent tests. Different lowercase letters above each bar represent statistically significant differences between treatments (p < 0.05). Treatments include the untreated control (CK) and treatment with 10 μg/mL COR (COR10).

Figure 6

Phytohormone concentration in maize plants. (A) JA-Ile concentration. (B) Me-JA concentration. (C) OPDA concentration. (D) SA concentration. (E) SAG concentration. (F) ACC concentration. Different lowercase letters above each bar represent statistically significant differences between treatments (p < 0.05). Treatments include the untreated control (CK) and treatment with 10 μg/mL COR (COR10).

Figure 7

Transcriptome response of maize treated with 10 μg/mL COR and Fusarium graminearum. (A) Hierarchical cluster dendrogram of differentially expressed genes; the color difference represents high (red) and low (green) expression. (B) PCA plot illustrating transcriptome data variability. (C) Number of differentially expressed genes (DEGs) that are up−and downregulated in maize stems. (D) Venn diagrams illustrating the unique and shared DEGs that were up− or downregulated.

Figure 8

KEGG analysis of DEGs identified using RNA-seq in CK vs. C10 at 24 and 72 h. The size of the black dot represents the gene count. The DEGs were chosen based on a criterion of an adjusted p value (p.adj) < 0.05, as indicated by the colored sidebar.

Figure 8

KEGG analysis of DEGs identified using RNA-seq in CK vs. C10 at 24 and 72 h. The size of the black dot represents the gene count. The DEGs were chosen based on a criterion of an adjusted p value (p.adj) < 0.05, as indicated by the colored sidebar.

Figure 9

WGCNA to identify key candidate genes involved in maize defense. (A) Cluster dendrogram and network heatmap of genes calculated using the co-expression module. (B) The hierarchical clustering of 25 modules that share co−expressed genes. Each leaflet on the tree represents a distinct gene. (C) Pearson correlations are utilized to determine module–trait relationships. The color key from green to red indicates r² values between −1 and 1. (D) Gene networks consist of six modules with substantial correlations to phenotypic attributes. The treatments include untreated control (CK) and 10 g/mL COR (C10).

Figure 9

WGCNA to identify key candidate genes involved in maize defense. (A) Cluster dendrogram and network heatmap of genes calculated using the co-expression module. (B) The hierarchical clustering of 25 modules that share co−expressed genes. Each leaflet on the tree represents a distinct gene. (C) Pearson correlations are utilized to determine module–trait relationships. The color key from green to red indicates r² values between −1 and 1. (D) Gene networks consist of six modules with substantial correlations to phenotypic attributes. The treatments include untreated control (CK) and 10 g/mL COR (C10).

Figure 9

WGCNA to identify key candidate genes involved in maize defense. (A) Cluster dendrogram and network heatmap of genes calculated using the co-expression module. (B) The hierarchical clustering of 25 modules that share co−expressed genes. Each leaflet on the tree represents a distinct gene. (C) Pearson correlations are utilized to determine module–trait relationships. The color key from green to red indicates r² values between −1 and 1. (D) Gene networks consist of six modules with substantial correlations to phenotypic attributes. The treatments include untreated control (CK) and 10 g/mL COR (C10).

Figure 9

WGCNA to identify key candidate genes involved in maize defense. (A) Cluster dendrogram and network heatmap of genes calculated using the co-expression module. (B) The hierarchical clustering of 25 modules that share co−expressed genes. Each leaflet on the tree represents a distinct gene. (C) Pearson correlations are utilized to determine module–trait relationships. The color key from green to red indicates r² values between −1 and 1. (D) Gene networks consist of six modules with substantial correlations to phenotypic attributes. The treatments include untreated control (CK) and 10 g/mL COR (C10).

Figure 9

WGCNA to identify key candidate genes involved in maize defense. (A) Cluster dendrogram and network heatmap of genes calculated using the co-expression module. (B) The hierarchical clustering of 25 modules that share co−expressed genes. Each leaflet on the tree represents a distinct gene. (C) Pearson correlations are utilized to determine module–trait relationships. The color key from green to red indicates r² values between −1 and 1. (D) Gene networks consist of six modules with substantial correlations to phenotypic attributes. The treatments include untreated control (CK) and 10 g/mL COR (C10).

Figure 10

Metabolomic analysis of maize treated with COR at different time points after infection with Fusarium graminearum. (A) PCA plot showing divergence in metabolome data among treatments, including the untreated control (CK) and treatment with 10 g/mL COR (C10). (B) Hierarchical clustering of abundantly identified metabolites. (C) Total number of upregulated and downregulated DAMs identified in CK and C10 at two time points. (D) Venn diagram depicting the unique and common DAMs shared by CK and C10. (E) The top 20 enriched KEGG terms of the DAMs detected in comparative metabolomics comparing CK and C10 at 24 and 72 h.

Figure 10

Metabolomic analysis of maize treated with COR at different time points after infection with Fusarium graminearum. (A) PCA plot showing divergence in metabolome data among treatments, including the untreated control (CK) and treatment with 10 g/mL COR (C10). (B) Hierarchical clustering of abundantly identified metabolites. (C) Total number of upregulated and downregulated DAMs identified in CK and C10 at two time points. (D) Venn diagram depicting the unique and common DAMs shared by CK and C10. (E) The top 20 enriched KEGG terms of the DAMs detected in comparative metabolomics comparing CK and C10 at 24 and 72 h.

Figure 10

Metabolomic analysis of maize treated with COR at different time points after infection with Fusarium graminearum. (A) PCA plot showing divergence in metabolome data among treatments, including the untreated control (CK) and treatment with 10 g/mL COR (C10). (B) Hierarchical clustering of abundantly identified metabolites. (C) Total number of upregulated and downregulated DAMs identified in CK and C10 at two time points. (D) Venn diagram depicting the unique and common DAMs shared by CK and C10. (E) The top 20 enriched KEGG terms of the DAMs detected in comparative metabolomics comparing CK and C10 at 24 and 72 h.