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Article

Baseline Sensitivity to and Succinate Dehydrogenase Activity and Molecular Docking of Fluxapyroxad and SYP-32497 in Rice Sheath Blight (Rhizoctonia solani AG1-IA) in China

by
Ping Zhao
1,2,
Yunyan Deng
1,
Tao Wang
3,
Zhiqiu Qi
1,
Ying Du
1,
Liru Liu
1 and
Mingshan Ji
1,*
1
College of Plant Protection, Shenyang Agricultural University, Shenyang 110866, China
2
State Key Laboratory of the Discovery and Development of Novel Pesticide, Shenyang Sinochem Agrochemicals R & D Co., Ltd., Shenyang 110021, China
3
Liaoning Province Lvyuan Nongfeng Agricultural Technology Service Co., Ltd., Shenyang 110100, China
*
Author to whom correspondence should be addressed.
Agronomy 2022, 12(12), 3075; https://doi.org/10.3390/agronomy12123075
Submission received: 3 November 2022 / Revised: 24 November 2022 / Accepted: 3 December 2022 / Published: 5 December 2022
(This article belongs to the Section Pest and Disease Management)
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Abstract

:
Rice sheath blight caused by Rhizoctonia solani occurs worldwide and is mainly controlled by fungicides. SYP-32497 is a novel succinate dehydrogenase inhibitor, which interferes with the succinate ubiquinone reductase in the mitochondrial respiratory chain of fungi. This study aimed to evaluate the baseline sensitivity of R. solani from 13 major rice producing areas in China to SYP-32497 and fluxapyroxad. The study also explored the cause for the activity discrepancy between SYP-32497 and fluxapyroxad via an enzyme activity inhibition test and molecular docking. A total of 360 R. solani isolates were sensitive to SYP-32497 and fluxapyroxad. Baseline sensitivities were unimodally distributed with mean values of 0.00667 ± 0.00475 and 0.0657 ± 0.0250 μg mL−1, respectively, for SYP-32497 and fluxapyroxad. Enzyme activity assays and molecular docking results revealed that SYP-32497 exhibited a much higher SDH inhibition (IC50 = 0.300 μg mL−1) than to fluxapyroxad (IC50 = 1.266 μg mL−1) because of its excellent SDH binding ability via hydrogen bonding, π-cation, and hydrophobic interactions. These results suggest that SYP-32497 is a good suitable control agent for alternative rice sheath blight.

Graphical Abstract

1. Introduction

Rice (Oryza sativa L.) is considered to be a globally important and highly nutritious crop [1]. Rice plays a central role in China’s granulated production, and more than 65% of residents utilize rice as their main food source. Rice sheath blight is one of the three most devastating diseases impacting rice production and cost-effectiveness, and it acutely reduces rice manufacturing outputs [2]. Rhizoctonia solani Kuhn (sexual stage: Thanetophorus cucumeris (Frank) Donk) is a rice sheath blight pathogen and can be categorized into 14 anastomosis groups (AGs) based on hyphal fusion patterns (anastomosis) [3]. Disparate R. solani AGs infect numerous crops (up to 27 plant families) and induce crucial diseases, such as causing root, crown, hypocotyl, pod and belly rot, sheath and leaf blight, banded leaf, brown patch, and canker [4,5,6]. The primary rice sheath blight AGs are AG1-IA, AG-4, and AG-Bb; more than 90% of rice sheath blight pathogens belong to AG1-IA [7,8]. R. solani infects rice under high temperatures and humidity, causing sheath lesions and increasing rice plant lodging susceptibility [9], affecting grain filling and yield, and accounting for up to 50% yield loss [10].
Although efforts have been made to breed resistant rice cultivars, the disease remains a major problem in crop productivity because of limited genetic disease resistance. To date, chemical controls using fungicides remains the mainstay measure for controlling rice sheath blight [11]. Succinate dehydrogenase (SDH), also known as mitochondrial Complex II, is a mitochondrial enzyme with unique properties that participates in both the citric acid cycle and the electron transport chain [12,13]. As a pivotal respiratory enzyme, SDH comprises four subunits: SDHA, SDHB, SDHC, and SDHD [14]. SDH is widely and abundantly found in fungi, and is therefore considered an important target enzyme for fungicides [15]. Succinate dehydrogenase inhibitor (SDHIs) fungicides, including boscalid, carboxin, flutolanil, thifluzamide, and fluxapyroxad are widely used to control basidiomycetes, ascomycetes, and imperfect fungi [16,17,18]. Many new and active SDHIs compounds have been discovered in recent years, and their known structural diversities have thus increased. SYP-32497, also known as 3-(difluoromethyl)-1-methyl-N-[2-methyl-3-(1-methylbutoxy)phenyl]-1H-pyrazole-4-formamide (Shenyang Sinochem Agrochemicals R & D Co., Ltd.), has high fungicidal activity and was developed in 2014 by modifying mepronil and bixafen [19]. It is also similar to the structure of fluxapyroxad (Figure 1).
SYP-32497 has a mode of action (MoA) similar to mepronil and bixafen, and acts as a respiratory inhibitor that successfully destroys succinate dehydrogenase activity in rice sheath blight, maize rust, and wheat powdery mildew. In China, thifluzamide and fluxapyroxad are registered to control rice sheath blight. To our knowledge, only the baseline sensitivity of R. solani to thifluzamide and fluxapyroxad has been established in the An hui Province, China [20,21], However, the sensitivity to fluxapyroxad and SYP-32497 has not been evaluated in various regions of China. A baseline sensitivity analysis monitors sensitivity shifts and resistance management, and forms an important part of the pesticide registration process. The objectives of this study were to (a) establish the baseline sensitivity of R. solani isolates towards fluxapyroxad and SYP-32497 in China, (b) determine how the fungicides affect succinate dehydrogenase activity in R. solani, and (c) to analyze the relationship between fluxapyroxad, SYP-32497, and protein binding properties by molecular docking.

