Optimized fermentation of Myxococcus fulvus WCH05 enhances biocontrol of pear fire blight in the field

Abstract

Myxococcus fulvus WCH05, isolated from desert soil in Manas County, Xinjiang, China, exhibits strong predatory activity against Erwinia amylovora and has potential for biocontrol of pear fire blight. To further explore its biocontrol potential and evaluate its efficacy in pear orchards, this study optimized the fermentation conditions of strain WCH05, targeting increased cell dry weight. A combination of single factor experiments, and response surface methodology (RSM) was employed to optimize the fermentation medium (carbon source, nitrogen source, and inorganic salt) and fermentation parameters (temperature, pH, shaking speed, working volume, and inoculum size). The biocontrol efficacy of strain WCH05 against pear fire blight was subsequently evaluated in potted Pyrus betulifolia seedlings under greenhouse conditions and in pear orchards over two consecutive years. The optimal fermentation conditions were determined as follows: soluble starch 8.0 g/L, yeast extract 4.0 g/L, MgSO₄ 1.2 g/L, initial pH 7.0, working volume 40% (100 mL/250 mL), agitation speed 200 r/min, incubation temperature 30 ℃, inoculum size 7%, and incubation time 72 h. Under these optimized conditions, the cell dry weight reached 3.25 g/L, a 2.5-fold increase compared to the unoptimized condition (1.30 g/L). In greenhouse trials, application of the WCH05 fermentation broth significantly reduced shoot blight incidence (P < 0.05), achieving protective efficacy of 86.2% (7 days post-inoculation, dpi) and 82.6% (14 dpi), which were superior to the efficacy achieved with the unoptimized broth. In field trials conducted in Korla City, Xinjiang, in 2023, the control efficacy against pear fire blight exceeded 81.5%. In 2024, field trials conducted in Korla City and Zhangye City, Gansu Province, showed control efficacies ranging from 81.0% to 90.9% and 82.5% to 89.7%, respectively. Notably, strain WCH05 consistently exhibited higher control efficacy than the antibiotic Kasugamycin in both years of field trials.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-026-04778-2.

Introduction

Pear fire blight, caused by the bacterium Erwinia amylovora, is a devastating disease affecting pome fruit trees, including fragrant pear, apple, hawthorn, and quince. E. amylovora infects blossoms, serving as a primary inoculum source for the spread of the pathogen to leaves, shoots, and young fruits. Pruning wounds also provide entry points for infection. Once established, the pathogen can persist within the host plant, leading to rapid spread and extremely challenging control and eradication, resulting in significant economic losses [1]. In China, pear fire blight was first reported in 2015 on apple trees in Huocheng County, Yili Prefecture, Xinjiang Uygur Autonomous Region [2]. Subsequently, large-scale outbreaks occurred in fragrant pear orchards in Korla City, Xinjiang, during 2017–2018, causing substantial economic damage [2]. The disease continues to spread, currently affecting 58 counties and districts across Xinjiang autonomous region and Gansu province, posing a serious threat to China’s fruit industry.

Current management strategies for pear fire blight include quarantine measures, pruning of infected plant tissues, chemical control, biological control, and developing resistant cultivars [3, 4]. However, commercially available fire blight-resistant fruit tree varieties are limited, and the extensive use of chemical pesticides has led to increasing concerns regarding pathogen resistance, environmental contamination, and pesticide residues in fruit. Research and practical applications have demonstrated that the use of beneficial microorganisms with antimicrobial activity and their metabolites can achieve comparable or even superior control efficacy to chemical pesticides, while offering advantages such as high selectivity, reduced risk of resistance development, and enhanced safety. Numerous studies have reported the screening of antagonistic microorganisms from epiphytes, endophytes, and soil microbiota for the biocontrol of pear fire blight, including species of Bacillus, Pseudomonas fluorescens, E. herbicola, non-pathogenic E. amylovora strains [5, 6], and bacteriophages [7]. Several commercial biocontrol products are available, such as BlightBan^™ A506 (Pseudomonas fluorescens A506) [8] and Biopro^™ (Bacillus subtilis BD170) [9]. However, factors such as climate and other ecological conditions have led to erratic success rates for bacterial biological control agents in the western United States. For instance, treatments with BlightBan A506 and BlightBan C9-1 demonstrated significant reductions in blossom blight incidence, ranging from 40% to 80%, across multiple experiments conducted over a six-year period in the Pacific Northwest [10]. Consequently, the field efficacy evaluation system for biocontrol agents must be underpinned by rigorous, multi-regional, and multi-season scientific validation. Only through a systematic assessment of their adaptability in complex ecological environments, the sustained nature of their functional efficacy, and the stability parameters of their control effects can a scientifically objective and comprehensive evaluation be established.

Myxobacteria are prokaryotes characterized by multicellular social behaviors and complex life cycles, exhibiting broad predatory activity against bacteria and fungi [11]. As emerging biocontrol agents, myxobacteria possess several advantages over previously reported biocontrol microorganisms, including diverse predation strategies, a wide host range, effective colonization ability, the capacity to produce a diverse array of novel secondary metabolites and stress-resistant myxospores, and involvement in soil organic matter metabolism [12, 13]. Consequently, myxobacteria have been recognized as a promising group of biocontrol microbes [14, 15], demonstrating potential for the biocontrol of various plant diseases, such as pear fire blight, pepper anthracnose, tomato bacterial wilt, and cucumber wilt [16–18].

In our previous work, a strain of Myxococcus fulvus WCH05 was isolated and purified from desert soil in Wucaiwan, Jimsar County, Changji Hui Autonomous Prefecture, Xinjiang, China. This strain exhibited strong predatory activity against E. amylovora, and pot experiments demonstrated its promising efficacy in controlling pear fire blight [19]. However, Further validation is required to ascertain whether M. fulvus WCH05 exhibits consistent control efficacy against pear fire blight under field conditions. Moreover, given that different microorganisms possess distinct environmental preferences, their physiology, growth, and activity are demonstrably influenced by fermentation conditions. Consequently, determining the optimal fermentation conditions for biocontrol agents is a prerequisite to accurately assessing their efficacy.

