Metabonomics analysis of Iron shell wheat (Triticum aestivum ssp. yunnanense King) reveals mechanisms of resistance against powdery mildew

doi:10.21203/rs.3.rs-1652019/v1

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Metabonomics analysis of Iron shell wheat (Triticum aestivum ssp. yunnanense King) reveals mechanisms of resistance against powdery mildew

https://doi.org/10.21203/rs.3.rs-1652019/v1

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Wheat powdery mildew (Bgt), a fungal seeding disease, is a threat to wheat agriculture worldwide. In this study, Iron shell wheat (Triticum aestivum ssp. yunnanense King) was used as the research material. Extensive targeted metabolomic analysis was conducted on the leaves of the susceptible strain Iron shell wheat 1 (DiKe 1) and the normal resistant strain Zhenkang Iron shell wheat (Yunmai 0030); further, the dynamic physiological changes in metabolite levels between the two strains were assessed. Significant differences were identified in tryptophan and pyrimidine metabolism as well as isoquinoline alkaloid biosynthesis. The main metabolites were phenolic acids, flavonoid carboglycosides, indole alkaloids, phenolic amines, amino acids, and their derivatives. The defense response to powdery mildew in the Iron shell wheat was dominated by tryptophan metabolism. The importance of L-dopa and Tyramine in powdery mildew resistance provides new insights into the relevant mechanisms and can help identify antigens for use in the breeding of powdery-mildew-resistant wheat varieties.

powdery mildew

Triticum aestivum ssp. yunnanense King

tryptophan metabolism

tyramine

L-dopa

Triticum aestivum ssp. yunnanense King, also known as Yunnan wheat, is a hexaploid wheat germplasm used in Yunnan, China, and it is one of the three common wheat subspecies which are unique to China [1–3]. T. aestivum ssp. yunnanense King is rich in genetic variation and has good disease-resistance ability. It is an important genetic resource that is used in the breeding of new disease-resistant wheat varieties. Wheat powdery mildew (Bgt) is an airborne disease caused by Blumeria graminis f., which is active in all wheat growing areas around the world [4]. In the early stages of disease, small white spots can be seen on the leaves, and the infected parts then expand rapidly to form a white mold layer. In the later stages, the color of the mold layer changes from white to gray, and then gray to light brown, until the leaves turn green, yellow, curly, and then die. The 1000 grain weight and crude protein content of wheat are inversely proportional to the occurrence of powdery mildew [5], which seriously interferes with the normal source sink relationship of plants [6], greatly reduces the quality of wheat, and can reduce the yield by up to 30% [7–8]. Wheat powdery mildew mainly occurs in marine or semi continental climate areas [9]. In recent years, due to the continuous changes in the global climate, wheat varieties, and pathogen populations, the incidence and spread of powdery mildew disease has shown an upward trend [10–11].

Wheat powdery mildew resistance is an extremely complex quantitative trait, that is not regulated by a single gene or metabolite. Approximately 14% of the annotated genes in Arabidopsis are directly related to pathogen defense in response to powdery mildew [12], and these genes and their metabolites are involved in a complex set of interactions. The expression of metabolites can be regarded as the final response in biological systems to genetic or environmental changes. They are not only directly involved in the response of plants to the external environment, but also affected by plant gene transcription and protein expression. Metabolites can also affect and regulate gene transcription as well as protein expression and activity [13]. Metabolome studies can thus examine the product changes of protease in the metabolic process, which is the bridge between gene and phenotype. As the basis of biological phenotype, the metabolome can help us to intuitively understand biological processes and their mechanisms. When wheat is subjected to biological or abiotic stress, it synthesizes relevant metabolites in response [14]. In previous studies, tryptophan derived metabolites [15], indole metabolites, jasmonic acid, callose, phenolic acids, flavonoids, alkaloids, and other compounds were identified as important for plant resistance to powdery mildew [16–18]. The response of wheat to powdery mildew is dynamic, and the expression of relevant metabolites is regulated by time.

