A composite microbial community for controlling bacterial wilt of tomato, its preparation method and application

Abstract

This invention discloses a method for constructing a synthetic microbial community with broad-spectrum adaptability using various machine learning models based on global public data. The constructed and simplified synthetic microbial community consists of three bacterial strains: *Pseudomonas putida* YDTA3, *Pseudomonas putida* PPF1, and *Stenotrophomonas* sp. Syn-C. Compared to single bacteria, the synthetic microbial community constructed in this invention exhibits stronger environmental adaptability, and the strains used to construct the synthetic community are irreplaceable and unique. Adding the synthetic microbial community to the rhizosphere of continuously cropped tomatoes inhibits the pathogenicity of pathogens, thereby significantly reducing the incidence of bacterial wilt in continuously cropped tomatoes.

Description

Technical Field

[0001] This invention belongs to the field of biotechnology for constructing complex functional microbial communities from microbial strains, and relates to a complex microbial community for controlling bacterial wilt of tomato, its preparation method, and its application. Background Technology

[0002] Soil-borne diseases severely plague my country's agricultural production, especially cash crops grown under intensive agriculture. Year-round monoculture often leads to the deterioration of soil microbial communities, ultimately resulting in outbreaks of soil-borne diseases. For a long time, chemical pesticides have been widely used to control soil-borne diseases, such as soil fumigation. However, fumigation can cause adverse effects such as soil compaction, pesticide residues, and damage to the rhizosphere ecosystem, which are detrimental to sustainable development and environmental protection. Therefore, how to regulate the microbial community while maintaining soil ecological balance to achieve crop protection has become an urgent problem to be solved.

[0003] The rhizosphere, a highly dynamic interface between roots and soil, is rich in a variety of potentially beneficial microorganisms that exhibit a range of biological activities crucial to plant growth and health. Over the past few decades, many beneficial microorganisms from the rhizosphere have been used for biocontrol in agricultural production. However, the control efficiency of single microbial strains is often limited by their poor colonization in plants and the rhizosphere, resulting in inconsistent biocontrol effects in the field. Synthetic microbial communities constructed by utilizing synergistic effects among strains enhance the robustness and stability of the community, enabling better adaptation to environmental changes and further improving rhizosphere immunity.

[0004] With the rapid development of high-throughput sequencing technology and bioinformatics, researchers can use sequencing data combined with phenotypic results to simulate and predict the interactions and regulatory mechanisms between microorganisms, and design synthetic microbial communities with specific functions based on this. This method is known as a "bottom-up" approach. However, simplifying and standardizing the massive amounts of rhizosphere microbiome data to select suitable strains for synthetic microbial community design remains challenging. Current common isolation and screening criteria rely on differential analysis or microbial network analysis to select relevant microorganisms. However, varying experimental conditions across studies often obscure the true characteristics of microbial communities, sometimes leading to unreliable or inconsistent conclusions. Therefore, data integration is needed to uncover microbial community characteristics and guide synthetic microbial community design, thereby more accurately reflecting the natural microbial community and its ecological evolutionary dynamics. Summary of the Invention

[0005] The purpose of this invention is to propose a design method for synthetic microbial communities and, based on this design principle, to construct a highly efficient and stable synthetic microbial community for controlling bacterial wilt of tomato. After adding the synthetic microbial community, its colonization performance in the rhizosphere is excellent, the pathogenicity of soil-borne bacterial wilt fungus is weakened, the activity of plant defensive enzymes is increased, and the incidence of plant disease is significantly reduced.

[0006] To achieve the above objectives, the technical solution provided by the present invention is as follows:

[0007] The first objective of this invention is to provide a complex microbial community for controlling bacterial wilt of tomato, the complex microbial community being composed of *Pseudomonas putida* YDTA3, *Pseudomonas putida* PPF1, and *Stenotrophomonas* sp. Syn-C.

[0008] The aforementioned *Pseudomonas putida* YDTA3 is deposited at the China Center for Type Culture Collection (CCTCC) on July 3, 2023, with accession number CCTCC NO: M 20231178.