2. Materials and Methods

2.1. Fungal Strains

During 2020–2021, 360 plants with rice sheath blight symptoms were collected from Jiangsu, Henan, Jilin, Hunan, Jiangxi, Anhui, Sichuan, Inner Mongolia, Zhejiang, Heilongjiang, Liaoning, Hubei, and Tianjin (Table 1), where no SDHIs have been used. Using the tissue separation method, a piece of tissue, 5 mm in size, was excised between diseased and healthy plant sections, then sterilized with 75% alcohol, and washed with sterile water. Hereafter, tissues were cultured in PDA (200 g potato, 20 g glucose, 15 g agar powder, 1 L water modified with streptomycin) for 2 days at 28 °C. This moment, mycelium were relatively sparse, so single hyphae were then purified and maintained on PDA slants at 4 °C for 2–4 weeks. The DNA of the test strains were extracted using OMEGA fungal DNA extraction kit (D3390-01, OMEGA, La Chaux-de-Fonds, Switzerland). Some strains were amplified by primers ITS1/ITS4, and the sequence obtained was 99.56% similar to AG1-IA strain registration number MG397054.1. Then, the sequences of all strains were amplified by specific primers (RHIP: 5′-CTCAACAGGCATGCTCCTC-3′; AG1IAP: 5′-CAGCAATAGTTGGGGA-3′) according to the literature [22]. The bands of all strains were 235 bp, which was consistent with the reports in the literature (Figure 2). Therefore, all the strains confirmed to be AG1-IA using anastomosis group (AG).

2.2. Fungicides

SYP-32497 (99%) and fluxapyroxad (98%) were sponsored by the Shenyang Research Institute of Chemical Industry. On an ultra-clean bench, 0.1010 g SYP-32497 and 0.1020 g fluxapyroxad were dissolved, respectively, in 10 mL DMSO stock solutions with effective concentrations of 10,000 μg mL−1 and then stored at 4 °C until required.

2.3. Sensitivity of R. solani to SYP-32497 and Fluxapyroxad

Autoclaved PDA was amended with either SYP-32497 or fluxapyroxad to obtain final concentrations of 0, 0.00078, 0.003125, 0.0125, 0.05, 0.2, and 0.8 μg mL−1. The concentration of DMSO in the medium was adjusted to 0.1% in volume. An inverted mycelial plug (5 mm in diameter) was excised from the edge of a 2-day-old colony and transferred to a 9 cm Petri dish containing the amended media; three replicates were made for each concentration. Colony diameters were measured after culturing at 28 °C for 1.5 days. The 50% effective concentration (EC50) was calculated by correlating mycelial growth inhibition rates against log-transformed fungicide concentrations. Experiments were conducted in duplicate. The mycelial growth inhibition (%) = (C − T)/C × 100, where C and T represent mycelial growth diameter (mm) in control and treatment groups, respectively.

2.4. Determination of Enzyme Efficiency

SDH catalyzes the reaction of succinate dehydrogenation to form fumaric acid. Hydrogen is transferred to reduce 2,6-dichlorophenol-indophenol (DPIP) by 5-N-methyl phenazonium sulfate (PMS). This reaction has a characteristic absorption peak at 600 nm and can be analyzed using a UV-visible spectrophotometer (Mettler Toledo, Columbus, OH, USA). The 2.6-DPIP reduction rate is determined via changes in the 600 nm absorbance peak, which represents SDH enzyme activity [23]. SDH enzyme activities were determined with YZ1 (isolated from Yizhou, Hunan Province) isolates of R. solani according to previous reports, with minor modifications [24,25]. An SDH Assay kit (Beijing Solarbio Technology Co., Ltd., Beijing, China) was used according to manufacturer instructions, whereby mycelial plugs (5 mm in diameter) were inoculated in 40 mL PDB medium at 28 °C and 120 r/min for 2 days, after which different concentrations of SYP-32497 or fluxapyroxad (0, 0.08, 0.4, 2, 10, 50 μg mL−1) were added. The concentration of DMSO in the medium was adjusted to 0.1% in volume. After 12 h, the mycelia were washed, dried, and weighed (0.1 g) into a mortar, after which, 1 mL reagent 1 and 10 μL reagent 2 were added. The mycelia were then ground on ice until they were completely dissolved, and the extract was transferred to 1.5 mL centrifuge tubes, followed by centrifugation at 4 °C at a speed of 11,000× g for 10 min to obtain the supernatant. The UV-visible spectrophotometer was used to quantify the obtained supernatant at a wavelength of 600 nm. Briefly, 168 μL reagent 3, 12 μL reagent 5, 10 μL of the sample, and 10 μL reagent 6 were added to the determination tube. For the blank treatment, 10 μL of distilled water was added instead of the sample. The initial absorbance (A1) at 20 s and the second absorbance (A2) at 1 min 20 s were recorded at 600 nm wavelength, and the change in absorbance was calculated as; ΔA = A1 − A2. The ΔA determination and ΔA blank were obtained and used to calculate the SDH activity as follows;
SDH activity (U/G mass) = [(ΔA determination − ΔA blank)/(ε × d) × V anti-total × 109]/(V sample/V total × W)/T = 1603.175 × (ΔA determination − ΔA blank)/W.
V anti-total: the total volume of the reaction system; ε: 2,6-dichlorophenol-indophenol extinction coefficient, 2.1 × 104 L/mol/cm; d: cupola light diameter, 1 cm; V sample: the added sample volume (0.01 mL); V total: the added reagent 1 and reagent 2 volume (1.01 mL); T: Reaction time (1 min); W: Sample quality.
Each sample was analyzed in triplicate, and mean values were used to estimate IC50 values. The IC50 was calculated by correlating the inhibition rates of SDH activity against the log-transformed fungicide concentrations. SDH activity inhibition (%) = (C − T)/C × 100, where C and T represent SDH activity in the control and treatment groups, respectively.

