CN115097053B - Metabolic marker for identifying phytophthora sojae root rot disease inductive reactance condition and application thereof - Google Patents
Metabolic marker for identifying phytophthora sojae root rot disease inductive reactance condition and application thereof Download PDFInfo
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Abstract
The invention discloses a metabolic marker for identifying the induction resistance condition of phytophthora sojae and application thereof, belonging to the technical field of plant disease control. Through metabonomics detection, metabolic pathway enrichment analysis and other data analysis, metabolic markers which can be used for assisting in reducing the complexity of disease-resistant breeding work are excavated from a large number of metabolites, and the metabolic markers are daidzein, genistin, ferulic acid and phlorizin respectively. The metabolic markers can assist in screening disease-resistant soybean varieties.
Description
Technical Field
The invention relates to the technical field of plant disease control, in particular to a metabolic marker for identifying the induction resistance condition of phytophthora sojae and application thereof.
Background
Soybean is an important grain and commercial crop, and is currently the fifth main grain in China, and is an important strategic crop. At present, soybean production has many disease problems, for example, phytophthora sojae root rot caused by phytophthora sojae infection is an important soybean root disease, and serious threat is brought about by soybean production worldwide. The disease has extremely strong survivability and soil-borne characteristics due to pathogenic bacteria, once the disease occurs, the disease has extremely high epidemic speed, wide spreading surface, extremely serious harm and extremely difficult prevention and treatment. The use of disease resistant varieties is the most fundamentally most effective means of preventing phytophthora sojae root rot, and many sources of resistance have also been successfully identified at present. Resistant varieties have many advantages, such as: not only can avoid the large-scale occurrence of phytophthora sojae root rot, but also solves the problem of environmental pollution caused by using a large amount of bactericides. But the breeding work of traditional soybean disease-resistant varieties is complicated.
The metabonomics analysis needs to be established on the basis of group indexes, a metabolite sample with common properties or a small molecular metabolite sample of a certain class of organisms is researched, the small molecular metabolites with obvious differences in the samples are found through high-throughput analysis and comprehensive data monitoring and data processing processes, and then the integrated information modeling and system biological information are utilized to monitor or evaluate gene functions, so that the metabonomics can carry out systematic analysis and research on physiological and biochemical changes of plant organisms. The metabolome is a final metabolite collection after the biological process is finished under a certain condition, is one of the most similar phenotypes in various histology researches, and can directly and dynamically reflect the physiological and biochemical states of cells, so that specific biochemical pathways can be effectively detected and found, and physiological or pathological phenomena can be accurately explained. At present, the development of metabonomic detection technology is rapid, and the pathophysiological state of organisms can be judged by detecting Mass Spectrum (MS), chromatograph (HPLC, GC) and chromatograph-mass spectrum combined technical spectrogram of samples and combining a mode identification method to find out related biomarkers.
The metabolic markers are used for assisting the breeding of disease-resistant varieties, so that the complexity of the disease-resistant breeding work can be reduced, but the metabolic markers for identifying the condition of the root rot disease resistance of phytophthora sojae are rarely reported at present.
Disclosure of Invention
The invention aims to provide a metabolic marker for identifying the induction resistance condition of phytophthora sojae root rot and application thereof.
In order to achieve the above purpose, the invention adopts the following technical scheme:
in a first aspect of the invention, there is provided the use of a small molecule substance as set forth in at least one of (1) - (4) below as a metabolic marker for the identification of phytophthora sojae root rot inductive reactance:
(1) Daidzein;
(2) Genistin;
(3) Ferulic acid;
(4) Phlorizin.
In the application, the content of the small molecular substance is inversely related to the disease index of the phytophthora sojae root rot.
In a second aspect, the invention provides an application of the small molecular substance as a metabolic marker in soybean disease-resistant variety breeding, wherein the small molecular substance is at least one of the following (1) - (4):
(1) Daidzein;
(2) Genistin;
(3) Ferulic acid;
(4) Phlorizin.
In a third aspect of the invention, there is provided the use of a reagent for detecting a metabolic marker in the manufacture of a product for identifying the condition of phytophthora sojae root rot disease resistance;
the metabolic marker is a small molecule substance as described in any one of the following (1) to (4):
(1) Daidzein;
(2) Genistin;
(3) Ferulic acid;
(4) Phlorizin.