We employed single factor experiments and response surface methodology (RSM) to optimize the fermentation medium and conditions for strain WCH05, aiming to increase its biomass production and enhance its biocontrol efficacy, thus laying the foundation for the development, large-scale production, and application of a microbial agent. Field trials were conducted in pear orchards across three locations over two consecutive years to evaluate its field performance, providing a solid basis for further development and utilization of this strain.

Materials and methods

Microorganisms and media

E. amylovora (Ea; strain E.a001), a highly virulent strain as determined by pathogenicity assays [20], was isolated from diseased fragrant pear branches in Korla City, Xinjiang, China. M. fulvus WCH05, a myxobacterial strain with high predatory activity against E. amylovora, was isolated, screened, and maintained in our laboratory.

MD1 medium [21] consisted of casein peptone 6.0 g/L, soluble starch 2.0 g/L, CaCl₂·2H₂O 0.4 g/L, and MgSO₄·7H₂O 2.0 g/L, with a pH of 7.2. LBS medium [22] contained soluble starch 7.0 g/L, yeast extract powder 5.0 g/L, casein peptone 1.0 g/L, and MgSO₄·7H₂O 1.0 g/L, with a pH of 7.0. CYE medium [23] was composed of casein peptone 10.0 g/L, yeast extract 5.0 g/L, and MgSO₄·7H₂O 1.0 g/L, with a pH of 7.6. VY/4 medium [24] contained yeast 5.0 g/L and CaCl₂·2H₂O 1.0 g/L, with a pH of 7.2. VY/2 medium [24] contained yeast 5.0 g/L and CaCl₂·2H₂O 1.0 g/L, with a pH of 7.2, and was supplemented with vitamin B12 to a final concentration of 50 µg/mL after sterilization. NB medium [25], used for culturing E. amylovora, consisted of peptone 10.0 g/L, NaCl 5.0 g/L, sucrose 5.0 g/L, and beef extract 3.0 g/L, with a pH of 7.2. TPM agar (Tris-HCl 1.58 g/L, KH₂PO₄ 0.14 g/L, MgSO₄ 2.0 g/L, and agar 15 g/L) [23] was used for the plate predation assays of strain WCH05 against E. amylovora.

Biomass determination

Biomass of strain WCH05 was determined by measuring cell dry weight [26]. Cultures were harvested by centrifugation at 12,000 r/min for 10 min at 4 °C, washed three times with sterile distilled water, and dried at 80 ± 2 °C for 4 h to constant weight. Biomass was expressed as g/L.

Predatory activity of M. fulvus WCH05 at different cell densities against E. amylovora

E. amylovora strain E.a001 was revived and a single colony was inoculated into NB broth. The culture was incubated at 28 ± 0.2 °C with shaking at 180 r/min for 12–16 h. Cells were harvested by centrifugation at 12,000 r/min for 1 min, washed three times with sterile distilled water, and resuspended to an OD₆₀₀ of 1.0. M. fulvus WCH05 was revived on VY/4 agar plates, and a portion of the resulting growth was transferred to MD1 broth and incubated at 30 ± 0.2 °C with shaking at 180 r/min for 2 d. Cells were then collected, resuspended in sterile distilled water, and adjusted to OD₆₀₀ values of 1.0, 1.5, 1.8, 2.1, 2.4, 2.7, and 3.0.

For the predation assay, 50 µL of the E. amylovora suspension was inoculated onto TPM agar plates and allowed to air dry for 15 min. Then, 2 µL of the M. fulvus WCH05 suspensions at different OD₆₀₀ values were spotted 2 mm from the edge of the E. amylovora lawn. Sterile distilled water (2 µL) served as a control. Each treatment was replicated three times. The plates were incubated at 30 ± 0.2 °C for 3 d, and the expansion of M. fulvus WCH05 was observed and recorded using a stereomicroscope (SM7, Motic China Group Co., Ltd.). After 5 d, the bacterial growth was scraped off using a sterile loop, serially diluted, and plated to determine the number of surviving E. amylovora cells, thus evaluating the predatory capacity of WCH05 at different cell densities.

Selection of growth medium and growth curve determination

M. fulvus WCH05 was revived on VY/4 agar plates, and a portion of the resulting growth was transferred to 20 mL of MD1 broth in a 50 mL flask and incubated at 30 ± 0.2 °C with shaking at 180 r/min for 2 d. The culture was then adjusted to an OD₆₀₀ of 1.0 and used as a seed culture. The seed culture was inoculated (3% v/v) into 100 mL of each candidate medium (VY/4, VY/2, MD1, LBS, and CYE) in 250 mL flasks. Cultures were incubated at 30 ± 0.2 °C with shaking at 180 r/min for 72 h, with three replicates per medium. The optimal growth medium for M. fulvus WCH05 was selected based on a comparison of cell dry weights.

For the growth curve determination, the seed culture (3% v/v) was inoculated into MD1 broth and incubated at 30 ± 0.2 °C with shaking at 180 r/min. Samples were taken every 4 h, centrifuged at 12,000 r/min for 10 min, and the cell dry weight was determined. A total of 25 time points were collected, with three replicates per time point. A growth curve was constructed by plotting cell dry weight against incubation time.

Single-factor optimization experiments

Optimization of medium components

Using MD1 medium as the basal medium, different carbon sources (pea starch, glucose, soluble starch, dextrin, sweet potato starch, sucrose, and galactose, each at a final concentration of 2.0 g/L) and nitrogen sources (soybean peptone, tryptone, yeast extract, beef extract, peptone, casein peptone, KNO₃, and urea, each at a final concentration of 6.0 g/L) were individually substituted for the corresponding components in the basal medium, while keeping other components constant. Cultures were grown in 250 mL Erlenmeyer flasks with a working volume of 40%, inoculated with a 3% (v/v) inoculum of seed culture (OD₆₀₀ = 1.0), and incubated at 30 °C with shaking at 180 r/min for 72 h. Cell dry weight was measured to determine the optimal carbon and nitrogen sources. Subsequently, the effects of different concentrations of the selected carbon and nitrogen sources (1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, and 10.0 g/L) on cell dry weight were evaluated to determine the optimal concentrations. Each treatment was performed in triplicate.