2.5. Molecular Docking

Molecular docking was performed by SYBYL-X 2.0 software (Trepos, Fort White, FL, USA) according to the literature [26]. The molecular structures of all compounds were created using ChemBioDraw Ultra 14.0 (Global Collaboration and Analytics Platforms for Chemistry, Biology, and Clinical Research, Waltham, MA, USA) and optimized to minimize their energies using the Powell method. SDH crystal structures from Gallus gallus in complex with carboxin (PDB ID: 2FBW) were used as molecular docking templates. The ligand carboxin (P/CBE 202), in the SDH ubiquinone-binding (Qp) site, was extracted and all water molecules were removed from this crystal complex. The low energy conformation of each compound was selected as the initial docking conformation. Surflex-Dock was applied for simulating and evaluating interactions between these compounds and the target protein using an empirical scoring function. Additionally, docking results were also visualized using the Pymol software 2.5.4.

2.6. Data Processing and Statistical Analysis

The data generated in this study were analyzed by SPSS v.18.0 (IBM). The EC50 and IC50 values of R. solani were calculated by regressing the percentage of growth inhibition against logarithmic fungicide concentrations.

3. Results

3.1. Baseline Sensitivity of R. solani to SYP-32497 and Fluxapyroxad

A total of 360 R. solani isolates were obtained from numerous Chinese provinces, including Jiangsu, Henan, Jilin, Hunan, Jiangxi, Anhui, Sichuan, Inner Mongolia, Zhejiang, Heilongjiang, Liaoning, Hubei, and Tianjin (Table 1). Isolate sensitivities to SYP-32497 and fluxapyroxad were assessed by mycelial growth inhibition tests. Natural populations had similar baseline sensitivities towards SYP-32497 and fluxapyroxad. SYP-32497 EC50 values for R. solani mycelial growth inhibition varied between 0.000790–0.0198 μg mL−1, with a mean of 0.00667 ± 0.00475 μg mL−1 (Figure 3). Fluxapyroxad EC50 values for R. solani mycelial growth inhibition varied between 0.0101–0.130 μg mL−1, with a mean of 0.0657 ± 0.0250 μg mL−1 (Figure 4). The SYP-32497 and fluxapyroxad EC50 values for the 360 field isolates were unimodally distributed with a positive skew, indicating that no SYP-32497 and fluxapyroxad resistance was detected (Figure 5).

3.2. Determination of Enzyme Efficiency

To preliminarily explore the SYP-32497 mode of action, we evaluated the effect of SYP-32497 and fluxapyroxad on SDH. SYP-32497 significantly inhibited succinate dehydrogenase activity, and its IC50 was 0.300 μg mL−1. In contrast, fluxapyroxad had an IC50 of 1.226 μg mL−1 and its inhibitory activity was thus lower (Figure 6).

3.3. Molecular Docking

A docking study was performed to illuminate detailed interactions between SYP-32497, fluxapyroxad, and the R. solani SDH complex. In the docking results, SYP-32497 revealed a binding mode similar to that of carboxin. The SYP-32497 amide group formed double hydrogen bonds with O/Trp-173 and Q/Tyr-58 residues (Figure 7A). A pyrazole ring was deeply embedded within the active cavity to form a π-cation interaction with P/Arg-43. Additionally, the benzene ring end of SYP-32497 was located in the hydrophobic cavity of the active pocket and formed a hydrophobic force with O/Pro-169, P/Met-36, and P/Ser-39. Free energy decomposition using a molecular dynamics simulation (Figure 7B) also showed that the above amino acids are important for the SYP-32497 and SDH binding process. Furthermore, the alkyl chain extended into the hydrophobic cavity of SDH, thereby creating a hydrophobic force which further stabilized the SYP-32497 and SDH binding (Figure 7C). Compared with SYP-32497, fluxapyroxad had a weaker affinity to SDH and only formed a hydrogen bond with the key amino acids on SDH (Figure 7D). The binding free energies of SYP-32497 and fluxapyroxad, with receptor SDH, were calculated by MM-PBSA and MM-GBSA using the molecular dynamics simulation (Table 2). SYP-32497 also had a stronger binding effect compared to the binding effect between fluxapyroxad and SDH.