[0009] The aforementioned *Pseudomonas putida* PPF1 is deposited at the China Center for Type Culture Collection (CCTCC) on January 17, 2024, with accession number CCTCC NO: M 2024130.

[0010] The oligotrophomonas sp. Syn-C is deposited at the China Center for Type Culture Collection (CCTCC) on March 28, 2023, with accession number CCTCC NO: M 2023426.

[0011] Furthermore, the composite microbial community contains a mixture of Pseudomonas putida YDTA3, Pseudomonas putida PPF1, and Stenotrophomonas sp. Syn-C in equal proportions.

[0012] Furthermore, the bacterial wilt of tomatoes is caused by the pathogenic bacterium Ralstonia solanacearum.

[0013] A second objective of this invention is to provide a method for constructing the aforementioned complex microbial community, the method comprising the following steps:

[0014] (1) Soil sequencing data related to bacterial wilt were downloaded from public data platforms, and multiple machine learning classification models were constructed for healthy and diseased samples. Key microorganisms were screened by combining the important features of multiple machine learning models.

[0015] (2) Based on the abundance differences of characteristic microorganisms in disease and health in the classification model, obtain the classification information of microorganisms that are significantly enriched in healthy samples;

[0016] (3) Screen bacteria in the bacterial library whose sequences match the bacterial sequences that are significantly enriched in the healthy sample, and mix them in equal amounts to obtain the synthetic bacterial community S1;

[0017] (4) The synthetic microbial community S1 was inoculated into the plant roots, and the successfully colonized strains were further screened. The single strains were mixed to construct the synthetic microbial community S2.

[0018] (5) The control effect of the synthetic microbial community S2 on bacterial wilt of tomato was determined, and the aforementioned complex microbial community was obtained.

[0019] Furthermore, (1) the machine learning model is Random Forest, Xgboost, SVM, DecisionTree, GLM, Naive Bayes, Logistic Regression, KNN.

[0020] The third objective of this invention is to provide the application of the aforementioned complex microbial community in the control of bacterial wilt in tomatoes.

[0021] Compared with the prior art, the beneficial effects of this invention are as follows:

[0022] This study collected global soil sequencing data related to bacterial wilt. Based on the common features and differential analysis results of eight machine learning models (Random Forest, Xgboost, SVM, Decision Tree, GLM, Naive Bayes, Logistic Regression, and KNN), and after pure bacterial isolation and matching with existing strains, 10 bacteria with high abundance in healthy samples were obtained, and the bacterial concentration was adjusted to 1×10⁻⁶. 7 The CFU / mL were mixed in equal proportions to obtain the synthetic bacterial community S1.

[0023] The synthetic bacterial community S1 exhibited good disease resistance. Sequencing of the full-length 16S rRNA genome using third-generation sequencing revealed three strains within the S1 synthetic community that ultimately colonized the tomato root system efficiently: *Pseudomonas putida* YDTA3, *Pseudomonas putida* PPF1, and *Stenotrophomonas* sp. Syn-C. Mixing these three strains in equal amounts yielded the final synthetic bacterial community S2.

[0024] To further verify the irreplaceability of the bacterial community combinations, a random removal experiment was conducted, and bacterial communities S2-Y, S2-P, and S2-S were constructed after randomly removing single bacteria. To further verify the uniqueness of the bacterial community combinations, strains with the same taxonomic information as those in S2 were randomly selected to construct synthetic bacterial communities S3, S4, and S5, respectively.

[0025] Compared to the three single strains, the synthetic bacterial community S2 described in this invention colonized plant roots more effectively. After randomly removing the single strains, the total colonization of communities S2-Y, S2-P, and S2-S decreased, and biofilm production was reduced. The randomly constructed synthetic bacterial communities S3, S4, and S5 did not exhibit significant synergistic effects compared to the single strains.

