1. Introduction
Plant diseases are a constraint factor in agricultural production, such as rice blast (Magnaporthe grisea) [1], resulting in significant yield and economic losses. In controlling these diseases, fungicides have been used as a major strategy in the production. Most pesticides affect plant diseases in a direct way by inhibiting the pathogen’s growth and biology, but some chemicals may also have effects in an indirect way by inducing plant resistance to pathogen infection [2,3]. Plants have various inherent mechanisms, such as producing defense-related chemicals to protect themselves from biological stresses and potential microbial pathogens. The well-studied systemic acquired resistance (SAR) confers resistance in plants to a broad spectrum of pathogens, concomitant with an increase in chemical inducers such as salicylic acid. Salicylic acid is a constitutive defense compound in plants and a major signal molecule for inducing SAR. SAR-induced resistance in hosts shows effectively inhibitory effects against various pathogens and pests. An apparent and sufficient increase in endogenous salicylic acid inducing the production of pathogenesis-related (PRs) genes are considered as a possible signal function [4,5,6,7]. For example, salicylic acid in rice is 50 times higher than its basal level in responding plant infection and results in high resistance to plant disease [8].
Since probenazole (3-allyloxy-1,2-benzisothiazole-1,1-dioxide) induces SAR in rice, it has been widely used as a plant-defense activator against rice blast for more than 30 years [3]. Despite its extensive use, the development of probenazole resistance in target pathogens has not been observed [9]. According to our observation, probenazole does not provide a strong inhibition on conidial germination against M. grisea, nor inhibit mycelial growth. However, probenazole-treated rice or other plants was highly resistant to bacterial leaf blight [10,11]. Thus, probenazole is thought to function either as an SAR activator, like benzo (1,2,3) thiadiazole-7-carbothioic acid S-methyl ester (BTH) and 2,6-dichloroisonicotinic acid (INA), or as a priming effector that enhances defense response activation following pathogen infection [12]. Probenazole has effects in controlling bacterial blight through affecting the stomata of cabbage [13]. Probenazole and its active metabolites 1, 2-benzisothiazol-3 (2H)-one 1,1-dioxide (BIT) act as a chemical inducer of SAR by stimulating a site upstream of the point of accumulation of salicylic acid in the SAR-signaling pathway [14]. BIT and presumably probenazole activate defense responses via the SA/NPR1 signaling pathway in Arabidopsis, tobacco, cucumber and rice [2,5,6,7,8,14]. Probenazole induces Arabidopsis thaliana resistance by activating SA-signaling coupled with a consistent increase in callose deposition, which is determined by examining SA-marker genes PR1 and PR2 and suppressing JA/ET-signaling determined by examining JA-marker genes VSP2, LOX2 and PDF1.2 [15]. However, the mechanism of the interaction between rice and probenazole remains unclear.
Metabolomics has been used to determine the relationship between signal transduction, primary metabolites and secondary metabolites in pathogen and host plant interaction [16]. In responding to pathogen infection, defense-related substances in the signaling pathway of plant cells change, such as salicylic acid and ethylene; some key substances also change, such as nitric oxides, ethylene, methyljasmonic acid or methylsalicylic acid to regulate the pathway of SAR, coupled with the change of plant structure and secondary metabolites [5,6,7,8,13]. All these changes contribute to the adjustment on physiology or morphology in hosts corresponding the invasion of pathogens.
The interaction between plant and pathogen can be examined through the change of metabolites. Similarly, the effect of plant defense inducer can be determined by analyzing metabolic pathways. The results will provide reference for understanding the mechanism, interpreting the interaction and searching for potential disease- and defense-related proteins. In our previous study, the non-inhibition of probenazole was tested on M. grisea in vitro. Thus, the objectives of this study were to examine the effect of probenazole on rice plants in defending M. grisea, profile the metabolome and determine compounds as well as the metabolic pathway related to induced resistance in rice under probenazole treatment.