4. Discussion

Fluxapyroxad is a succinate dehydrogenase inhibitor that was officially commercialized in 2012 in China. This is the first fluxapyroxad baseline sensitivity report regarding Chinese R. solani populations. To our knowledge, 360 R. solani isolates, which had not been previously exposed to fluxapyroxad and other SDHIs, were tested. These were found to be very sensitive to fluxapyroxad. The EC50 values for fluxapyroxad mycelial growth inhibition of wild-type R. solani populations were 0.0101–0.130 μg mL−1, with an average EC50 value of 0.0657 ± 0.0250 μg mL−1. The baseline sensitivity was unimodally distributed, and the maximum:minimum EC50 ratio was only 12.84. This indicated that no resistant subpopulations were present among the isolates. Therefore, the sensitivity baseline can be used for monitoring any future shifts in sensitivity of R. solani populations to fluxapyroxad in the field.
As a newly developed SDHI, SYP-32497 significantly inhibited the mycelial growth of 360 isolates of R. solani. The EC50 values of the mycelial growth inhibition by SYP-32497 varied from 0.000790 to 0.0198 μg mL−1, with an average EC50 value of 0.00667 ± 0.00475 μg mL−1. The baseline sensitivity was distributed as a unimodal curve. Therefore, the sensitivity baseline can be used for monitoring any future shifts in the sensitivity of R. solani population to SYP-32497 in the field. Various pathogens, such as Botrytis cinerea, Fusarium graminearum, and Corynespora cassiicola, have developed resistance to SDHIs [27,28,29,30], which are listed as moderately resistant by the Fungicide Resistance Action Committee (FRAC, https://www.frac.info/, accessed on 22 October 2022). However, R. solani field resistance towards SDHI has not been reported. Moreover, no change in R. solani sensitivity to fluxapyroxad was observed compared with previous studies. Chen et al. established that the sensitivity baseline of Rhizoctonia solani to fluxapyroxad in Anhui from 2008 to 2010 was 0.054 [21], which was not different from the 0.0657 obtained in this study. However, the area we studied was more extensive and representative than that used in the study. Therefore, our results are feasible as a sensitivity baseline, and SDHIs still have a large application value for controlling rice sheath blight.
In SDHIs, SYP-32497 (0.000790–0.01976) was suitably active against R. solani mycelial growth compared to fluxapyroxad (0.0101–0.1297), mepronil (0.005–0.304), and boscalid (0.05–8.65) [11]. A similar trend was observed for SDH inhibition and fungicidal activity in vitro against R. solani, whereby SYP-32497 significantly inhibited SDH activity with an IC50 value of 0.300 μg mL−1. Although the SDH from R. solani was weakly sensitive toward fluxapyroxad and with poor in vitro activity, the IC50 value of fluxapyroxad was 1.226 μg mL−1. Reagent and binding ability differences of the target protein are key to driving reagent selective activities [31,32]. The binding ability strengthens if there is a strong affinity between the molecule and the protein, resulting in a superior germicidal effect. SDH binds strongly to the ubiquinone binding site (QP site), blocking the substrate from accessing the site and thereby preventing the further cycle of succinate oxidation [33]. The molecular docking results showed that the SYP-32497 amide group forms a double hydrogen bond with the O/Trp-173 and Q/Tyr-58 residues. This contributed to a more stable binding between SDHIs and SDH [33]. However, fluxapyroxad only forms hydrogen bonds with key amino acids on SDH. Additionally, the alkyl chain extends into the hydrophobic cavity of SDH, thereby creating hydrophobicity, further stabilizing the binding of SYP-32497 and SDH. Therefore, SYP-32497 inhibited more mycelial growth and enzyme activities compared with fluxapyroxad.
SYP-32497 inhibited fungal growth by restraining SDH activity. The results of this study are consistent with previous reports [34]. SDHIs may be susceptible to resistance due to the specificity of their unit sites [35]. The risk of R. solani developing resistance to thifluzamide is low to moderate [20]. Moreover, H249Y in the SDHB protein caused laboratory-thifluzamide-resistance in R. solani, whereas mutant adaptability was simultaneously weakened [36]. Thus, it can be seen that R. solani can hardly develop resistance to SDHIs. Currently, SYP-32497 is not registered for the control of R. solani in China. However, it can potentially be an acceptable fungicide for controlling R. solani. Although this study established the baseline sensitivity of SYP-32497 and fluxapyroxad to R. solani, its risk assessment and molecular resistance mechanisms need to be clarified.
In general, multinucleated R. solani is not easy to develop fungicide resistance. At present, except jinggangmycin, R. solani is still sensitive to many kinds of fungicides. Gao et al. found that R. solani in Shanghai is still sensitive to epoxiconazole, difenoconazole, hexaconazole, and tebuconazole [37]. Even though triazole fungicides have been used in rice fields for a long time, the resistance of pathogens to these fungicides should be evaluated by establishing a sensitivity baseline and continuously monitoring the changes in the fungicide sensitivity of the pathogens. If left uncontrolled, the fungicides-resistant strains will lead to the spread of diseases. Thus, the rotational use of fungicides is a very critical technology, just as we did not pay attention to the use of jinggangmycin at the beginning, increasing the risk of jinggangmycin resistance [11]. Our research provides a new alternative fungicide, SYP-32497, which can be used in rotation with other fungicides for long-term control of rice sheath blight caused by R. solani.
However, the different AGs of R. solani exhibit different sensitivities to the same fungicide. The AG-4 is less sensitive than the AG1-IA, and the dinucleated R. solani is more likely to develop resistance to fungicides. Zhao et al. found that AG-4 had developed a relatively severe resistance to thifluzamide [38]. Our study only evaluated the sensitivity of AG1-IA to SPY-32497 and fluxapyroxad was tested, which was different for the different karyotypes. Additionally, we did not analyze the infectivity germinating sclerotia. R. solani overwinters in the field through sclerotia and becomes the initial infection source in the second year [39]. Thus, the inhibition test of SPY-32497 and fluxapyroxad on sclerotia germination needs to be further studied.

5. Conclusions

In summary, rice sheath blight caused by R. solani is the most destructive disease inrice, and fungicides are the main control measures for this disease. Our results showed that SYP-32497 and fluxapyroxad inhibit the growth of R. solani by hindering succinate dehydrogenase activity, and no resistance was reported against these two fungicides. Thus, if registered, SYP-32497 might be a new fungicide for the control of rice sheath blight.