To understand the mechanisms associated with wheat resistance to powdery mildew stress, we have investigated the changes in metabolite levels using metabolome detection technology, which produces more accurate qualitative and quantitative analysis than the other two technologies (Targeted metabolomics /Untargeted metabolomics). Analysis of the metabolic differences between the susceptible and normal wheat leaves from a molecular perspective was conducted to explore the mechanisms of wheat powdery mildew resistance. The resulting data will provide a theoretical basis for the development of new varieties with high and stable yields and strong disease resistance.

Data quality control and qualitative and quantitative metabolite analysis

The overlapping display analysis for the total ion flow which was detected and analyzed by mass spectrometry for the quality of the control samples (QC), showed that the overlap was high in both the positive and negative ion modes (Fig. S1a and b). This provides an important guarantee for the authenticity and reliability of the data. According to the PCA score diagram (Fig. 1a) and the sample correlation diagram (Fig. S1c), the Pearson correlation coefficients in the four sample groups are R > 0.8, and the overall repeatability is good. Among them, the contribution values of PC1 and PC2 are 26.34% and 22.1%, respectively. There are obvious differences among the groups, which is of research significance. The results showed that 1078 metabolites were detected, including 95 amino acids and their derivatives, 178 phenolic acids, 67 nucleotides and their derivatives, 234 flavonoids, 30 lignans and coumarins, 3 tannins, 111 alkaloids, 22 terpenoids, 84 organic acids, 154 lipids, and 100 others. A heat map showing all the metabolites classified by substance is shown in Fig. 1b. The substances with many metabolites that may vary in each group are the flavonoids, organic acids, lipids, and alkaloids. Before the difference analysis, the samples of each group were analyzed by opls-da. The opls-da score diagram and opls-da verification diagram (Fig. S2) showed that there were significant differences among the groups, especially N-G vs P-G and P-K vs P-G, Q2, which were greater than 0.85. Most of the P values for the established models were < 0.05, and their prediction ability was better.

Analysis of metabolite differences among the combinations

The obtained multivariable analysis of the variable importance in projection (VIP) from the opls-da model was combined with the fold change to further screen out the differential metabolites. Metabolites with fold changes ≥ 2 or ≤ 0.5 and VIP ≥ 1 were regarded as differential metabolites. The quantities of the differential metabolites between the different combinations are shown in Table S1.

Taking N-G vs P-G, N-K vs P-K, and P-K vs P-G as the key research objects, a metabolite-differences diagram (Fig. 2) shows the relative content difference and statistical significance of the metabolites in different combinations, and the differences in multiple histograms (Fig. S3) show the top ten metabolites with up-down differences in each combination. The results show that there are 200 difference metabolites in N-G vs P-G (up 133; down 67). There are 34 alkaloids in the up-regulated substances, and phenolic acids and flavonoids were the most down-regulated substances, and these included vitexin-7-O-glucoside, N-p-coumaroyl-N'-feruloylputrescine, p-coumaroylferuloylputrescine, N-feruloylserotonin, and LysoPC 20:0, while down-regulated substances included DIMBOA, neochlorogenic acid, 5-O-caffeoylquinic acid*, 3-O-p-coumaroylquinic acid*, and 4-acetoxy-3-ethoxybenzaldehyde. There are 223 differential metabolites (up 140; down 83) in P-K vs P-G. Lipids and alkaloids account for more up-regulation, and include L-cysteine, kaempferol, heptadecanoic acid, 2'-O-methyladenosine, and cis-moschamine. There are more phenolic acids and flavonoids that were down-regulated. The first 10 down-regulated phenolic acids are mostly the same as N-G vs P-G. There were other down-regulations, such as for 13s-hydroperoxy-6z, 9z, 11e-octadecaterinoic acid 6-methoxy-2-4h-chrome-4-one, lysoPC 19:2 (2n isomer), and lysoPC 19:2. There were 138 differential metabolites in N-K vs P-K (up 60; down 78). The most up-regulated substances were phenolic acids, such as 1-O-p-hydroxycinnamoyl-3-O-caffeoylglycerol, vitexin-7-O-glucoside, and 3-indolepropionic acid. The most down-regulated substances were phenolic acids and flavonoids, such as L-cysteine, acetate, and benzoylmalic acid. There are 18 differential metabolites (up 8; down 10) in N-K vs N-G. Up-regulated substances included pimaric acid, 3-hydroxydecanoic acid, and 3-indolepropionic acid, and down-regulated substances include epicatechin gallate*, palmitoleic acid, and the glutathione (reduced form). In conclusion, phenolic acids, alkaloids, and flavonoids were found to be closely related to the resistance of iron shell wheat to powdery mildew.