2. Results
2.1. Effect of Probenazole on the Metabolome of Rice Seedlings
Through M. grisea-inoculation coupled with probenazole treatment, the disease index of the control group is 51.29 ± 5.02, and treated groups are 48.4 ± 1.38, 36.59 ± 2.9, and 31.09 ± 6.78, respectively (Figure 1), which has been previously published [17]. The metabolome of M. grisea-inoculated rice seedlings with or without probenazole treatments was analyzed on GC-MS (Figure 2). After deconvolution, about 300 peaks were obtained. The metabolome was analyzed using PCA. On the score plot (Figure 3), the probenazole-treated group was distinctively separated from the non-treated group, indicating that probenazole significantly affected the metabolic profile of rice seedlings. This effect was proportionally leveraged with the increase in probenazole concentration. Furthermore, the distance between different biological samples within the same sample was relatively small, while the distance between non-treated and probenazole-treated sampleswas relatively large.
2.2. Effect of Probenazole on Differential Metabolites of Rice Seedlings
Metabolites of rice seedlings were detected by GC-MS and compared between probenazole-treated and non-treated samples. A total of 54 metabolites showed obvious change in the three probenazole-treated groups compared with the non-treated group, which were considered closely related to probenazole-induced rice resistance to pathogen infection. Differential metabolites were analyzed against the Fiehn library and NIST library (Supplementary Table S1). All compounds were identified, and the determination was made according to the retention time of the Fiehn spectrum library. All the 54 different metabolites obtained included organic acids, sugars, amino acids, organic alcohols, glycosides, sterols and other categories. In probenazole-treated rice seedlings, 42 metabolites were all up-regulated in rice seedlings treated at three rates. The up-regulated metabolites included salicylic acid, phosphonic acid, aspartate, malate, alanine, fructose, γ-aminobutyric acid, glycine and other important metabolites. Meanwhile, seven metabolites were constantly down-regulated, including terephthalic acid, valine and proline (Supplementary Table S1). The rest of the five metabolites had no constant change directions under different rates of chemical treatment. Of the metabolisms involved in the salicylic acid pathway, shikimic acid was up-regulated but phenylalanine was down-regulated, whereas its downstream metabolite salicylic acid showed up-regulation under the probenazole treatment.
2.3. Effect of Probenazole on Metabolic Pathways of Rice Seedlings
The metabolic pathways in rice seedling were analyzed using the platform at Metabo Analyst (
3. Discussion
The fungicide probenazole was effective in the control of rice blast, but the effect is not via a direct inhibition of pathogen growth. Instead, it affects disease development in an indirect way by inducing plant resistance [14]. We partially confirmed this in our previous work [17]. We have further elucidated the mechanisms of inducing plant resistance in this study, based on the analysis of metabolic profile of rice seedlings. We have found that salicylic acid and serotonin were up-regulated under probenazole treatment. We speculate that salicylic acid induced the expression of pathogenesis-related genes and enhanced the ability of plants in resisting pathogens, and higher content of salicylic acid indicated a higher level of induced resistance in plant.
Salicylic acid participates in the regulation of various physiological and biochemical processes in plants, such as plant flowering, heat production, seed germination, stomata closure, membrane permeability and ion absorption, shown in a previous study [19]. More importantly, it activates the programmed cell death of plants, resulting in necrotic spots at the infection site to prevent further invasion by pathogens [20]. Serotonin participates in various defense reactions of hosts, including programmed cell death, free radical scavenging, and the production of antibacterial metabolites [21]. All these evidences indicated that probenazole induced blast resistance in rice.
Shikimate and phenylalanine are initial precursors in the phenylpropanoid pathway, which is related to plant defense, and strengthens plant cell walls to prevent the colonization of pathogens [22,23]. Since the accumulation of shikimate was up-regulated but phenylalanine was down-regulated, whereas their downstream metabolite salicylic acid showed an up-regulation, it is speculated that probenazole might initiate the transformation of the chemical process. This result was in agreement with other reports that the accumulation of salicylic acid is stimulated by probenazole treatment [9,14]. The overexpression of phenylalanine ammonia-lyase, a key enzyme for salicylic acid synthesis [24], in the probenazole treatment is considered to contribute to wheat resistance to pathogens [25,26]. Besides, whether the other enzymes in the salicylic acid biosynthesis pathway have been strengthened still need to be proven in future research.