Author Contributions

Conceptualization, Y.D. (Yunyan Deng); Methodology, Y.D. (Yunyan Deng) and Z.Q.; Formal analysis, T.W.; Investigation, Y.D. (Yunyan Deng) and M.J.; Data curation, P.Z., T.W., Z.Q., Y.D. (Ying Du) and L.L.; Writing original draft, P.Z.; Project administration, M.J.; Funding acquisition, M.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to thank the Shenyang Research Institute of Chemical Industry, which provided the active agent needed for the experiment.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pareja, L.; Fernández-Alba, A.R.; Cesio, V.; Heinzen, H. Analytical methods for pesticide residues in rice. TrAC Trends Anal. Chem. 2011, 30, 270–291. [Google Scholar] [CrossRef]
  2. Zhang, Z.J.; Zeng, Y.; Jiang, Z.Y.; Shu, B.S.; Sethuraman, V.; Zhong, G.H. Design, synthesis, fungicidal property and QSAR studies of novel beta-carbolines containing urea, benzoylthiourea and benzoylurea for the control of rice sheath blight. Pest Manag. Sci. 2018, 74, 1736–1746. [Google Scholar] [CrossRef] [PubMed]
  3. Moliszewska, E.; Nabrdalik, M.; Ziembik, Z. Rhizoctonia solani AG 11 isolated for the first time from sugar beet in Poland. Saudi J. Biol. Sci. 2020, 27, 1863–1870. [Google Scholar] [CrossRef]
  4. Singh, P.; Mazumdar, P.; Harikrishna, J.A.; Babu, S. Sheath blight of rice: A review and identification of priorities for future research. Planta 2019, 250, 1387–1407. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Gonzalez, M.; Pujol, M.; Metraux, J.-P.; Gonzalez-Garcia, V.; Bolton, M.D.; Borrás-Hidalgo, O. Tobacco leaf spot and root rot caused by Rhizoctonia solani Kuhn. Mol. Plant Pathol. 2011, 12, 209–216. [Google Scholar] [CrossRef] [PubMed]
  6. Abbas, A.; Mubeen, M.; Sohail, M.A.; Solanki, M.K.; Hussain, B.; Nosheen, S.; Kashyap, B.K.; Zhou, L.; Fang, X. Root rot a silent alfalfa killer in China: Distribution, fungal, and oomycete pathogens, impact of climatic factors and its management. Front. Microbiol. 2022, 13, 961794. [Google Scholar] [CrossRef] [PubMed]
  7. Ghosh, S.; Gupta, S.K.; Jha, G. Identification and functional analysis of AG1-IA specific genes of Rhizoctonia solani. Curr. Genet. 2014, 60, 327–341. [Google Scholar] [CrossRef] [PubMed]
  8. Zheng, A.; Lin, R.; Zhang, D.; Qin, P.; Xu, L.; Ai, P.; Ding, L.; Wang, Y.; Chen, Y.; Liu, Y.; et al. The evolution and pathogenic mechanisms of the rice sheath blight pathogen. Nat. Commun. 2013, 4, 1424. [Google Scholar] [CrossRef] [Green Version]
  9. Wu, W.; Huang, J.; Cui, K.; Nie, L.; Wang, Q.; Yang, F.; Shah, F.; Yao, F.; Peng, S. Sheath blight reduces stem breaking resistance and increases lodging susceptibility of rice plants. Field Crops Res. 2012, 128, 101–108. [Google Scholar] [CrossRef]
  10. Suharti, W.S.; Nose, A.; Zheng, S.H. Metabolomic study of two rice lines infected by Rhizoctonia solani in negative ion mode by CE/TOF-MS. J. Plant Physiol. 2016, 206, 13–24. [Google Scholar] [CrossRef]
  11. Zhang, C.Q.; Liu, Y.H.; Ma, X.Y.; Feng, Z.; Ma, Z.H. Characterization of sensitivity of Rhizoctonia solani, causing rice sheath blight, to mepronil and boscalid. Crop Prot. 2009, 28, 381–386. [Google Scholar] [CrossRef]
  12. Dalla Pozza, E.; Dando, I.; Pacchiana, R.; Liboi, E.; Scupoli, M.T.; Donadelli, M.; Palmieri, M. Regulation of succinate dehydrogenase and role of succinate in cancer. Semin. Cell Dev. Biol. 2020, 98, 4–14. [Google Scholar] [CrossRef] [PubMed]
  13. Moosavi, B.; Berry, E.A.; Zhu, X.L.; Yang, W.C.; Yang, G.F. The assembly of succinate dehydrogenase: A key enzyme in bioenergetics. Cell. Mol. Life Sci. 2019, 76, 4023–4042. [Google Scholar] [CrossRef]
  14. Gill, A.J. Succinate dehydrogenase (SDH)-deficient neoplasia. Histopathology 2018, 72, 106–116. [Google Scholar] [CrossRef] [PubMed]
  15. Yang, D.-Y.; Zhao, B.; Fan, Z.; Yu, B.; Zhang, N.; Li, Z.-M.; Zhu, Y.; Zhou, J.; Kalinina, T.A.; Glukhareva, T.V. Synthesis and Biological Activity of Novel Succinate Dehydrogenase Inhibitor Derivatives as Potent Fungicide Candidates. J. Agric. Food Chem. 2019, 67, 13185–13194. [Google Scholar] [CrossRef] [PubMed]
  16. Huang, X.P.; Luo, J.; Li, B.X.; Song, Y.F.; Mu, W.; Liu, F. Bioactivity, physiological characteristics and efficacy of the SDHI fungicide pydiflumetofen against Sclerotinia sclerotiorum. Pestic. Biochem. Physiol. 2019, 160, 70–78. [Google Scholar] [CrossRef] [PubMed]
  17. Miyamoto, T.; Hayashi, K.; Okada, R.; Wari, D.; Ogawara, T. Resistance to succinate dehydrogenase inhibitors in field isolates of Podosphaera xanthii on cucumber: Monitoring, cross-resistance patterns and molecular characterization. Pestic. Biochem. Physiol. 2020, 169, 104646. [Google Scholar] [CrossRef]
  18. Ji, X.; Li, J.; Meng, Z.; Zhang, S.; Dong, B.; Qiao, K. Synergistic Effect of Combined Application of a New Fungicide Fluopimomide with a Biocontrol Agent Bacillus methylotrophicus TA-1 for Management of Gray Mold in Tomato. Plant Dis. 2019, 103, 1991–1997. [Google Scholar] [CrossRef]
  19. Lyu, L.; Wand, G.; Wu, S.-S.; Shan, Z.-G.; Li, B. Synthesis and Fungicidal Activity of SYP-32497. Agrochemicals 2020, 59, 871–872. [Google Scholar]
  20. Mu, W.; Wang, Z.; Bi, Y.; Ni, X.; Hou, Y.; Zhang, S.; Liu, X. Sensitivity determination and resistance risk assessment of Rhizoctonia solani to SDHI fungicide thifluzamide. Ann. Appl. Biol. 2017, 170, 240–250. [Google Scholar] [CrossRef]
  21. Chen, Y.; Yao, J.; Yang, X.; Zhang, A.-F.; Gao, T.-C. Sensitivity of Rhizoctonia solani causing rice sheath blight to fluxapyroxad in China. Eur. J. Plant Pathol. 2014, 140, 419–428. [Google Scholar] [CrossRef]
  22. Matsumoto, M.; Matsuyama, N. Trials of direct detection and identification of Rhizoctonia solani, AG1 and AG2 subgroups using specifically primed PCR analysis. Mycoscience 2002, 43, 185–189. [Google Scholar] [CrossRef]