Based on the optimized carbon and nitrogen sources, different inorganic salts (CuSO₄, MnSO₄, CaSO₄, MgSO₄, FeSO₄, K₂SO₄, and ZnSO₄, each at a final concentration of 0.4 g/L) were individually added to determine the optimal inorganic salt. Subsequently, the effects of different concentrations of the selected inorganic salt (0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.2, and 2.4 g/L) on cell biomass were evaluated to determine the optimal concentration. Each treatment was performed in triplicate.

Optimization of culture conditions

Using the optimized carbon, nitrogen, and inorganic salt, the initial culture conditions were set as follows: 3.0% inoculum, initial pH 7.0, 40% working volume (100 mL in 250 mL flasks), 30 °C incubation temperature, and 180 r/min shaking speed for 72 h. Single-factor optimization was performed to determine the effects of five factors on M. fulvus WCH05 biomass: incubation temperature (26, 28, 30, 32, and 34 °C), initial pH (6.0, 6.2, 6.4, 6.6, 6.8, 7.0, 7.2, 7.4, 7.6, 7.8, and 8.0), inoculum size (1, 2, 3, 4, 5, 6, 7, 8, 9, and 10%), working volume (12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, and 60%), and shaking speed (160, 180, 200, 220, and 240 r/min). When optimizing one factor, the other conditions were kept constant. Cell dry weight was used as the indicator, and each treatment was performed in triplicate.

Response surface optimization experiments

Plackett-Burman (PB) tests

Based on the results of the single-factor optimization experiments, Plackett-Burman (PB) tests were conducted for further optimization. Experiments were designed using Design Expert 13.0 software [27], with each factor set at two levels (high level “+1” and low level “−1”). Each experiment was replicated three times. Cell dry weight after fermentation was used as the response variable to screen the main factors influencing M. fulvus WCH05 growth from among carbon source, nitrogen source, inorganic salt, incubation temperature, initial pH, inoculum amount, working volume, and shaking speed.

Box-Behnken design (BBD) tests

Based on the principles of the Box-Behnken Design (BBD), cell dry weight (determined as described in "Biomass determination" section) was used as the response variable. Using the optimal parameters obtained from the single-factor experiments as the center point, Design Expert 13.0 software was used to design a four-factor, three-level experiment consisting of 29 runs [28]. The results were then analyzed using the same software.

Verification experiments for response surface optimization results

Cell dry weight of M. fulvus WCH05 obtained under the optimized fermentation conditions was measured as described in "Biomass determination" section. Cell dry weight obtained under the initial fermentation conditions (MD1 medium, 40% working volume, 3% inoculum, initial pH 7.2, 30 °C incubation temperature, and 180 r/min shaking speed for 72 h) served as the control.

Protective efficacy of M. fulvus WCH05 fermentation broth against fire blight on potted Pyrus betulifolia seedlings

Two-year-old healthy potted P. betulifolia seedlings were used to evaluate the protective efficacy of M. fulvus WCH05 fermentation broth (cell suspension of WCH05) against fire blight. Seven treatments were established: (A) fermentation broth obtained under initial fermentation conditions; (B) undiluted fermentation broth obtained under optimized fermentation conditions; (C) fermentation broth obtained under optimized fermentation conditions diluted 50-fold; (D) fermentation broth obtained under optimized fermentation conditions diluted 100-fold; (E) streptomycin solution (4000-fold dilution, 72% active ingredient, North China Pharmaceutical Group Corporation); (F) sterile distilled water (control); and (G) untreated healthy P. betulifolia seedlings (negative control). The dilution fold for Streptomycin was chosen based on the manufacturer’s recommendation.

Treatments A–F were applied to the seedlings by spraying the leaves and branches to runoff (30 mL per pot) using a hand-held sprayer. After 24 h, the seedlings were spray-inoculated with an E. amylovora suspension (10⁷ CFU/mL, 30 mL per pot). Each treatment consisted of three pots, with approximately 8–10 new shoots per pot and was replicated three times. Inoculated seedlings were incubated in a greenhouse at 28–30 °C and 70% relative humidity. Disease development was monitored for 14 d, and the number of infected shoots, canker length, and disease severity were recorded every 7 d. Disease incidence, disease index, and control efficacy were calculated. At the end of the experiment, infected plant material was autoclaved and discarded.

Disease severity on potted P. betulifolia seedlings was rated [29]. Disease incidence (%) = (Number of infected shoots / Total number of inoculated shoots) × 100. Disease index = Σ (Number of shoots in each disease severity class × Representative value of the disease severity class) / (Total number of inoculated shoots × Highest disease severity value) × 100. Control efficacy (%) = (Disease index of control – Disease index of treatment) / Disease index of control × 100.

Field efficacy of M. fulvus WCH05 fermentation broth against fire blight in pear orchards

Field trials were conducted in three pear orchards with a history of severe fire blight incidence and typical agricultural management practices in Korla City, Xinjiang, and Zhangye City, Gansu Province, in 2023 and 2024 (Table 1). Each orchard included three treatments: fermentation broth obtained under optimized fermentation conditions diluted 50-fold, Kasugamycin solution (active ingredient concentration 2%, Jiangmen Plant Protection Co., Ltd.) (600-fold dilution, according to the manufacturer’s recommendation), and water (control). Due to the regulatory ban on streptomycin application in China, we utilized Kasugamycin instead of streptomycin for all field trials. Each treatment was applied to one row (25–65 trees) with three replicates, and one buffer row was left between treatments. Two applications were performed at the initial flowering stage (30% bloom), and the petal fall stage (80% petal fall). Due to frost damage in Korla City in early May 2023 and continuous rainfall in Zhangye City in early June 2024, one additional application was performed (details of the orchards and application times are presented in Table 1). Applications were performed on cloudy, windless days or on sunny days with low temperatures using a 100 L pump sprayer. Approximately 1–2 L of treatment solution was applied per tree at the initial flowering stage, and approximately 2–3 L per tree at the petal fall stage and the third application. The spray volume was increased to accommodate the larger target surface area resulting from the developing tree canopy. Disease incidence was assessed every 14 d after the second application, and the disease index and control efficacy were calculated [30]. Infected tissues were pruned and destroyed after each assessment.

Table 1.