Defense responses via jasmonic acid can be activated in response to the infection of necrotrophic pathogens in host plants through wound signaling molecules [27,28]. It participates in abiotic stress responses including drought stress as well [29,30]. Stearate and palmitate increased in probenazole-treated rice seedlings, both of which were precursors of jasmonic acid. Meanwhile, octadecanoid intermediates might participate in a lipid-based signaling system related to jasmonic acid that activates proteinase inhibitor synthesis in response to pathogen attack [31] and this compound was distinctly increased in probenazole-treated rice seedlings.
Pathogen infection affects energy consumption and the production of carbon sources [32]. Sucrose, glucose and fructose are crucial carbon elements in plant photosynthesis. These compounds make syntheses of storage reservoirs used for plant development [33]. We have previously observed a significant increase in sucrose content in pathogen-inoculated leaves of strawberry [34]. Invertase activity increases in response to the infection of powdery mildew in barley, resulting in the accumulation of sucrose and decreased photosynthetic activities [35]. These compounds all increased in probenazole-treated rice seedlings compared to the non-treated group, indicating that probenazole helped plants in resistance against the pathogen.
The glycolysis pathway and tricarboxylic acid (TCA) cycle are involved in mediating respiration homeostasis by generating energy and carbon skeletons that are necessary for biosynthesis, cellular maintenance, and active transport in plants, as well as its relationship with mitochondrial electron transport chain flexibility [36,37]. We observed that glucose, fructose, D-glucose-6-phosphate, fructose-1,6-diphosphate, malate and succinate were all significantly increased in probenazole-treated rice seedlings, suggesting that probenazole could enhance important metabolic pathways in plants.
Cell wall-associated plant defense is an important basal resistance [38]. The components of cell walls are cross-linked by both ionic and covalent bonds into a network that strengthens plant resistance. This development involves the conjugate of xylose, fucose, arabinose, galacturonic and gluconate [39]. The rapidity of the cross-linking of abundant cell-wall-structural proteins makes a rapid defense mechanism to toughen the cell wall as a barrier to pathogen ingress prior to the deployment of transcription-dependent defenses [29]. Therefore, cell walls with highly deposited callose possess resistance to pathogen penetration [40]. SA promotes the increase in lignin to synthesize deposition on the cell wall through the shikimic acid pathway. This lignification enhances the mechanical strength and reduces the degradation of the cell wall by extracellular enzymes from pathogens. The sensitivity and lignification of plants to hyphae or toxins released from pathogens prevent further penetration and infection of pathogens [32]. In our study, we found that compounds involved in the pathway of defense-related cell wall structures including gluconate and galacturonic were all up-regulated in rice seedlings. One possible reason was that most of the above compounds were over synthesized and prepared for cell wall construction in host plants.
Ethylene plays important roles in stress responses [41,42,43,44], growth and development [45] and senescence [46]. Enhanced ethylene production is an early and active response of plants to the perception of pathogen attack and is associated with the induction of defense reactions [47]. Ethylene is suggested to act as a signal involved in SAR [48,49]. The ripening process of climacteric fruit is accompanied by a peak in ethylene production and thus results in a dramatic decrease in fruit hardness [50]. Salicylic acid can inhibit ethylene formation from 1-aminocyclopropane-1-carboxylic acid (ACC) [51]. In this study, ethylene and its precursors were not detected, while the metabolites malonic acid, asparagine, homoserine, aspartate and alanine decreased, compared with threonine, which decreased in the ethylene pathway in rice seedlings. We interpreted that the up-regulation of salicylic acid inhibited ethylene production and therefore sustained plant resistance [51].