[0026] Compared with three single strains and the bacterial communities S2-Y, S2-P, and S2-S after randomly removing single strains, the synthetic bacterial community S2 described in this invention is more effective in reducing the pathogenicity of *Ralstonia solanacearum*. The randomly constructed synthetic bacterial communities S3, S4, and S5 cannot effectively inhibit the pathogenicity of *Ralstonia solanacearum*.

[0027] Compared to three single bacterial strains and bacterial communities S2-Y, S2-P, and S2-S after random removal of single bacteria, the synthetic bacterial community S2 described in this invention more effectively activates the plant defense system. The randomly constructed synthetic bacterial communities S3, S4, and S5 did not activate the plant defense system.

[0028] Compared with three single bacterial strains and bacterial colonies S2-Y, S2-P, and S2-S after random removal of single bacterial strains, the synthetic bacterial colony S2 described in this invention is more effective in preventing bacterial wilt in tomatoes. The incidence of bacterial wilt in tomatoes with the addition of randomly constructed synthetic bacterial colonies S3, S4, and S5 is significantly higher than that with S2.

[0029] The construction method provided by this invention has universality, effectively improves the screening accuracy of synthetic microbial communities, and can provide a theoretical basis for the construction of synthetic microbial communities in fields such as environmental governance and human health. Attached Figure Description

[0030] Figure 1 Accuracy of machine learning classification models;

[0031] Figure 2Ranking of the importance of characteristic microorganisms in machine learning models; relative abundance of specific microorganisms in healthy and diseased samples; construction of 10 strains of synthetic microbial community S1;

[0032] Figure 3 The control effect of synthetic microbial community S1 on bacterial wilt of tomato;

[0033] Figure 4 A strain of the synthetic microbial community S1 was successfully colonized in the rhizosphere of tomato.

[0034] Figure 5 The colonization numbers of single bacterial strains, synthetic bacterial groups S2, S2-Y, S2-P, S2-S, and randomly synthesized bacterial groups S3, S4, and S5 in the rhizosphere of tomato;

[0035] Figure 6 Biofilm yields for single strains, synthetic bacterial groups S2, S2-Y, S2-P, S2-S, and randomly synthetic bacterial groups S3, S4, and S5;

[0036] Figure 7 The attenuating effects of single strains, synthetic bacterial groups S2, S2-Y, S2-P, S2-S, and randomly synthesized bacterial groups S3, S4, and S5 on Ralstonia solanacearum were investigated.

[0037] Figure 8 The effects of single bacterial strains, synthetic bacterial groups S2, S2-Y, S2-P, S2-S, and randomly synthesized bacterial groups S3, S4, and S5 on inducing reactive oxygen species in tomato roots were studied.

[0038] Figure 9 The incidence of bacterial wilt was observed one month after applying single strains, synthetic bacterial groups S2, S2-Y, S2-P, S2-S, and randomly synthesized bacterial groups S3, S4, and S5 to the roots of continuously cropped tomatoes.

[0039] Biological Preservation Instructions:

[0040] Biomaterials:

[0041] *Pseudomonas putida* YDTA3; Classification and nomenclature: *Pseudomonas putida* (Latin name: *Pseudomonas putida*); Deposited at the China Center for Type Culture Collection (CCTCC), July 3, 2023, China, China Center for Type Culture Collection, Wuhan University, Wuhan, China, CCTCC NO: M20231178;

[0042] Pseudomonas putida PPF1; Classification and nomenclature: Pseudomonas putida; Deposited at the China Center for Type Culture Collection (CCTCC) on January 17, 2024, at Wuhan University, Wuhan, China, with accession number CCTCC NO: M 2024130.

[0043] Stenotrophomonas sp. Syn-C; Classification and nomenclature: Stenotrophomonas sp.; Deposited at the China Center for Type Culture Collection (CCTCC), March 28, 2023, China, China Center for Type Culture Collection, Wuhan University, Wuhan, China, CCTCC NO: M2023426. Detailed Implementation

[0044] The present invention will be further explained below with reference to the embodiments, but the embodiments do not limit the present invention in any way.