  23. Hederstedt, L.; Rutberg, L. Succinate Dehydrogenase—A Comparative Review. Microbiol. Rev. 1981, 45, 542–555. [Google Scholar] [CrossRef] [PubMed]
  24. Shi, Y.; Zhu, F.; Sun, B.; Xie, X.; Chai, A.; Li, B. Two adjacent mutations in the conserved domain of SdhB confer various resistance phenotypes to fluopyram in Corynespora cassiicola. Pest Manag. Sci. 2021, 77, 3980–3989. [Google Scholar] [CrossRef] [PubMed]
  25. Gao, Y.; He, L.; Zhu, J.; Cheng, J.; Li, B.; Liu, F.; Mu, W. The relationship between features enabling SDHI fungicide binding to the Sc-Sdh complex and its inhibitory activity against Sclerotinia sclerotiorum. Pest Manag. Sci. 2020, 76, 2799–2808. [Google Scholar] [CrossRef] [PubMed]
  26. Wang, G.; Cui, P.; Bai, H.; Wei, S.; Li, S. Late-Stage C-H Functionalization of Nicotinamides for the Expedient Discovery of Novel Antifungal Leads. J. Agric. Food Chem. 2019, 67, 11901–11910. [Google Scholar] [CrossRef]
  27. Dooley, H.; Shaw, M.W.; Mehenni-Ciz, J.; Spink, J.; Kildea, S. Detection of Zymoseptoria tritici SDHI-insensitive field isolates carrying the SdhC-H152R and SdhD-R47W substitutions. Pest Manag. Sci. 2016, 72, 2203–2207. [Google Scholar] [CrossRef]
  28. Sun, H.Y.; Cui, J.H.; Tian, B.H.; Cao, S.L.; Zhang, X.X.; Chen, H.G. Resistance risk assessment for Fusarium graminearum to pydiflumetofen, a new succinate dehydrogenase inhibitor. Pest Manag. Sci. 2020, 76, 1549–1559. [Google Scholar] [CrossRef]
  29. Bardas, G.A.; Veloukas, T.; Koutita, O.; Karaoglanidis, G.S. Multiple resistance of Botrytis cinerea from kiwifruit to SDHIs, QoIs and fungicides of other chemical groups. Pest Manag. Sci. 2010, 66, 967–973. [Google Scholar] [CrossRef]
  30. Miyamoto, T.; Ishii, H.; Stammler, G.; Koch, A.; Ogawara, T.; Tomita, Y.; Fountaine, J.M.; Ushio, S.; Seko, T.; Kobori, S. Distribution and molecular characterization of Corynespora cassiicola isolates resistant to boscalid. Plant Pathol. 2010, 59, 873–881. [Google Scholar] [CrossRef]
  31. Jin, H.; Zhou, J.; Pu, T.; Zhang, A.; Gao, X.; Tao, K.; Hou, T. Synthesis of novel fenfuram-diarylether hybrids as potent succinate dehydrogenase inhibitors. Bioorg. Chem. 2017, 73, 76–82. [Google Scholar] [CrossRef]
  32. He, M.Y.; Li, W.K.; Meiler, J.; Zheng, Q.C.; Zhang, H.X. Insight on mutation-induced resistance to anaplastic lymphoma kinase inhibitor ceritinib from molecular dynamics simulations. Biopolymers 2019, 110, e23257. [Google Scholar] [CrossRef] [PubMed]
  33. Sierotzki, H.; Scalliet, G. A review of current knowledge of resistance aspects for the next-generation succinate dehydrogenase inhibitor fungicides. Phytopathology 2013, 103, 880–887. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Hou, Y.P.; Chen, Y.L.; Qu, X.P.; Wang, J.X.; Zhou, M.G. Effects of a novel SDHI fungicide pyraziflumid on the biology of the plant pathogenic fungi Bipolaris maydis. Pestic. Biochem. Physiol. 2018, 149, 20–25. [Google Scholar] [CrossRef]
  35. Fraaije, B.A.; Bayon, C.; Atkins, S.; Cools, H.J.; Lucas, J.A.; Fraaije, M.W. Risk assessment studies on succinate dehydrogenase inhibitors, the new weapons in the battle to control Septoria leaf blotch in wheat. Mol. Plant Pathol. 2012, 13, 263–275. [Google Scholar] [CrossRef] [Green Version]
  36. Miao, J.; Mu, W.; Bi, Y.; Zhang, Y.; Zhang, S.; Song, J.; Liu, X. Heterokaryotic state of a point mutation (H249Y) in SDHB protein drives the evolution of thifluzamide resistance in Rhizoctonia solani. Pest Manag. Sci. 2021, 77, 1392–1400. [Google Scholar] [CrossRef]
  37. Gao, S.; Xu, L.; Zeng, R.; Gao, P.; Song, Z.; Dai, F. Baseline sensitivity of Rhizoctonia solani to four DMI fungicides. J. Basic Microbiol. 2022, 62, 701–710. [Google Scholar] [CrossRef]
  38. Zhao, C.; Li, Y.; Liang, Z.; Gao, L.; Han, C.; Wu, X. Molecular Mechanisms Associated with the Resistance of Rhizoctonia solani AG-4 Isolates to the Succinate Dehydrogenase Inhibitor Thifluzamide. Phytopathology 2022, 112, 567–578. [Google Scholar] [CrossRef]
  39. Liu, B.; Wang, H.; Ma, Z.; Gai, X.; Sun, Y.; He, S.; Liu, X.; Wang, Y.; Xuan, Y.; Gao, Z. Transcriptomic evidence for involvement of reactive oxygen species in Rhizoctonia solani AG1 IA sclerotia maturation. PeerJ 2018, 6, e5103. [Google Scholar] [CrossRef] [PubMed]
Agronomy 12 03075 g001 550
Figure 1. Structures of mepronil, SYP-32497, bixafen, and fluxapyroxad.
Figure 1. Structures of mepronil, SYP-32497, bixafen, and fluxapyroxad.
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Figure 2. PCR amplification DNA of R. solani AG1-IA.
Figure 2. PCR amplification DNA of R. solani AG1-IA.
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Figure 3. Frequency distribution of sensitivity (baseline sensitivity) of SYP-32497 to R. solani.
Figure 3. Frequency distribution of sensitivity (baseline sensitivity) of SYP-32497 to R. solani.
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Figure 4. Frequency distribution of sensitivity of (baseline sensitivity) fluxapyroxad to R. solani.
Figure 4. Frequency distribution of sensitivity of (baseline sensitivity) fluxapyroxad to R. solani.
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Figure 5. Mycelial inhibition of R. solani (YC6, YZ1, JX14) treated with different concentrations of fluxapyroxad and SYP-32497.
Figure 5. Mycelial inhibition of R. solani (YC6, YZ1, JX14) treated with different concentrations of fluxapyroxad and SYP-32497.
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Figure 6. Enzymatic efficiencies after treatment with SYP-32497 and fluxapyroxad.
Figure 6. Enzymatic efficiencies after treatment with SYP-32497 and fluxapyroxad.