Under environmental stresses, γ-aminobutyrate rapidly accumulates and involves itself in the expression of genes for plant signal transduction, transcriptional control, hormone biosynthesis and reactive oxygen species generation and polyamine metabolism, resulting in chemical responses through mitigating stress and enhanced plant resistance [52,53,54,55]. We have shown that the up-regulated glutamine and γ-aminobutyrate were associated with blast resistance in probenazole-treated rice seedlings. Therefore, γ-aminobutyrate is an important metabolite for disease resistance.
4. Materials and Methods
4.1. Chemical, Plant and Fungal Strain
Probenazole (a.i. 96.8%) was provided by Jiangsu Heyi Chemical Co., Ltd. (Jiangsu, China). Methanol (HPLC grade) was purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). Pyridine, methoxyamine hydrochloride, N, O-bis(trimethylsilyl)trifluoroacetamide (BSTFA) (containing 1% trimethylchlorosilane, TMS) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The above reagents are all analytical grades. Ultrapure water was obtained from a Milli-Q system (Millipore, Billerica, MA, USA).
Rice seedlings were grown in 0.15 m2 plots in a greenhouse from 25 September to 10 October 2018. At 15 days after emergence, the plants were treated with probenazole in granular formulation (a.i. 16%) at different rates, including A: 0, B: 75.00 g·m−2, C: 112.50 g·m−2, and D: 150.00 g·m−2 (Table 2). The choice of high and low concentrations is within the recommended dose (
4.2. Pretreatment
The sample of rice seedlings was processed following the procedure of metabolome analysis according to Dai et al. [56]. Briefly, the sample was pre-chilled with liquid nitrogen and ground in a ball mill (MM400, Verder Shanghai Instruments and Equipment Co., Ltd., Shanghai, China) at 30 Hz for 1 min. For each treatment, five samples were collected as replicates, 100 ± 1 mg sample was weighed and dissolved in 1.8 mL of extraction solvent (methanol/water, v/v = 8/2) with 10 μg∙mL−1 ribitol as internal standard with 5 replications (in 5 tubes). The sample was treated with 100 Hz ultrasonic for 20 min, followed by centrifugation at 13,800× g for 15 min. Immediately, 0.4 mL of supernatant was pipetted and desiccated at 45 °C in a vacuum concentrator and stored at −20 °C until use. Derivatization was performed in two steps. (1) An aliquot of 100-μL methoxyamine hydrochloride solution at 20 mg∙mL−1 was added to the sample and incubated at 30 °C for 2 h. (2) The sample was added with 100 μL containing BSTFA (1% TMS) and incubated on a dry bath block at 37 °C for 6 h. After centrifugation, 120 μL of liquid supernatant was transferred into a sample vial sealed with a rubber cap, and metabolome detection was performed within 48 h.
4.3. Gas Chromatography and Mass Spectrometry (GC-MS) Analysis
Rice metabolites were separated and detected using an HP-5MS capillary column (30 m × 0.25 mm × 0.25 μm) coupled with the 7890A-5975C GC-MS system (Agilent, CA, USA). Helium was used as carrier gas with a 1.1 mL∙min−1 flow rate. Each injection volume was 1 μL. A GC oven was heated to 60 °C for 1 min, raised to 325 °C at 10 °C/min for 2 min. The auxiliary heater was 290 °C. The ion source (EI) temperature was set to 250 °C. Electron impact ionization (70 eV) was set in a full scan mode (m/z 50 to 600) to 0.2 s/scan.
4.4. Data Analysis
MassHunter Qualitative Analysis B.07.00 (Agilent Technologies, Santa Clara, CA, USA) was used for data processing and deconvolution with the parameter of 30000 absolute peak height, and NIST14 and Fiehn mass spectrometry databases were used as references for qualitative analysis. Agilent MassHunter Mass Profiler Professional 13.1.1 was used for principal component analysis (PCA), cluster analysis and variance analysis. Metabo Analyst online (
5. Conclusions
Probenazole application induced rice resistance to rice blast, which was confirmed by significant metabolic changes, including up-related salicylic acid, γ-aminobutyrate and shikimate while there was down-regulated phenylalanine, valine and proline. These might be related to the strengthened enzymes, such as phenylalanine ammonia-lyase in the salicylic acid pathway. As such, plant protection in the phenylpropanoid pathway effectively enhanced the defense ability of rice. This work will enrich the understanding on the mode of action of probenazole in a salicylic acid-mediated plant immune system.