Overview of pear orchard and date of biocontrol agent application and disease assessment

Year	Site	Varity	Orchard overview	Application/survey date
2023	Xiaolangan Village, Awati Township, Korla City, Xinjiang	Fragrant Pear (Pyrus sinkiangensis)	18-year-old tree, row spacing of 4 m × 2 m. No intercropping. Conventional management. No chemical fungicides or other microbial agents. Insecticides were applied as needed. Each treatment consisted of 25 pear trees, replicated three times.	First: April 9; Second: April 20; Third: May 9/First: May 4; Second: May 18; Third: June 1; Fourth: June 15
	Kalayagachi Village, Awati Township, Korla City, Xinjiang	Fragrant Pear (Pyrus sinkiangensis)	5-year-old tree, row spacing of 4 m × 1 m. No intercropping. Conventional management. No chemical fungicides or other microbial agents. Insecticides were applied as needed. Each treatment consisted of 60 pear trees, replicated three times.	First: April 10; Second: April 20/First: May 4; Second: May 18; Third: June 1; Fourth: June 15
2024	Zhangye Agricultural Experiment Station, Gansu Academy of Agricultural Sciences	‘Zao su’ Pear (Pyrus bretschneideri Rehd)	7-year-old tree, row spacing of 4 m × 2 m. No intercropping. Conventional management. No chemical fungicides or other microbial agents. Insecticides were applied as needed. Each treatment consisted of 65 pear trees, replicated three times.	First: April 18; Second: April 29; Third: June 8/First: May 13; Second: May 27; Third: June 10; Fourth: June 24

Meteorological data

Meteorological data, encompassing average temperature, humidity, wind speed, and precipitation, were collected from the nearest meteorological station.

Data analysis

SPSS Statistics 22.0 (IBM, Armonk, NY, USA) software was used to analyze the obtained data. Means, standard deviations (SD), and relative standard deviations (RSD) were calculated. Design-Expert 13.0 software (Stat-Ease, Inc., Minneapolis, MN, USA) was used for designing Plackett–Burman design and Box-Behnken design experiments, as well as for data analysis (Cao et al., 2024). Statistical analyses were also performed with SPSS Statistics 22.0 software using paired t-tests with Bonferroni correction. P values < 0.05 were considered statistically significant. Figures were generated using GraphPad Prism 8.0.2 (GraphPad, San Diego, CA, USA) software [31].

Results and analysis

Predation of E. amylovora by M. fulvus WCH05 is dependent on cell density

The predatory activity of M. fulvus WCH05 against E. amylovora (Ea) was significantly enhanced with increasing cell density. In co-culture assays, after 3 d, M. fulvus WCH05 at an OD₆₀₀ of 3.0 almost completely covered the Ea colonies, while at an OD₆₀₀ of 1.0, it covered only approximately half (Supplementary Fig. 1A), demonstrating a clear density-dependent effect. Furthermore, quantification of viable Ea cells after 5 d of co-incubation revealed a significant decrease in Ea numbers with increasing M. fulvus WCH05 cell density (Supplementary Fig. 1B). These results unequivocally demonstrate a positive correlation between the predatory efficiency of M. fulvus WCH05 against Ea and its cell density. Consequently, optimizing fermentation conditions to maximize M. fulvus WCH05 biomass production became a key objective.

Screening of initial medium and growth curve of M. fulvus WCH05

To determine the optimal initial medium for M. fulvus WCH05 growth, biomass production was compared in five different media (VY/4, VY/2, MD1, LBS, and CYE) under standardized conditions (3% inoculum, 30 °C, 180 r/min, 72 h). Significant differences in growth were observed among the five media (Fig. 1A). Specifically, cell dry weights in MD1, VY/4, and CYE (1.30, 1.25, and 1.26 g/L, respectively) were significantly higher than those in VY/2 (1.10 g/L) and LBS (0.71 g/L). MD1 supported the highest biomass production and was selected as the optimal initial medium for subsequent experiments.

Fig. 1.

Screening of optimal culture media and growth curve of Myxococcus fulvus WCH05. (A) Comparison of M. fulvus WCH05 growth in different culture media. (B) Growth curve of M. fulvus WCH05 in the optimized medium (MD1). Data are means ± SD of three replicates. Means followed by different letters are significantly different (Duncan’s multiple range test, P < 0.05)

The growth curve of M. fulvus WCH05 in MD1 medium was determined (Fig. 1B). The bacterium exhibited a lag phase for approximately 12 h, followed by exponential growth between 12 and 68 h. The stationary phase was reached at 68 h, and a decline phase was observed after 76 h. Based on these results, a 72-h incubation period (corresponding to the stationary phase) was selected for subsequent experiments, with cell dry weight at this time point used as the response variable for fermentation optimization.

Single-factor screening of main medium components

M. fulvus WCH05 demonstrated growth in all seven tested carbon sources. Based on the resulting cell dry weight, the carbon sources were ranked in descending order: soluble starch > sucrose > dextrin > pea starch > sweet potato starch > glucose > galactose (Fig. 2A). Soluble starch supported the highest biomass production and was identified as the optimal carbon source. Further experiments examining the effect of soluble starch concentration on biomass production revealed a positive correlation up to a concentration of 8.0 g/L, at which point the maximum cell dry weight of 2.67 g/L was achieved (Fig. 2D). However, increasing the soluble starch concentration beyond 8.0 g/L resulted in a decrease in biomass. Therefore, 8.0 g/L soluble starch was determined as the optimal concentration for M. fulvus WCH05 fermentation.

Fig. 2.

Effects of medium components on the cell dry weight of Myxococcus fulvus WCH05. (A) Different carbon sources. (B) Different nitrogen sources. (C) Different inorganic salts. (D) Soluble starch concentration. (E) Yeast extract concentration. (F) MgSO₄ concentration. Data are means ± SD of three replicates. Means followed by different letters are significantly different (Duncan’s multiple range test, P < 0.05)

Among the tested nitrogen sources, yeast extract resulted in the highest cell dry weight, followed by soybean peptone > beef extract > casein peptone > tryptone > urea > KNO₃ (Fig. 2B). Therefore, yeast extract was selected as the optimal nitrogen source. The effect of yeast extract concentration on M. fulvus WCH05 growth was also investigated. A maximum cell dry weight of 2.91 g/L was achieved at a yeast extract concentration of 4.0 g/L (Fig. 2E), which was selected as the optimal concentration.