K-means analysis

The relative levels of all the differential metabolites identified according to the screening criteria in all grouping comparisons were standardized by Z-score, and then the changes in the trends of the nine differential metabolites were obtained after K-means cluster analysis (Fig. 3a). The results showed that there were 76 differential metabolites in sub-class 2, 59 in sub-class 5, and 23 in sub-class 7. In sub-class 4, the metabolite content of P-G was significantly lower than that of P-K and n-k, and this included L-alanine, N-propionylglycine, and chlorogenic acid. In sub-class 2, sub-class 7, and sub-class 8, the metabolite content in P-G was significantly higher than that in P-K and n-k, and this included L-tryptophan, 2-piperidone, indole, agmatine, and scutellarin.

The statistics for the different metabolites among the groups and the relationships between the different metabolites in each group are shown in a Venn diagram (Fig. 3b). The results show that there are 389 significantly different metabolites in total, and 64 specifically different metabolites (up 39; down 25) in N-G vs P-G. Alkaloids and flavonoids are more abundant, such as indole, spermidine, and some benzoxazine metabolites such as 6-hydroxy-2'-methoxyflavone, and syringen-7-O-glucoside. There were 98 specific metabolites (up 48; down 59) in P-K vs P-G, and the most abundant were flavonoids, such as kaempferol and eriodictyol. There were 48 specific differential metabolites (up 22; down 26) in N-K vs P-K, and most substances were phenolic acids; N-K vs N-G had 6 specific differential metabolites (up 4; down 2). A common differential metabolite among the four combinations was lysophosphatidylcholine 20:0 (2n isomer).There are 10 specific metabolites in the N-G vs P-G, P-K vs P-G, and N-K vs P-K groups. Such as 7-O-methylnaringenin, L-dopa, neochlorogenic acid, and 3-methyl-1-pentanol.

Differential metabolite enrichment analysis using the KEGG pathway

KEGG pathway enrichment analysis was performed according to the results of the differential metabolites, and a P value ≤ 0.05 indicated that the pathway was enriched and annotated with a significant difference. The top 20 metabolic pathways with enrichment degree in different combinations are shown in Fig. 4. The results show that 64 metabolic pathways were enriched and annotated in N-G vs P-G, and three of them were significantly different, namely tryptophan metabolism, pyrimidine metabolism, and isoquinoline alkaloid biosynthesis. There were 7 significantly different metabolites in tryptophan metabolism and all of them were up-regulated. Indole, 3-indoleacetonitrile, tryptamine, 2-benzoic acid, N-acetylisatin, and L-tryptophan, methoxyindoleacetic acid, in pyrimidine metabolism; there were 7 significantly different metabolites, and only 2-deoxyribose-1-phosphate was down-regulated. A total of 57 metabolic pathways were enriched and annotated in P-K vs P-G, and the three significant differences were pyrimidine metabolism, folate biosynthesis, and alpha-linolenic acid metabolism. There were 8 significantly different metabolites in the pyrimidine metabolism. Compared with the pyrimidine metabolism of N-G vs P-G, one more metabolite was cytidine 5'-monophosphate. The other 7 metabolites were identical with the same expression trends, such as cytosine, orotic acid, thymidine, and cytidine. There were 52 metabolic pathways enriched and annotated in N-K vs P-K, of which 11 were significantly different. The top 3 pathways were the sulfur relay system, biosynthesis of amino acids, and lysine degradation, respectively. In the sulfur relay system, three different metabolites were annotated and down-regulated, including L-cysteine, O-acetylserine, and S-adenosyl-l-methionine. In the biosynthesis of amino acids, 9 differential metabolites (up 4; down 5) were annotated. The up-regulated were L-proline, L-ornithine, phosphoenolpyruvate, and D-erythrose-4-phosphate, while the down-regulated included L-cysteine, anthranilic acid, and α -ketoglutaric acid. A total of 25 metabolic pathways were enriched and annotated in N-K vs N-G, and 6 were significantly different, including acridone alkaloid biosynthesis, nitrogen metabolism and biotin metabolism.