[0045] Culture media and chemical reagents involved in the examples:

[0046] MM Inorganic Salt Culture Medium: Sodium chloride 0.15g, magnesium sulfate heptahydrate 0.5g, calcium chloride hexahydrate 0.1g, ferrous sulfate heptahydrate 0.0025g, ammonium sulfate 0.5g.

[0047] Inorganic salt solution: Sodium chloride 0.015g, magnesium sulfate heptahydrate 0.05g, calcium chloride hexahydrate 0.01g, ferrous sulfate heptahydrate 0.00025g, ammonium sulfate 0.05g.

[0048] Nutrient agar medium (NB): 3.0g beef extract, 5.0g peptone, 2.5g glucose, pH 7.0.

[0049] SMSA medium: 16g agar, 10g peptone, 1g acid-hydrolyzed casein, 5mL glycerol, 10mL 1% polymyxin, 0.5mL 1% crystal violet, 5mL 1% TTC, 2.5mL 1% bacitracin, 0.5mL penicillin, 10mL 1% chloramphenicol, 10mL 1% actinomycin.

[0050] Example 1. Analysis of global bacterial wilt-associated soil microbial communities

[0051] 1700 datasets were downloaded by searching the keywords "Bacterial wilt community" and "Ralstoniasolanacearum community" on Google Scholar, including 1130 healthy samples and 570 diseased samples. Classification models were built for the healthy and diseased samples using R (v 4.1), and differential analysis was performed.

[0052] The results are as follows Figure 1 As shown, eight common machine learning methods were tested, including Random Forest, Xgboost, SVM, Decision Tree, GLM, NaiveBayes, Logistic Regression, and KNN. A total of 49 feature OTUs were identified by combining the common features of multiple models. Differential analysis revealed that 15 OTUs had relatively high abundance in healthy samples, such as Pseudomonas, Sphingomonas, Nocardioides, Stenotrophomonas, and Devosia e, etc. Figure 2 ).

[0053] Example 2. Method for constructing synthetic bacterial communities

[0054] 1. Preliminary Construction of Synthetic Microbial Community

[0055] 1.1 Strain screening

[0056] Healthy tomato rhizosphere soil samples collected from previously continuously cropped soils in the laboratory were mixed with sterile water at a ratio of 1:9 and vortexed thoroughly. One mL of the liquid was taken and evenly spread onto nutrient agar solid medium using the serial dilution plating method, and incubated upside down for 12-24 hours. Single colonies were picked and re-inoculated into nutrient agar liquid medium for purification culture and preservation using the glycerol method.

[0057] Strains exhibiting good growth during purification were selected as research subjects, and their full-length sequences were determined using first-generation sequencing. Sequence similarity was compared with those of the aforementioned characteristic microorganisms, and the strain with the highest similarity was selected as the target strain. A total of 10 strains enriched in healthy samples were screened: *Nocardioides lentus*, *Nocardioides deserti*, *Nocardioides* sp., *Klebsiella* sp., *Chryseobacterium* sp., *Devosiariboflavina*, *Enterobacter* sp., *Lysobacter niastensis*, *Aeromicrobium* sp., and *Stenotrophomonas* sp. The concentration of the obtained 10 bacterial cultures was adjusted to 1 × 10⁻⁶. 7 CFU / mL, after being mixed in equal volumes, yielded the synthetic bacterial community S1.

[0058] 1.2 Biocontrol effect of synthetic microbial community S1 on bacterial wilt of tomato

[0059] Tomato seeds were soaked in 100 mL of 0.75% NaClO solution for 30 minutes, washed five times with sterile water, and cultured in sterile Petri dishes at 25°C for 3 days. 150 g of soil was placed in a tissue culture container and autoclaved three times to inactivate all soil microorganisms. After sterilization, colony growth was examined on NA medium to assess the sterilization effect. Five-day-old tomato seedlings grown under sterile conditions were transferred to sterile soil in tissue culture containers. When the plants reached approximately 4 cm in height, 20 mL of a synthetic microbial culture (S1) solution was added. An equal volume of deionized water was added to the control treatment. All bags were inoculated with the pathogen *Ralstonia solanacearum*. Plant disease incidence was assessed one month after inoculation.