Supplementary Materials
The following are available online at
Author Contributions
Investigation and writing—original draft preparation, Z.W. and G.W.; methodology, B.Z.; formal analysis, T.D. and X.C.; writing—review and editing, J.H.; supervision, X.L. (Xili Liu); project administration, A.G. and X.L. (Xiaolin Li); funding acquisition, P.L. All authors have read and agreed to the published version of the manuscript.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by National Key R&D Program of China (2017YFD0201602, Yunnan Main Grain Crop Seed Industry Innovation Platform and Large-scale Green Production System Construction, and Study and Demonstration of Rice Varieties Breeding and Seed Quality Control Technology (2018ZG008).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data presented in this study are available in insert article and Supplementary Materials here.
Conflicts of Interest
The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
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Figures and Tables
Enlarge this image.Figure 1. Rice seedlings either untreated (A) or treated with probenazole at 75.00 g·m−2 (B), 112.50 g·m−2 (C), and 150.00 g·m−2 (D), followed by inoculation with Magnaporthe grisea five days after the treatment.
Enlarge this image.Figure 2. Total ion current diagram of gas chromatography–mass spectrometry on metabolites of rice seedlings either non-treated or treated with probenazole followed by inoculation with Magnaporthe grisea five days after the treatment.
Enlarge this image.Figure 2. Total ion current diagram of gas chromatography–mass spectrometry on metabolites of rice seedlings either non-treated or treated with probenazole followed by inoculation with Magnaporthe grisea five days after the treatment.
Enlarge this image.Figure 3. Principle component analysis (PCA) scores of metabolomes in rice seedlings inoculated with Magnaporthe grisea without chemical treatment (A group, ■) or treated with probenazole at 75.00 g·m−2 (B group, ■), 112.50 g·m−2 (C group, ■), and 150.00 g·m−2 (D group, ■).
Enlarge this image.Figure 4. Differential metabolic pathways in rice seedlings related to plant resistance against pathogens. Color panels display fold changes of differential metabolites in rice seedlings treated with probenazole at 75 g·m−2 (B group), 112.5 g·m−2 (C group), and 150 g·m−2 (D group) compared to non-treated group (A group), respectively. Metabolites in bold font mean a significant (p < 0.05) differential compared to non-treated group, and metabolites in grey mean non-significant differential.
Differential metabolite of rice seedlings treated with probenazole, showing pathways containing more than two compounds.
| Pathway | Match Status a | P b | Holm P c | Impact d |
|---|---|---|---|---|
| Ascorbate and aldarate metabolism | 1/4 | 0.016 | 0.196 | 0.500 |
| Phenylalanine, tyrosine and tryptophan biosynthesis | 1/4 | 0.097 | 0.582 | 0.500 |
| Alanine, aspartate and glutamate metabolism | 3/14 | 0.000 | 0.002 | 0.424 |
| Phenylalanine metabolism | 1/10 | 0.226 | 0.945 | 0.357 |
| Glycine, serine and threonine metabolism | 1/11 | 0.048 | 0.443 | 0.270 |
| Arginine biosynthesis | 3/14 | 0.004 | 0.093 | 0.228 |
| Glyoxylate and dicarboxylate metabolism | 1/8 | 0.007 | 0.125 | 0.185 |