Powdery mildew resistance is an extremely complex quantitative trait, and plant defenses often involve the induction of systems after a plant detects an attack. Innate defense systems, both PAMP-triggered immunity [19] and effector-triggered immunity [20], involve the regulation of various plant hormones through complex signal networks. In this study, extensive targeted metabolic technology was used to study the metabolic differences between susceptible and normal resistant strains and to improve our understanding of the related mechanisms of resistance to powdery mildew that occur in Triticale, in combination with its defense response.

Pathogens, like our breeding technologies, are constantly evolving, and as a result, many of our fungicides are not as effective as they once were [21]. To ensure the sustainability and productivity of crops, the breeding of new resistant varieties is the best and most economically valuable strategy. Based on the qualitative and quantitative analysis of metabolites, this study compared the metabolic differences between diseased and disease resistant Triticale. The screened differential metabolic pathways and differential metabolites reflected the dynamic responses of Triticale to powdery mildew, and the enrichment results of the metabolic pathways showed that the main metabolic pathways related to powdery mildew resistance are tryptophan metabolism, pyrimidine metabolism, and the biosynthesis of amino acids. The differential metabolites identified were mainly phenolic acids, flavonoids, carboglycosides, indole alkaloids, phenolic amines, amino acids, and their derivatives, which are similar to previous findings [19–22], indicating that these substances play an important role in the fight against powdery mildew. Among the flavonoids, catechins, kaempferol, and rhamnose are considered antibacterial agents and antioxidants [23–25], Metabolites such as P-coumaroyl feruloylputrescine, L-cysteine, kaempferol, agmatine, acetate, 7-O-methylnaringenin, and L-dopa play an important regulatory role in the resistance of iron shell wheat to powdery mildew. Most plants utilize the same defense mechanism when pathogens invade, which contains a broad spectrum of resistance [26–27], in addition, we found higher quantities of most alkaloid substances in the infected strains, while the flavonoids and phenolic acids were higher in the resistant strain. We concluded that the strength of the plants disease resistance was related to flavonoids and phenolic acids, and high expression levels for alkaloids were likely to be due to the plants defense against pathogen invasion.

The detection results for a wide range of metabolites were analyzed with a focus on the defense mechanisms of iron-husk wheat with tryptophan metabolism against powdery mildew. Arabidopsis thaliana, after infection with powdery mildew, changes the expression levels of secondary metabolites derived from tryptophan and reduced the level of indol-3-ylmethyl glucosinolate [28], which proves that tryptophan-derived metabolites play an important role in plant defense responses [29–31]. In addition, indoles and indole metabolites transformed from tryptophan were found to be involved in the defense responses of plants, such as indole-3-acetaldehyde oxime and indole-3-acetonitrile [32]. The expression levels of putrescine, tyramine, agidine, and 5-ht were higher in resistant cultivars but not in susceptible cultivars after inoculation [33]. Phenylbenzine ammonia-lyase (PAL) plays an important role in the normal growth and development of plants and resistance to pathogen attack. L-dopa provides a substrate for the synthesis of PAL by detoxifying phenylbenzene [34–35]. In defense responses dominated by the tryptophan metabolic pathway (Fig. 5), tryptophan and L-glutamine can be synthesized by glycerate-3p generated anthranilate. The expression levels of tyramine, L-dopa, and 2-deoxy-ribose-1P in susceptible lines were significantly lower than those in resistant lines. The expression levels of tryptophan, L-dopa, indole, tryptamine, orotate, and cytosine were significantly higher than those of normal resistant strains, which may be because the invasion of powdery mildew initiated defense mechanisms in the crops and increased the formation of antibacterial substances. For example, L-dopa provides many substrates for PAL synthesis. The low expression or inadequate synthesis ability of tyramine and 2-deoxy-ribose-1 in DiKe 1 led to susceptible varieties of powdery mildew. Therefore, we inferred that tyramine, L-dopa, and 2-deoxy-ribose-1P were the key metabolites utilized by iron husk wheat against powdery mildew.