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Figure 7. The docking binding mode of SYP-32497 and fluxapyroxad with succinate dehydrogenase (PDB code: 2FBW): (A) The binding pattern of compound SYP-32497 to SDH; (B) Free energy decomposition of SYP-32497 combined with SDH; (C) Composite diagram of SYP-32497 and the combination mode of fluxapyroxad and SDH; (D) The binding pattern of fluxapyroxad and SDH.
Figure 7. The docking binding mode of SYP-32497 and fluxapyroxad with succinate dehydrogenase (PDB code: 2FBW): (A) The binding pattern of compound SYP-32497 to SDH; (B) Free energy decomposition of SYP-32497 combined with SDH; (C) Composite diagram of SYP-32497 and the combination mode of fluxapyroxad and SDH; (D) The binding pattern of fluxapyroxad and SDH.
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Table
Table 1. Sensitivity of SYP-32497 and fluxapyroxad to R. solani in China.
Table 1. Sensitivity of SYP-32497 and fluxapyroxad to R. solani in China.
Region, ProvinceCoordinatesNumber of Isolates and CodeSYP–32497 EC50 (μg mL−1)Fluxapyroxad EC50 (μg mL−1)
RangeMeanRangeMean
Hefei, Anhui ProvinceE117.22 N31.823 HF0.00794–0.019760.01528 ± 0.006410.07680–0.104900.09367 ± 0.01487
Tiaozhou, Anhui ProvinceE117.54 N32.9312 TZ0.00085–0.014830.00426 ± 0.004230.04210–0.101400.06721 ± 0.02037
Fengyang, Anhui ProvinceE117.82 N32.8517 FY0.00079–0.009740.00268 ± 0.002390.00093–0.008040.04547 ± 0.02469
Jixi, Heilongjiang ProvinceE132.40 N45.9114 JX0.00105–0.009450.00397 ± 0.002440.03220–0.086800.06606 ± 0.01623
Jiamusi, Heilongjiang ProvinceE130.89 N47.044 JMS0.00156–0.017450.01155 ± 0.006940.08070–0.125400.10015 ± 0.01856
Haerbin, Heilongjiang ProvinceE127.03 N45.4915 HEB0.00202–0.010730.00502 ± 0.002760.03500–0.094900.06315 ± 0.01663
Xinyang, Henan ProvinceE114.21 N32.128 XY0.00149–0.014930.00870 ± 0.003980.05340–0.096700.08115 ± 0.01437
Yanghe, Henan ProvinceE113.74 N32.444 YH0.00413–0.007690.00663 ± 0.001690.03780–0.125700.09825 ± 0.04064
Xiaochang, Hubei ProvinceE113.97 N31.394 XC0.00555–0.018370.01446 ± 0.006060.09120–0.111200.09888 ± 0.00864
Songzi, Hubei ProvinceE111.88 N30.183 SC0.00371–0.007750.00514 ± 0.002260.03850–0.071800.05050 ± 0.01850
Yizhou, Hunan ProvinceE112.32 N28.9313 YZ0.00125–0.013150.00535 ± 0.003430.03690–0.124000.08252 ± 0.02572
Miluo, Hunan ProvinceE113.09 N28.892 ML0.00258–0.005850.00422 ± 0.002310.04980–0.061100.05545 ± 0.00799
Inner MongoliaE123.28 N46.719 XAM0.00445–0.016920.00952 ± 0.004540.05230–0.094800.07062 ± 0.01571
Yancheng, Jiangsu ProvinceE119.89 N33.4318 YCH0.00171–0.018710.00907 ± 0.005720.05160–0.129700.08518 ± 0.02194
Nanjing, Jiangsu ProvinceE118.89 N32.0411 NJ0.00093–0.008040.00452 ± 0.002310.03310–0.095100.05313 ± 0.01919
Nanchang, Jiangxi ProvinceE115.64 N28.457 NC0.00082–0.004220.00241 ± 0.001200.02740–0.070900.04783 ± 0.01431
Yichun, Jiangxi ProvinceE115.19 N28.022 YC0.01215–0.012280.01222 ± 0.000090.03770–0.055900.04680 ± 0.01287
Gaoan, Jiangxi ProvinceE115.14 N28.479 GA0.00178–0.017230.00637 ± 0.004490.04060–0.077600.06131 ± 0.01275
Xinjian, Jiangxi ProvinceE115.85 N28.695 XJ0.00273–0.011060.00655 ± 0.003540.04240–0.088900.06684 ± 0.02044
Fuzhou, Jiangxi ProvinceE116.37 N28.017 FZ0.00192–0.018360.01115 ± 0.007050.01590–0.127800.07637 ± 0.04073
Shuangliao, Jilin ProvinceE123.41 N43.5212 SL0.00299–0.019570.00802 ± 0.004450.05010–0.113300.07340 ± 0.01824
Changyi, Jilin ProvinceE126.40 N44.1421 CY0.00155–0.017150.00820 ± 0.004890.05050–0.125400.07559 ± 0.02047
Panshi, Jilin ProvinceE126.07 N42.959 PS0.00175–0.014190.00779 ± 0.005190.04260–0.109900.08222 ± 0.02303
Gongzhuling, Jilin ProvinceE124.75 N43.469 GZL0.00132–0.019010.00959 ± 0.005290.03660–0.097600.07673 ± 0.01920
Shenyang, Liaoning ProvinceE123.55 N41.9710 SY0.00323–0.017460.00865 ± 0.004730.04540–0.105200.07091 ± 0.01844
Fushun, Liaoning ProvinceE124.98 N41.754 FS0.00171–0.013090.00714 ± 0.004680.04620–0.084400.05838 ± 0.01781
Tieling, Liaoning ProvinceE123.88 N42.3233 TL0.00096–0.017160.00701 ± 0.005350.01680–0.095900.04333 ± 0.01932
Xinmin, Liaoning ProvinceE122.90 N41.899 XM0.00100–0.009110.00491 ± 0.002600.02480–0.079800.05912 ± 0.01825
Dandong, Liaoning ProvinceE123.9 N39.8611 DD0.00330–0.012430.00665 ± 0.003290.03730–0.085000.05799 ± 0.01403
Liaoyang, Liaoning ProvinceE123.10 N41.438 LY0.00085–0.008130.00409 ± 0.002690.03270–0.070800.05218 ± 0.01405
Dalian, Liaoning ProvinceE122.84 N39.744 DL0.00252–0.003600.00286 ± 0.000510.04370–0.061000.05153 ± 0.00784
Panjin, Liaoning ProvinceE122.19 N40.982 PJ0.00149–0.001900.00170 ± 0.000290.03890–0.056300.04760 ± 0.01230
Yingkou, Liaoning ProvinceE122.19 N40.827 YK0.00275–0.017560.00720 ± 0.005830.03940–0.129700.07489 ± 0.02904
Benxi, Liaoning ProvinceE125.30 N41.212 BX0.00256–0.002630.00260 ± 0.000050.04940–0.057700.05355 ± 0.00587
Anshan, Liaoning ProvinceE122.73 N40.985 AS0.00587–0.009380.00714 ± 0.001460.05260–0.090400.07180 ± 0.01432
Qingshen, Sichuan ProvinceE103.84 N29.832 QS0.00622–0.007650.00694 ± 0.001010.06780–0.092400.08010 ± 0.01739
TianjinE117.61 N39.4111 TJ0.00397–0.015860.00825 ± 0.003800.04350–0.103300.06325 ± 0.01933
Jinhua, Zhejiang ProvinceE119.49 N29.0716 JH0.00225–0.018100.00860 ± 0.004540.01680–0.123600.08876 ± 0.02787
Jiaxing, Zhejiang ProvinceE120.75 N30.7518 JXI0.00079–0.012220.00311 ± 0.002510.02–0.068400.03958 ± 0.01264
Table
Table 2. The binding free energy of SYP-32497 and fluxapyroxad with SDH.
Table 2. The binding free energy of SYP-32497 and fluxapyroxad with SDH.
FungicidesBinding Free Energy (kcal/mol)
GBPB
SYP-32497−45.9022−36.8614
Fluxapyroxad−23.7088−19.2052
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Zhao, P.; Deng, Y.; Wang, T.; Qi, Z.; Du, Y.; Liu, L.; Ji, M. Baseline Sensitivity to and Succinate Dehydrogenase Activity and Molecular Docking of Fluxapyroxad and SYP-32497 in Rice Sheath Blight (Rhizoctonia solani AG1-IA) in China. Agronomy 2022, 12, 3075. https://doi.org/10.3390/agronomy12123075