With 8.0 g/L soluble starch and 4.0 g/L yeast extract as the carbon and nitrogen sources, respectively, the effects of different inorganic salts on M. fulvus WCH05 growth were evaluated. MgSO₄ significantly promoted growth compared to the other inorganic salts tested (Fig. 2C). A maximum cell dry weight of 3.09 g/L was achieved at a MgSO₄ concentration of 1.2 g/L (Fig. 2F), which was consequently selected as the optimal concentration.

Single-factor optimization of fermentation conditions

Based on the optimized medium composition identified in previous experiments, single-factor optimization of fermentation conditions was performed.

Incubation temperature significantly affected M. fulvus WCH05 growth (Fig. 3A). The highest cell dry weight (3.31 g/L) was obtained at 30 °C.

Fig. 3.

Effects of fermentation conditions on the cell dry weight of Myxococcus fulvus WCH05. (A) Incubation temperature. (B) Initial pH. (C) Inoculum volume. (D) Working volume. (E) Shaking speed. Data are means ± SD of three replicates. Means followed by different letters are significantly different (Duncan’s multiple range test, P < 0.05)

Initial pH also played a crucial role (Fig. 3B). Cell dry weight increased with increasing pH from 6.0 to 7.0, reaching a maximum of 3.22 g/L at pH 7.0. Further increases in pH led to a decrease in biomass, indicating that both acidic and alkaline conditions were detrimental to growth.

The effect of inoculum size was investigated (Fig. 3C). Cell dry weight increased with increasing inoculum size up to 7%, reaching a maximum of 3.32 g/L. However, no significant differences were observed between inoculum sizes of 6% and 10%.

A working volume of 40% (100 mL in 250 mL flasks) resulted in the highest cell dry weight (3.22 g/L) (Fig. 3D).

Among the tested shaking speeds, 200 r/min resulted in the highest cell dry weight (3.28 g/L) (Fig. 3E). It was also observed that higher shaking speeds led to more dispersed cell growth.

Based on these single-factor optimization experiments, the following optimal fermentation parameters were determined: 30 °C incubation temperature, initial pH 7.0, 7% inoculum size, 40% working volume (100 mL in 250 mL flasks), and 200 r/min shaking speed.

Response surface optimization of fermentation conditions for biomass production by M. fulvus WCH05

Plackett-Burman (PB) test

Eight factors identified in the single-factor experiments (soluble starch, yeast extract, MgSO₄, incubation temperature, initial pH, inoculum size, working volume, and shaking speed) were selected for a Plackett-Burman (PB) design to screen for significant factors affecting M. fulvus WCH05 biomass production. The 12 PB experiments resulted in cell dry weights ranging from 2.81 to 3.26 g/L (Supplementary Table 1). Statistical analysis (Table 2) revealed a significant model (R² = 99.21%, adjusted R² = 97.09%, P = 0.0046 < 0.05). Soluble starch, yeast extract, MgSO₄, and inoculum size had positive effects on biomass production, while initial pH, working volume, rotational speed, and temperature had negative effects. Soluble starch, yeast extract, working volume, and inoculum size had the most significant effects on biomass (P < 0.05), with soluble starch, yeast extract and working volume reaching highly significant levels (P < 0.01). Analysis of F-values indicated the following order of influence on cell dry weight: soluble starch > yeast extract > working volume > inoculum size. These four factors were selected for further optimization using a Box-Behnken design (BBD).

Table 2.

Analysis of variance for each factor Plackett-Burman design

Source	Coefficient estimate	Satanized effect	Contribution /%	Sum of squares	Mean square	F	P	Importance ranking
A	0.0902	0.180	40.08	0.0976	0.0976	151.75	0.0012	1
B	0.0828	0.166	33.8	0.0823	0.0823	128.07	0.0015	2
C	0.0237	0.047	2.76	0.0067	0.0067	10.45	0.0481	5
D	0.0120	-0.024	0.71	0.0017	0.0017	2.69	0.1996	6
E	-0.0522	-0.104	13.41	0.0327	0.0327	50.80	0.0057	3
F	0.0408	0.081	8.22	0.0200	0.0200	31.12	0.0114	4
G	-0040	-0.008	0.08	0.0001	0.0001	0.29	0.6228	7
H	-0032	-0.006	0.05	0.0001	0.0001	0.18	0.6945	8
Model	2.98	0	0	0.2413	0.0302	46.92	0.0046

A (Soluble starch), B (Yeast extract); C (MgSO₄), D (Initial pH), E (Working volume), F (Inoculation amount), G (Rotational speed), H (Temperature), R² = 99.21%, R²_adj = 97.09%

Box-Behnken design (BBD) test

Based on the PB test results, a BBD was employed to further optimize biomass production, using soluble starch (A), yeast extract (B), working volume (C), and inoculum size (D) as independent variables. The center points for each variable were based on the optimal values from the single-factor experiments: soluble starch (6.0–10.0 g/L), yeast extract (2.0–6.0 g/L), working volume (32–48%, 80–120 mL in 250 mL flasks), and inoculum size (5–9%). The BBD results are shown in Supplementary Tables 2, and the analysis of variance (ANOVA) for the regression model is presented in Table 3. The model was highly significant (R² = 94.51%, adjusted R² = 89.02%, P < 0.0001). The lack of fit was not significant (P = 0.4793 > 0.05), confirming the model’s reliability for prediction. The quadratic terms A², B², C², and D², and the interaction term A×B and C×D had significant effects on biomass production (P < 0.05), while other interaction terms were not significant (P > 0.05). The fitted quadratic regression equation was Y = 3.10 + 0.3892A + 0.0996B + 0.1152C − 0.0265D − 0.3208AB − 0.0962AC + 0.0675AD − 0.0404BC − 0.0875BD − 0.3185CD − 0.4135A² − 0.3571B² − 0.3188C² − 0.2398D².

Table 3.