In the application, the reagent is a liquid chromatography-mass spectrometry detection reagent.
In the above application, preferably, the metabolic markers are ferulic acid and phlorizin.
In a fourth aspect of the present invention, there is provided a method for screening disease resistant minispecies from wild soybean varieties, comprising the steps of:
detecting the content of the metabolic markers in the wild soybean samples, comparing the content of the metabolic markers with the content of the metabolic markers in known disease-resistant soybean varieties and disease-resistant soybean varieties, and screening disease-resistant seeds according to the comparison result of the content of the metabolic markers.
Preferably, soybean hypocotyl is selected as the sample.
Preferably, wild soybeans with a higher metabolic marker content than the disease resistant soybean variety or higher than the disease resistant soybean variety are selected as disease resistant micro-seeds.
The invention has the beneficial effects that:
according to the invention, through metabonomics detection, metabolic pathway enrichment analysis and other data analysis, metabolic markers which can be used for assisting in reducing the complexity of disease-resistant breeding work are excavated from a large number of metabolites, and the metabolic markers can assist in screening disease-resistant varieties.
Drawings
Fig. 1: the potential key metabolic pathway of soybean phytophthora capsici at soybean variety Williams79 hypocotyl infection.
Fig. 2: the potential key metabolic pathway of soybean phytophthora capsici at soybean variety Williams82 hypocotyl infection.
Fig. 3: the potential key metabolic pathway of soybean phytophthora capsici at root infection of soybean variety Williams 79.
Fig. 4: the potential key metabolic pathway of soybean phytophthora root rot when soybean variety Williams82 root is infected.
Fig. 5: the target compounds were subjected to absolute quantification of targeted metabolome (left column is soybean variety Williams82, right column is Williams 79).
Fig. 6: and (5) carrying out targeted content detection on 25 parts of wild soybean varieties with unknown disease resistance.
Fig. 7: and verifying the disease resistance of the wild soybean variety with high content of the targeting substance.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
As mentioned above, the breeding work of traditional soybean disease-resistant varieties is complicated. Based on the method, the metabolic pathway enrichment condition of two disease-resistant varieties is analyzed by analyzing the disease-resistant varieties of soybeans of two Williams families, the high similarity of disease-resistant mechanisms among disease-resistant varieties is found, the high similarity of metabolite production is also found, and finally four resistance metabolic markers, namely daidzein, genistin, ferulic acid and phlorizin are selected. Then selecting a plurality of wild soybean varieties to perform preliminary targeted detection, and finally selecting soybean varieties with higher content to perform the next experiment, so as to verify whether the varieties have disease resistance or disease resistance. The inoculation experiment result shows that compared with the known infected Williams minispecies, the soybean varieties with higher content have certain disease resistance. Therefore, the metabolic marker has high-efficiency and practical effects on disease-resistant breeding and seed selection work, and the invention is provided.
In order to enable those skilled in the art to more clearly understand the technical solutions of the present application, the technical solutions of the present application will be described in detail below with reference to specific embodiments. If experimental details are not specified in the examples, the conditions are generally conventional or recommended by the reagent company; reagents, consumables, etc. used in the examples described below are commercially available unless otherwise specified.
Example 1: screening of metabolic markers
Source and collection of samples
The soybean material and phytophthora sojae used in the invention are all from the national key laboratory of crop biology of Shandong agricultural university. The public is available from the applicant for use in repeating the present invention.
The collecting method comprises the following steps: respectively taking Williams82, williams79 and Williams soybean materials, wherein Williams82 and Williams79 are disease-resistant varieties, and Williams is disease-sensitive varieties; cleaning soybean hypocotyls and roots thereof, keeping the roots intact and undamaged, placing the middle parts of the soybean hypocotyls of different varieties in an 8-connecting pipe, dripping diluted phytophthora sojae zoospore suspension on the surfaces of the hypocotyls at the placing positions, spreading 2-3 layers of dry paper towels on the roots, spraying water by using a watering can at regular intervals, and covering preservative films to preserve moisture; root treatment is to submerge the roots of different soybean varieties in zoospore suspension of phytophthora sojae of the same concentration. Taking materials at 1cm above and below the soybean hypocotyl inoculation part after 0,1, 4, 8 and 12 hours of inoculation, taking all materials at the root, freezing with liquid nitrogen, and storing in a refrigerator at-80 ℃ for detecting phytophthora sojae metabolome, wherein a soybean sample in a normal growth state after 0 hour of inoculation is a control sample.