[0060] The results are as follows Figure 3 As shown, the disease incidence rate of the control tomato was 72%, while that of the plants inoculated with S1 was 20%, which significantly reduced the disease incidence rate compared to the control.

[0061] 2. Optimization of Synthetic Microbial Community

[0062] The aforementioned synthetic bacterial group S1 exhibits good disease resistance. To determine which bacteria successfully colonized the tomato rhizosphere and functioned under greenhouse conditions through plant-microbe interactions, S1 was inoculated into sterile tomato seedlings. Plant samples were collected 30 days later, DNA was extracted, and full-length sequencing of 16S rRNA amplicon was performed on the PacBio platform.

[0063] Full-length sequencing results ( Figure 4The results showed that of the 10 strains of the S1 synthetic microbial community, only 3 strains successfully colonized the tomato rhizosphere: YDTA3, PPF1, and Syn-C. These 3 strains were mixed in equal proportions to obtain the final synthetic microbial community S2.

[0064] Example 3. Synergistic effect and efficacy verification among strains of synthetic bacterial community S2

[0065] The strains named YDTA3, PPF1, and Syn-C screened in Example 2, as well as the strains with the same taxonomic information previously preserved in the laboratory, namely Pseudomonas1 (Pseudomonas fluorescens), Pseudomonas2 (Pseudomonas stutzeri), Pseudomonas3 (Pseudomonas paucimobilis), Pseudomonas4 (Pseudomonas fluorescens), Pseudomonas5 (Pseudomonas putida), Pseudomonas6 (Pseudomonas putida), Stenotrophomonas1 (Stenotrophomonas maltophilia), Stenotrophomonas2 (Stenotrophomonas rhizophila), and Stenotrophomonas3 (Stenotrophomonas maltophilia), were taken out of the -80°C freezer and allowed to thaw slightly. Then, a disposable inoculation loop was used to streak the bacterial culture onto NB solid medium, and the medium was incubated overnight at 28°C with the medium inverted. Select uncontaminated plates with uniform colony appearance and inoculate single colonies into NB liquid medium. Incubate at 180 rpm in a constant temperature (28°C) shaker until the absorbance (OD 600) reaches 1.0. Centrifuge the bacterial culture at 10000g for 5 min, discard the supernatant, and wash the cells three times with sterile inorganic salt solution. Then, concentrate or dilute the bacterial culture to 1×10⁻⁶. 7 CFU / mL.

[0066] Synthetic bacterial community S2 was constructed by mixing three biocontrol bacteria (YDTA3, PPF1, and Syn-C) in equal proportions.

[0067] S2-Y is composed of a mixture of PPF1 and Syn-C in equal proportions.

[0068] S2-P is composed of a mixture of YDTA3 and Syn-C in equal proportions.

[0069] S2-S is composed of a mixture of YDTA3 and PPF1 in equal proportions.

[0070] The randomly synthesized bacterial community S3 is composed of a mixture of Pseudomonas1, Pseudomonas2, and Stenotrophomonas1 in equal proportions.

[0071] The randomly synthesized bacterial community S4 is composed of a mixture of Pseudomonas3, Pseudomonas4, and Stenotrophomonas2 in equal proportions.

[0072] The randomly synthesized bacterial community S4 was composed of a mixture of Pseudomonas5, Pseudomonas6, and Stenotrophomonas3 in equal proportions. Experiments were conducted on single strains, rhizosphere colonization of the synthesized bacterial community, and biofilm production.

[0073] The cultivation of sterile tomato seedlings was as described in section 1.2 of Example 2. When the plant height reached approximately 4 cm, 20 ml of bacterial suspensions containing a single bacterial strain, synthetic bacterial groups S2, S2-Y, S2-P, S2-S, and random synthetic bacterial groups S3, S4, and S5 were added, along with an equal volume of deionized water in the control container. Four weeks after inoculation, rhizosphere soil samples were collected from the sterile tomatoes, and the number of bacteria in the rhizosphere soil was counted using dilution plating and plate counting methods. All plates were incubated at 28°C for 48 hours (Shanghai Ximo Medical Instrument Manufacturing Co., Ltd., China).