Analysis of variance for the Box-Behnken design

Source	Sum of squares	df	Mean squared	F	P	Distinctiveness
Model	5.01	14	0.3579	17.22	< 0.0001	**
A	1.53	1	1.53	73.43	< 0.0001	**
B	0.1801	1	0.1081	5.20	0.0387
C	0.1145	1	0.1145	5.51	0.6718
D	0.0083	1	0.0083	0.4004	0.6832
AB	0.2575	1	0.2575	12.39	0.0034	**
AC	0.0484	1	0.0484	2.33	0.1493
AD	0.0182	1	0.0182	0.8767	0.3650
BC	0.0035	1	0.0035	0.1683	0.6879
BD	0.0306	1	0.0306	1.47	0.2249
CD	0.2208	1	0.2208	10.62	0.0057	**
A 2	0.9149	1	0.9149	44.01	< 0.0001	**
B 2	0.7543	1	0.7543	36.29	< 0.0001	**
C 2	0.6449	1	0.6449	31.02	< 0.0001	**
D 2	0.3559	1	0.3559	17.12	0.0010	**
Residual	0.291	14	0.0208
Lack of Fit	0.194	10	0.0216	1.11	0.4793
Pure Error	0.097	4	0.0194
Cor Total	5.3	28

A (Soluble starch), B (Yeast extract), C (Working volume), D (Inoculation amount), R² = 94.51%, R²_adj = 89.02%, *P < 0.05, **P < 0.01

Three-dimensional response surface plots were generated based on the regression equation (Fig. 4). The steep slopes observed in the plots for the interactions between soluble starch and yeast extract, and between working volume and inoculum size (Fig. 4A and F), indicated strong synergistic effects. The relatively flat surfaces of the other interaction plots suggested weaker interactions (Fig. 4B–E).

Fig. 4.

Interactive effects of medium and conditions on the cell dry weight of Myxococcus fulvus WCH05. (A) Soluble starch (A) × Yeast extract (B). (B) Soluble starch (A) × Working volume (C). (C) Soluble starch (A) × Inoculum volume (D). (D) Yeast extract (B) × Working volume (C). (E) Yeast extract (B) × Inoculum volume (D). (F) Working volume (C) × Inoculum volume (D)

Validation of the optimized response surface results

Analysis of the regression equation using Design-Expert software predicted a maximum biomass production (Y) of 3.20 g/L under the following optimal conditions: 8.0 g/L soluble starch, 4.0 g/L yeast extract, 40% working volume (100 mL in 250 mL flasks), and 7% inoculum size. Three validation experiments conducted under these predicted optimal conditions resulted in an average cell dry weight of 3.25 g/L, with a relative error of 1.56% compared to the predicted value, confirming the reliability of the model. This optimized biomass production represented a 2.5-fold increase compared to the initial biomass production of 1.30 g/L in MD1 medium ("Screening of initial medium and growth curve of M. fulvus WCH05" section), demonstrating the practical value of the optimization process.

In summary, the optimal fermentation conditions for M. fulvus WCH05 were determined to be: 8 g/L soluble starch, 4 g/L yeast extract, 1.2 g/L MgSO₄, initial pH 7.0, 40% working volume, 7.0% inoculum size, 200 r/min shaking speed, and 30 °C incubation for 72 h.

Protective efficacy of M. fulvus WCH05 fermentation broth against fire blight on P. betulifolia seedlings

Spray application of M. fulvus WCH05 fermentation broth significantly reduced disease incidence (P < 0.05). At 7 and 14 d post-inoculation with E. amylovora, the fermentation broth obtained under initial conditions provided 80.3% and 79.6% protection, respectively. Optimization of fermentation conditions significantly improved the protective efficacy to 86.2% and 82.6% at 7 and 14 d, respectively, approaching the efficacy of streptomycin (89.0%). Diluting the optimized fermentation broth 50-fold still provided considerable protection (75.3% and 71.1% at 7 and 14 d, respectively), while a 100-fold dilution reduced the protective efficacy to 59.2% and 51.2% (Table 4, Supplementary Fig. 2).

Table 4.

The effect of strain WCH05 fermentation broth on potted pear seedlings

Treatment	7d			14d
	Incidence rate %	Disease index	Control effect %	Incidence rate %	Disease index	Control effect %
Optimized fermentation broth	9.2 ± 1.9 c	1.6 ± 0.4 cd	86.2 ± 3.6 ab	21.1 ± 4.4 c	5.8 ± 0.6 cd	82.6 ± 1.9 ab
Optimized fermentation broth (50-fold dilution)	12.9 ± 2.9 c	2.9 ± 0.9 c	75.3 ± 4.3 b	33.1 ± 1.3 bc	9.7 ± 0.1 c	71.1 ± 3.3 b
Optimized fermentation broth (100-fold dilution)	24.8 ± 5.5 b	4.9 ± 0.2 b	59.2 ± 1.7 c	47.4 ± 8.5 ab	16.3 ± 2.4 b	51.2 ± 7.1 c
Unoptimizatized Fermentation broth	11.8 ± 2.6 c	2.4 ± 0.5 cd	80.3 ± 4.3 ab	23.3 ± 2.6 c	6.8 ± 0.7 cd	79.6 ± 2.2 ab
Streptomycin	5.5 ± 0.6 c	1.1 ± 0.1 d	90.8 ± 0.1 a	19.7 ± 0.8 c	3.8 ± 1.4 d	89.0 ± 4.1 a
CK	48.0 ± 3.5 a	11.9 ± 0.7 a	—	52.0 ± 3.5 a	33.5 ± 2.1 a	—

Different letters following mean ± SD indicate significant differences analyzed by the least significant difference at 5% significance level, CK: treated with Ea but not inoculated with WCH05; “—” represents inability to calculate prevention effect

Field efficacy of M. fulvus WCH05 fermentation broth against fire blight in Pear orchards

Field trials evaluating the control of fire blight by M. fulvus WCH05 fermentation broth were conducted in pear orchards in Korla City, Xinjiang, and Zhangye City, Gansu Province, over two consecutive years (2023 and 2024).