Data generated from a metabolomic analysis were assessed to determine the defense responses of iron-clad wheat to powdery mildew. Differences in tryptophan and pyrimidine metabolism and isoquinoline alkaloid biosynthesis in response to powdery mildew were analyzed. Important metabolites, such as tyramine, L-dopa, and 2-deoxy-ribose-1P, were implicated in the defense against powdery mildew. The metabolic network identified in this study provides new insights into powdery mildew resistance mechanisms and provides clues that could help to guide the development of new resistant wheat varieties.

Materials

A greenhouse cultivation experiment was conducted using 50 Yunnan iron-shelled wheat materials planted at Xundian Daheqiao Base of Yunnan Agricultural University in Kunming, China (25°31'3"N, 103°16'42"E). Powdery mildew infection occurred in the greenhouses during the booting stage. (Iron shell wheat 1) DiKe 1 was the susceptible variety, denoted as P, while Zhenkang Iron shell wheat (Yunmai 0030) was the resistant variety, denoted as N. In Yunmai 0608, the inverted second leaf of each plant was seriously infected, while the flag leaf was not. The inverted second leaf was denoted as G, and the flag leaf as K. There were 4 groups of samples (3 replicates), namely P-G, P-K, N-G and N-K (Figure 6). The cut samples were immediately placed in liquid nitrogen, stored at −80℃, and then sent to Wuhan Maiwei Metabolism Company for metabolism and transcription sequencing. All the experiments were performed in accordance with relevant guidelines and regulations

Targeted metabolome detection and analysis

Please refer to [36-42] for the detection and analysis methods of metabolomics.

Acknowledgements

We gratefully acknowledge the financial support of the Yunnan Province Yang Wuyun Expert Workstation. We would like to thank Editage (www.editage.cn) for English language editing and Wuhan MetWare Biotechnology Co., Ltd. (www.metware.cn) for metabolome analyses.

This work was Supported by the Yunnan Expert Workstation (202205AF150001).

Author contributions

X.Z., writing—original draft, methodology; T.H., writing—original draft, formal analysis; Q.W., conceptualization, writing—review and editing; Y.G., L.L., investigation;methodology, visualization; P.Z., collected field samples and prepared plant materials; J.L., formal analysis, investigation; H.X., formal analysis, investigation; C.Z., supervision; P.Q., supervision, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript.

Data availability statement: The datasets generated and/or analyzed during the current study are not publicly available due [Mining of this metabolome data is continuing] but are available from the corresponding author on reasonable request

Additional Information: The wheat experimental materials used in this study have been licensed for use

Supplementary Materials: he following supporting information can be downloaded at: www. Scientific Reports.com/xxx/s1.

Competing Interests: The authors declare no competing interests.

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Metabonomics analysis of Iron shell wheat (Triticum aestivum ssp. yunnanense King) reveals mechanisms of resistance against powdery mildew

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Abstract

Figures

Introduction

Results

Data quality control and qualitative and quantitative metabolite analysis

Analysis of metabolite differences among the combinations

K-means analysis

Differential metabolite enrichment analysis using the KEGG pathway

Discussion

Conclusion

Materials And Methods

Materials

Targeted metabolome detection and analysis

Declarations

References

Competing Interests

Supplementary Files

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