AMA Style

Zhao P, Deng Y, Wang T, Qi Z, Du Y, Liu L, Ji M. Baseline Sensitivity to and Succinate Dehydrogenase Activity and Molecular Docking of Fluxapyroxad and SYP-32497 in Rice Sheath Blight (Rhizoctonia solani AG1-IA) in China. Agronomy. 2022; 12(12):3075. https://doi.org/10.3390/agronomy12123075

Chicago/Turabian Style

Zhao, Ping, Yunyan Deng, Tao Wang, Zhiqiu Qi, Ying Du, Liru Liu, and Mingshan Ji. 2022. "Baseline Sensitivity to and Succinate Dehydrogenase Activity and Molecular Docking of Fluxapyroxad and SYP-32497 in Rice Sheath Blight (Rhizoctonia solani AG1-IA) in China" Agronomy 12, no. 12: 3075. https://doi.org/10.3390/agronomy12123075

APA Style

Zhao, P., Deng, Y., Wang, T., Qi, Z., Du, Y., Liu, L., & Ji, M. (2022). Baseline Sensitivity to and Succinate Dehydrogenase Activity and Molecular Docking of Fluxapyroxad and SYP-32497 in Rice Sheath Blight (Rhizoctonia solani AG1-IA) in China. Agronomy, 12(12), 3075. https://doi.org/10.3390/agronomy12123075

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