(II) LC/MS analysis and data processing
1. Pretreatment of soybean material samples
After grinding the soybean hypocotyl and root samples, 6 biological replicates were set for each group, 100mg of each replicate was taken, and 1mL of extract methanol was added to the samples: acetonitrile: water (2:2:1, volume ratio), 4 ℃ ultrasonic 10min,13000prm centrifugal 5min, taking the supernatant to the centrifuge tube, put into the rotary evaporator to evaporate and concentrate, adding 100 mu L methanol to redissolve, before sample injection, filtering through 0.22 mu m filter membrane, and then loading.
2. Ultra-high liquid chromatography mass spectrometry
(1) Liquid chromatography
Chromatographic column: thermo HYPERSIL GOLD aQ C18 chromatography column (2.1X 100,1.9 μm); column temperature: 35 ℃; mobile phase: a: an aqueous solution containing 0.1% acetic acid (volume fraction), B: acetonitrile solution containing 0.1% acetic acid (volume fraction); elution gradient: 0-0.5min, a=90%; 0.5-7min, decreasing A to 0%;7-8.5min, a=0%; 8.6min, A is increased to 90%;8.6-10min, a=90%; sample injection volume: 3. Mu.L.
(2) Mass spectrometry conditions
Positive ion mode: spray voltage: 3.8kv; sheath gas: 40, a step of performing a; auxiliary gas: 10; ion transport tube temperature: 350 ℃. Resolution ratio: 17500; microcomputerized number: 1, a step of; AGC target:2e5; normalized collision energy: 50.
negative ion mode: spray voltage: 2.9kv; sheath gas: 40, a step of performing a; auxiliary gas: 0; ion transport tube temperature: 350 ℃. Resolution ratio: 17500; microcomputerized number: 1, a step of; AGC target:2e5; normalized collision energy: 50.
3. data processing, analysis and screening of markers
(1) Metabolome raw data extraction and analysis
Using high performance liquid chromatography and Q exact TM The original data obtained by detection of the combined quadrupole Orbitrap mass spectrometer is subjected to peak extraction, peak alignment, normalization, missing data filling, noise reduction treatment and the like according to a set experimental method by Compound Discoverer software to obtain positive ion phase and negative ion phase variables meeting experimental requirements: the mass-to-charge ratio (m/z), retention time (retention time), peak area (group area), predicted metabolite name (formula), the mass can be characterized by matching the scanned secondary mass spectrum of the metabolite with the secondary spectrum database, and the relative quantitative analysis of the metabolite can be performed by scanning the peak area of the metabolite.
The obtained product is exported to EXCEL for further analysis, and the main component analysis (PCA), partial least square method-discriminant analysis (PLS-DA) and orthogonal partial least square method-discriminant analysis (OPLS-DA) are adopted to respectively carry out credibility analysis and inspection on the mass spectrum data after positive ion phase and negative ion phase variables meeting the requirements are determined, and the difference of the secondary metabolites to be tested is analyzed according to the VIP value (threshold value > 1) of the OPLS-DA model, the P value (threshold value < 0.05) of student t test of the peak areas of the metabolites among different soybean varieties and the area fold change of the obtained metabolites.
(2) Screening of markers
By utilizing Compound Discoverer software custom library searching flow, we search and compare the following databases: software self-contained databases including 6549 flavonoids and 4400 endogenous metabolites; araCyc, bioCyc, KEGG, plantCyc and lipidMAPS open source database; mzVault self-built database; mzCloud secondary spectrogram database. By searching these databases and matching the secondary mass spectrometry information on the metabolites, the resulting resistant differential metabolites were sorted according to the screening conditions of Log2Fold Change >1 or < -1 and P-value <0.05 as potential biomarkers, and the results are shown in tables 1 to 4.