| Inositol phosphate metabolism | 1/15 | 0.173 | 0.807 | 0.129 |
| Pentose and glucuronate interconversions | 1/18 | 0.370 | 1.000 | 0.125 |
| Starch and sucrose metabolism | 1/9 | 0.073 | 0.559 | 0.123 |
| Tryptophan metabolism | 1/41 | 0.653 | 1.000 | 0.105 |
| Arginine and proline metabolism | 1/19 | 0.248 | 0.945 | 0.102 |
| Glycerolipid metabolism | 1/16 | 0.336 | 1.000 | 0.093 |
| Galactose metabolism | 1/9 | 0.028 | 0.298 | 0.092 |
| Glutathione metabolism | 1/28 | 0.513 | 1.000 | 0.089 |
| Citrate cycle (TCA cycle) | 1/10 | 0.088 | 0.570 | 0.077 |
| Glycolysis / Gluconeogenesis | 1/13 | 0.137 | 0.702 | 0.072 |
| Fructose and mannose metabolism | 1/20 | 0.401 | 1.000 | 0.051 |
| Pentose phosphate pathway | 3/22 | 0.016 | 0.196 | 0.047 |
| Phosphatidylinositol signaling system | 1/28 | 0.513 | 1.000 | 0.037 |
| Butanoate metabolism | 2/15 | 0.053 | 0.443 | 0.032 |
| Pyruvate metabolism | 1/22 | 0.431 | 1.000 | 0.031 |
| Fatty acid biosynthesis | 1/47 | 0.704 | 1.000 | 0.015 |
| Glycerophospholipid metabolism | 1/36 | 0.605 | 1.000 | 0.013 |
| Primary bile acid biosynthesis | 1/46 | 0.696 | 1.000 | 0.008 |
| Tyrosine metabolism | 1/42 | 0.662 | 1.000 | 0.007 |
| Amino sugar and nucleotide sugar metabolism | 2/37 | 0.238 | 0.945 | 0.000 |
| Aminoacyl-tRNA biosynthesis | 5/24 | 0.000 | 0.000 | 0.000 |
| beta-Alanine metabolism | 1/21 | 0.416 | 1.000 | 0.000 |
| Biosynthesis of unsaturated fatty acids | 1/18 | 0.229 | 0.945 | 0.000 |
| D-Glutamine and D-glutamate metabolism | 1/6 | 0.142 | 0.702 | 0.000 |
| Fatty acid degradation | 1/39 | 0.634 | 1.000 | 0.000 |
| Fatty acid elongation | 1/39 | 0.634 | 1.000 | 0.000 |
| Histidine metabolism | 1/16 | 0.336 | 1.000 | 0.000 |
| Lysine degradation | 1/25 | 0.474 | 1.000 | 0.000 |
| Nicotinate and nicotinamide metabolism | 1/15 | 0.319 | 1.000 | 0.000 |
| Nitrogen metabolism | 1/6 | 0.142 | 0.702 | 0.000 |
| Pantothenate and CoA biosynthesis | 2/19 | 0.081 | 0.564 | 0.000 |
| Porphyrin and chlorophyll metabolism | 1/30 | 0.538 | 1.000 | 0.000 |
| Propanoate metabolism | 1/23 | 0.446 | 1.000 | 0.000 |
| Purine metabolism | 1/65 | 0.816 | 1.000 | 0.000 |
| Pyrimidine metabolism | 1/39 | 0.634 | 1.000 | 0.000 |
| Selenocompound metabolism | 1/20 | 0.401 | 1.000 | 0.000 |
| Valine, leucine and isoleucine biosynthesis | 3/8 | 0.001 | 0.021 | 0.000 |
| Valine, leucine and isoleucine degradation | 1/20 | 0.267 | 0.973 | 0.000 |
a Match status is the number of matching metabolites over the total number of metabolites. b P: probability of enrichment analysis; c Holm P is probability adjusted by Holm Bonferroni method; d impact is the path topology value path influence.
Table 2Grouping of probenazole-treated rice seedlings inoculated with Magnaporthe grisea.
| Pesticide | Dispose Group | Gram/m2 |
|---|---|---|
| None | A | 0 |
| 16% probenazole granules | B | 75.00 |
| 16% probenazole granules | C | 112.50 |
| 16% probenazole granules | D | 150.00 |
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; Liu, Xili 1 1 College of Plant Protection, China Agricultural University, Beijing 100193, China;
2 Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China;
3 School of Food and Agriculture, University of Maine, Orono, ME 04469, USA;