Observations (Table 5) revealed distinct disease progression patterns in the two locations. In Korla City (2023), typical shoot blight symptoms were observed 14 d after the second application (May 4). A cold wave accompanied by sleet occurred in Korla City from May 5 to May 7 (Fig. 5A–C). The low-temperature and humid conditions led to a marked increase in disease incidence in mid to late May. As temperatures continued to rise in June, disease occurrence gradually declined. In 2024, the disease incidence peaked 14 d after the second application (May 4) and then gradually decreased, with symptoms subsiding by June. In contrast, in Zhangye City (2024), only sporadic shoot blight symptoms were observed 28 d after the second application (May 27), with the disease peaking in mid-to-late June. The delayed disease development in Zhangye City compared to Korla City may be attributed to lower temperatures from April to June and increased rainfall in June (Fig. 5B).

Table 5.

Field efficacy of Myxococcus fulvus WCH05 for biocontrol of pear fire blight (2023–2024)

Year	Orchard	Treatment	14 days after the second spraying of bacteria			28 days after the second spraying of bacteria			42 days after the second spraying of bacteria			56 days after the second spraying of bacteria
			Incidence %	Disease index	Control efficacy %	Incidence%	Disease index	Control efficacy%	Incidence %	Disease index	Control efficacy %	Incidence %	Disease index	Control efficacy%
2023	Korla City, Xinjiang	WCH05	1.3±1.3 b	0.5±0.3 b	83.3±8.3 a	6.7±2.3 b	1.3±0.5 b	81.5±3.7 a	4.0±2.4 b	0.8±0.3 b	81.3±10.8a	1.3±1.3 a	0.3±0.2 b	88.9±11.1a
		Kasugamycin	2.7±1.7 b	0.8±0.5 b	75.0±14.4 a	6.7±1.3 b	1.8±0.3 b	74.1±3.7 a	5.3±1.3 b	1.1±0.5 b	75.0±6.3 a	2.7±1.3 a	0.5±0.3 b	77.9±11.1 a
		CK	10.7±1.3 a	3.2±0.5 a	—	17.3±2.7 a	7.2±0.9 a	—	10.7±1.3 a	3.7±0.3 a	—	6.7±1.3 a	2.4±0.5 a	—
2024	Korla City, Xinjiang	WCH05	5.0±1.0 b	1.2±0.1 b	81.0±1.7 a	2.2±0.6 b	0.4±0.1 b	84.0±4.0 a	1.7±0.5 a	0.2±0.1 b	88.3±5.9 a	0.6±0.6 b	0.1±0.1 b	90.9±9.1 a
		Kasugamycin	5.6±1.5 b	1.6±0.1 b	75.8±1.7 a	2.8±0.6 b	0.6±0.1 b	80.0±4.0 a	1.1±0.5 a	0.3±0.2 b	82.4±10.2 a	1.1±0.6 b	0.2±0.1 b	81.8±9.1 a
		CK	15.6±0.6 a	6.4±0.1 a	—	9.4±0.6 a	2.8±0.3 a	—	6.1±1.5 a	1.9±0.3 a	—	5.0±1.0 a	1.0±0.1 a	—
	Zhangye, Gansu Province	WCH05	0	0	—	0.6±0.6 b	0.1±0.1 b	88.4±11.6 a	2.9±0.6 b	0.6±0.1 c	89.7±2.1 a	2.9±0.5 b	1.3±0.1 b	82.5±1.5 a
		Kasugamycin	0	0	—	1.0±0.5 b	0.2±0.1 b	80.0±10.0 a	2.6±0.5 b	0.9±0.2 b	82.7±1.2 a	6.2±0.9 b	1.8±0.1 b	74.6±2.4 a
		CK	0	0	—	5.1±0.5 a	1.0±0.1 a	—	21.5±0.9 a	5.3±0.1 a	—	28.2±1.4 a	7.3±0.4 a	—

Means ± standard deviation (SD) followed by different letters indicate significant differences according to Duncan’s multiple range test (P < 0.05). CK represents the naturally occurring disease rate. The symbol “—” indicates that the prevention effect could not be calculated

Fig. 5.

Meteorological parameters from April to June (2023–2024) at Korla and Zhangye experimental sites. (A) Average temperature. (B) Average precipitation. (C) Average relative humidity. (D) Average wind speed. The red arrow indicates a cold wave and sleet event in early May 2023 in Korla, Xinjiang. The orange arrow indicates continuous rainfall in early June 2024 in Zhangye, Gansu

Field efficacy results (Table 5) demonstrated that the M. fulvus WCH05 fermentation broth provided effective control of fire blight. In Korla City (2023), the control efficacy ranged from 81.5% to 88.9%, compared to 74.1% to 77.9% for Kasugamycin. In Korla City (2024), the M. fulvus WCH05 fermentation broth provided 81.0% to 90.9% control, while Kasugamycin provided 75.8% to 82.4% control. In Zhangye City (2024), the M. fulvus WCH05 fermentation broth achieved 82.5% to 89.7% control, and Kasugamycin achieved 74.6% to 82.7% control.

Discussion

Due to the scarcity of resistant cultivars, the control of fire blight currently relies heavily on chemical pesticides, leading to increasing concerns regarding pathogen resistance, environmental pollution, and pesticide residues in fruit [32]. Consequently, the search for safe and effective biocontrol agents against fire blight has become a global research priority. Myxobacteria, with their generalist predatory lifestyle, adaptability to diverse environments, and capacity to produce a wide array of bioactive compounds, have emerged as a promising group of biocontrol microorganisms with significant potential for controlling plant diseases in agricultural production [33, 34]. However, fundamental research on myxobacteria remains relatively limited, and scalable fermentation and efficient cultivation technologies are still under development [35].

The collective predatory behavior of myxobacteria also reflects their dependence on population density; when the density is too low, growth becomes delayed, ceases, or even leads to cell death. During the degradation of macromolecular organic substances to obtain nutrients, myxobacteria require cooperative interactions, in which cells physically contact each other to form biofilms. Through this aggregated state, they maintain a high local concentration of enzymes for predation and the acquisition of utilizable small-molecule nutrients [36, 37]. When the optical density (OD₆₀₀) of the WCH05 cell suspension was 3.0, the viable cell count of the target bacterium Ea decreased from 4.2 × 10¹⁰ CFU/mL to 5.0 × 10⁴ CFU/mL; however, when the OD₆₀₀ was 1.5, the viable count decreased from 4.2 × 10¹⁰ CFU/mL to 2.7 × 10⁶ CFU/mL. These results indicate that the predatory efficiency of strain WCH05 is strongly correlated with its population density. Therefore, in this study, to enhance the biomass (cell density) of strain WCH05 per unit volume of fermentation broth, the culture medium and conditions were optimized using single-factor experiments and response surface methodology. This optimization aimed to improve its predatory and disease control efficiency, providing a foundation for the future development of biopesticides.