Table 1: williams82 hypocotyl potential biomarker
Table 2: williams79 hypocotyl potential biomarker
Table 3: williams82 root potential biomarker
Table 4: williams79 root potential biomarker
After potential biomarkers with KEGG ID in hypocotyls and roots of two disease-resistant varieties are arranged, metabolic pathway enrichment analysis is carried out in a Lithospermum biological cloud platform (www.omicstudio.cn), metabolic pathway enrichment analysis diagrams (figures 1-4) of differential metabolites of two near isogenic disease-resistant varieties inoculated with phytophthora sojae are produced, and markers (daidzein, genistin, ferulic acid and phlorizin) in both soybean varieties Williams82 and Williams79 are selected as resistance markers for further experimental study.
Based on the screening of non-targeted metabolome, we initially mapped to some compounds, and next we used peak areas to absolute quantitate the targeted metabolome for the compounds of interest (daidzein, genistin, ferulic acid, phlorizin), as shown in figure 5.
By comparing the content changes of the two disease-resistant micro-species, the content of the compounds is found to increase along with the increase of the inoculation time, so that the daidzein, genistin, ferulic acid and phlorizin are primarily estimated to be used as metabolic markers for the next research.
Example 2: targeted content detection of metabolic markers
In order to verify the content of the metabolic marker estimated in the preliminary step in the example 1 in other soybean varieties, we selected a plurality of types of hypocotyls of wild soybean varieties with unknown phytophthora sojae resistance to disease for targeted content detection, and the soybean varieties to be tested are all conventional experimental varieties with good germination rate and stable growth, and the total amount of the soybean varieties is 25 parts.
Based on the results of the absolute contents of the target substances (fig. 6), the study selects the first three species with good germination rate for disease resistance verification. Whether these species are resistant to disease or not is verified by the method of hypocotyl inoculation.
Experiments show that a large number of lesions appear in the known infected variety Williams after 12 hours after hypocotyl inoculation, and a small number of lesions appear in the wild soybean variety screened for disease resistance verification and can still grow normally; after 24 hours of hypocotyl inoculation, the susceptible variety Williams showed a pronounced constriction wilt, while the wild soybean variety remained slightly spotted and still grew normally (FIG. 7).
Therefore, the small species with high content of the metabolic markers (daidzein, genistin, ferulic acid and phlorizin) have better disease resistance.
Further, the correlation between the above 4 metabolic markers and the soybean root rot disease index was analyzed, and the severity classification criteria of soybean root rot disease are shown in Table 5.
Table 5: severity classification standard for soybean root rot
And as a result of SPSS analysis, it was found that there was a significant negative correlation between the contents of only two substances, ferulic acid and phlorizin, and the disease index (table 6). Therefore, ferulic acid and phlorizin are more suitable as metabolic markers for identifying the induction of phytophthora sojae root rot. Table 6:
* Represents P < 0.01
* Representing P <0.05
In summary, analysis of the metabonomics data of the hypocotyl and root samples of the two disease-resistant varieties after inoculation with phytophthora sojae shows that the two disease-resistant varieties are highly similar in metabolite production and metabolic pathway enrichment analysis, and that some metabolites which increase with the growth of inoculation time exist, and it is presumed that these metabolites and metabolic pathways are involved in disease resistance of soybean to phytophthora sojae, and that the soybean of the two disease-resistant varieties are similar in disease resistance mechanism.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (5)
1. The use of at least one small molecule substance as a metabolic marker for the identification of phytophthora sojae root rot inductive reactance conditions as follows (1) - (2):
(1) Ferulic acid;
(2) Phlorizin.
2. The use according to claim 1, wherein the content of the small molecule substance is inversely related to the index of the disease state of phytophthora sojae.
3. The application of at least one small molecular substance as metabolic marker in soybean disease-resistant variety breeding:
(1) Ferulic acid;
(2) Phlorizin.
4. Application of a reagent for detecting a metabolic marker in the preparation of a product for identifying the condition of phytophthora sojae root rot resistance;
the metabolic marker is a small molecular substance as shown in any one of the following (1) - (2):
(1) Ferulic acid;
(2) Phlorizin.
5. The use according to claim 4, wherein the reagent is a liquid chromatography-mass spectrometry detection reagent.
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