[0074] The results show that ( Figure 5 When the four strains were inoculated individually, the rhizosphere colonization numbers of YDTA3, PPF1, and Syn-C were 5.4 × 10⁻⁶. 4 5.7×10 5 and 5.8×10 5 CFU / g. The colonization rate of the synthetic bacterial community S2 was 6.4 × 10⁻⁶. 6 The rhizosphere colonization numbers of S2-Y, S2-P, and S2-S were 6.4 × 10⁻⁶ CFU / g, respectively. 6 7.4×10 5 and 6.0×10 6 CFU / g. Compared to single strains, this significantly increased the total number of rhizosphere bacteria colonies. The rhizosphere colonization numbers of randomly synthesized bacterial communities S3, S4, and S5 were 3.5 × 10⁻⁶. 4 4.0×10 4 4.5×10 3 The CFU / g was significantly lower than that of the synthetic bacterial community S2 and the colonization rate of a single strain.

[0075] Biofilm yield was measured after the strains were shaken at 28℃ and 180 rpm for 24 hours. The results showed that the biofilm yield of YDTA3 and PPF1 was less than 0.02 g, while that of Syn-C was 0.04 g. The biofilm yields of the synthetic colonies S2-Y, S2-P, and S2-S (without a single strain) were 0.02, 0.04, and 0.01 g, respectively. The synthetic colony S2, constructed from three strains, had the highest biofilm yield of 0.06 g. The biofilm yields of the randomly constructed synthetic colonies S3, S4, and S5 were all less than 0.02 g. Figure 6 ).

[0076] 2. Attenuating effects of single strains and synthetic flora on Ralstonia solanacearum:

[0077] Single colonies were incubated on NB medium for 24 h and resuspended in sterile water after centrifugation (15 min, 5000 g). One mL of bacterial suspension from a single strain or synthetic population was mixed with an equal volume of bacterial suspension from *Ralstonia solanacearum*, with sterile water serving as a control. Each treatment was repeated three times and incubated at 28 °C for 48 h in a constant temperature incubator (CIMO Medical Devices Manufacturing Co., Ltd., Shanghai, China), followed by colony counting using SMSA plates. Ten colonies from each sample were selected to calculate their attenuation index, and the average value was determined.

[0078] Weakening index = diameter of red spot on a single Ralstonia solanacearum colony / total diameter of a single Ralstonia solanacearum colony

[0079] Strains with a weakening index <0.60 are highly pathogenic, strains with a weakening index >0.80 are non-pathogenic, and the pathogenicity of strains with a weakening index between 0.60 and 0.80 is uncertain.

[0080] The results are as follows Figure 7 As shown, YDTA3, PPF1, Syn-C, S2-Y, S2-P, and S2-S all exhibited certain attenuation effects on *Ralstonia solanacearum*. The *Ralstonia solanacearum* strain co-cultured with the synthetic bacterial group S2 showed an attenuation index of 0.85, classifying it as a weakly pathogenic strain. Compared to YDTA3, PPF1, Syn-C, S2-Y, S2-P, and S2-S, the *Ralstonia solanacearum* strain showed a significant advantage in attenuation index. Furthermore, the attenuation effect caused by the addition of single strains varied considerably and was unstable, while the attenuation effect of the synthetic bacterial group S2 on *Ralstonia solanacearum* was very stable. The randomly constructed synthetic bacterial groups S3, S4, and S5 showed no significant attenuation effect on *Ralstonia solanacearum*.

[0081] 3. Single strain and synthetic microbial community induce plant resistance:

[0082] Example 2, section 1.2, describes the cultivation of sterile tomato seedlings. When the plant height reached approximately 4 cm, 20 ml of a single bacterial strain and a synthetic bacterial culture solution were added, with an equal volume of deionized water added to the control group. Plant root samples were collected at 0, 1, 3, 6, 9, and 22 hours after inoculation. After washing with PBS, 50 mg of the sample was weighed and added to 500 μL of homogenization buffer. The sample was then homogenized thoroughly and rapidly using a homogenizer. Centrifuged at 100 × g at 4°C for 5 minutes, and the supernatant was collected. 190 μL of the homogenized supernatant and 10 μL of O11 probe were added to a 96-well plate, and the mixture was thoroughly mixed using a pipette. The plate was incubated at 37°C in the dark for 20–30 minutes. The plate was then placed in a microplate reader, and the fluorescence intensity was detected at an excitation wavelength of 488 nm and an emission wavelength of 530 nm.

[0083] The results are as follows Figure 8 As shown, YDTA3, S2-Y, S3, and S4 had no inducing effect on reactive oxygen species (ROS) in tomato roots, while synthetic bacteria S2, S5, S2-P, S2-S, PPF1, and Syn-C all induced an increase in ROS content in tomato roots. ROS production peaked at 3 hours, then gradually decreased, returning to initial levels at 22 hours. The ROS induced by synthetic bacteria S2 was significantly higher than that induced by PPF1, S5, S2-P, S2-S, and Syn-C, reaching a maximum of 5e+07.

[0084] 4. Application of single strain and synthetic microbial community control in continuously cropped tomatoes

[0085] The cultivation of tomato plants and the preparation of YDTA3, PPF1, Syn-C, and synthetic microbial communities S2, S2-Y, S2-P, S2-S, S3, S4, and S5 were as described previously. The prepared biocontrol bacterial solution was applied to the roots of the plants at a volume of 10 mL per seedling, once a week, with normal watering and insecticide spraying at other times. After one month, disease incidence was observed and the incidence rate was calculated. Each treatment consisted of 30 tomato seedlings, with 4 replicates. Incidence rate (%) = number of diseased plants / total number of plants × 100%.

[0086] Tomato disease incidence rate as follows Figure 9 As shown, the disease incidence in tomatoes under continuous cropping conditions was significantly improved, indicating that biocontrol bacteria have a significant effect on controlling bacterial wilt in continuously cropped tomatoes. YDTA3, PPF1, Syn-C, S2-Y, S2-P, and S2-S all reduced the incidence to some extent. S3, S4, and S5 showed no significant control effect. The synthetic microbial community S2 showed a significant advantage in control compared to other combinations of single strains and genus substitutions, indicating that the combination of S2 could exert a synergistic effect and more effectively control the outbreak of the disease, reducing the incidence by 40% compared to the control.

[0087] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A complex microbial consortium for the prevention and control of tomato bacterial wilt, characterized by, The complex microbial community consists of *Pseudomonas putida* (… Pseudomonas putida YDTA3, Pseudomonas putida ( Pseudomonas putida PPF1, Oligotrophomonas ( Stenotrophomonas (sp.) Syn-C composition; The Pseudomonas putida YDTA3 is preserved in the China Center for Type Culture Collection, and the preservation date is July 3, 2023, and the preservation number is CCTCC NO: M 20231178. The Pseudomonas putida PPF1 is preserved in the China Center for Type Culture Collection, and the preservation date is January 17, 2024, and the preservation number is CCTCC NO: M 2024130. The Stenotrophomonas Syn-C is preserved in the China Center for Type Culture Collection, and the preservation date is March 28, 2023, and the preservation number is CCTCC NO: M 2023426.

2. The complex microbial consortium of claim 1, wherein, The Pseudomonas putida YDTA3, the Pseudomonas putida PPF1, and the Stenotrophomonas Syn-C are mixed in equal proportions in the complex microbial flora.

3. The complex microbial consortium of claim 1, wherein, The tomato bacterial wilt is caused by the pathogenic bacteria Ralstonia solanacearum.

4. The complex microbial flora of claim 1 is used for preventing and controlling the tomato bacterial wilt.

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