This study optimized the medium composition by focusing on three factors: carbon source, nitrogen source, and inorganic salts. Carbon sources are essential substances for microbial cell structure and can also serve as energy sources. This experiment showed that when the carbon source in the medium was soluble starch, the biomass of strain WCH05 in shake flasks was significantly higher than that of various other carbon sources, which may be related to the ability of myxobacteria to produce a variety of amylases. This is consistent with the results of yeast, with its complex nutritional composition, low concentration, and slow release, which is almost suitable for the growth and short-term preservation of various myxobacteria [38]. We found that yeast powder is more suitable for the growth of myxobacteria in optimizing the fermentation conditions of myxococcus. In addition, microbial growth and metabolism require a suitable carbon-nitrogen ratio. A low carbon-nitrogen ratio can lead to excessive bacterial growth, premature aging, and autolysis. A high carbon-nitrogen ratio is not conducive to bacterial reproduction, resulting in low fermentation density. We noted that both low and high concentrations of carbon and nitrogen sources reduced the biomass of strain WCH05, indicating that a suitable carbon-nitrogen ratio is beneficial to the growth and reproduction of strain WCH05. Inorganic salts provide essential mineral elements for microbial growth. Shimkets and others have reported that high concentrations of Mg²⁺ are essential for the growth of myxobacteria [38]. We also found that when MgSO₄ was used as an inorganic salt component in the fermentation medium, the biomass of strain WCH05 was higher.

The mechanism of microbial fermentation is complex, and the production of target products is not only affected by the fermentation substrate, but also by the fermentation conditions. Different bacteria have different optimal growth temperatures and pH values. pH value affects the charge of the cell membrane, the permeability of the cell membrane, and the absorption of nutrients [39]. Similarly, Wu et al. found that the optimal initial pH of the myxobacteria strain X6-II-1 against potato late blight was 7.2 and the culture temperature was 30℃ [40]. Wu et al. used a combination of single-factor experiments and orthogonal experiments to optimize the fermentation conditions of M. xanthus B25-I-1 and determined the optimal initial pH to be 7.2 and the culture temperature to be 32℃ [41]. The strain WCH05 has similar culture temperature and initial pH values to most myxobacteria. The volume of the culture medium directly affects the contact between the microbial biomass and the air and thus affects the dissolved oxygen content in the medium. The rotation speed of the shaker affects the aeration within the medium, thereby affecting the growth of microbial strains. The strain WCH05 had an optimal working volume of 40% (100/250 mL) at a rotation speed of 200 r/min. This indicates that strain WCH05 requires a smaller working volume and a higher rotation speed for production, suggesting that this strain requires higher aeration and dissolved oxygen levels during fermentation. In subsequent industrial production, it is recommended that the biomass of strain WCH05 can be increased by increasing the dissolved oxygen level and rotation speed.

The response surface methodology (RSM) is a highly suitable procedure for determining the effects of independent variables and identifying optimal conditions in multivariable systems. Single-factor experiments combined with RSM determined the optimal medium fermentation broth for strain WCH05: 8.0 g/L soluble starch, 4.0 g/L yeast extract, and 1.2 g/L MgSO₄. The optimal cultivation conditions were an incubation temperature of 30 °C, a shaking speed of 200 r/min, an initial medium pH of 7.0, a seed inoculum of 7%, a working volume of 40% (100/250 mL), and a cultivation time of 72 h. The optimized medium developed for the fire blight antagonistic strain WCH05 is simple, inexpensive, and readily available, significantly reducing fermentation costs. The shake-flask fermentation parameter model was validated through repeated fermentation experiments, achieving a dry cell weight of 3.25 g/L for strain WCH05, a 2.5-fold increase compared to the pre-optimization conditions. Pot experiments demonstrated that spraying the fermentation broth of strain WCH05 significantly reduced the incidence of fire blight. After optimization, the disease control efficacy was improved, with the undiluted fermentation broth achieving a control efficacy of over 82.6%, approaching the efficacy of streptomycin (89.0%). Even at a 50-fold dilution, the control efficacy remained above 71.1%, demonstrating promising biocontrol potential.

Myxobacteria employ diverse predatory strategies, including frontal attack [42], wolf-pack attack [43], and solitary predation [15]. Their predation relies on secondary metabolites, lytic enzymes, and outer membrane vesicles (OMVs) [44–46]. Secondary metabolites act as small-molecule weapons that penetrate prey cells to disrupt metabolism or kill them [47], while OMVs serve as short-range “transporters” delivering toxic compounds [13]. Lytic enzymes such as peptidases, proteases, and lysozymes provide the biochemical basis for predation [48]; for example, Myxococcus xanthus DK1622 secretes proteins that degrade the peptidoglycan layer of Gram-positive bacteria [12]. At high cell densities, extracellular hydrolytic enzymes aggregate, maintaining locally high concentrations that allow the population to collectively share hydrolysis products and support individual growth [36]. Likewise, Archangium sp. AC19 preys on oomycetes using a CAZyme cocktail, whose cooperative activity and effective release require high population density [49]. Predation of E. amylovora by strain WCH05 depends on direct cell contact within a biofilm formed at high density, maintaining locally elevated enzyme levels and enhancing its destructive capacity [19]. Thus, increasing WCH05 cell density in fermentation broth enhances enzyme secretion and coordination, likely a key factor underlying its improved biocontrol efficacy.

Severe epidemics of fire blight occur when periods of warm (> 15 °C), wet weather coincide with open flowers on pear or apple trees [50]. Chemical control during the flowering period is a recognized and effective technical approach for managing fire blight [51]. However, in addition to floral infection, the pathogen can also enter through developing buds, lenticels, stomata, and mechanical wounds (such as pruning cuts and insect feeding wounds). Increased rainfall and humid weather can accelerate disease spread and epidemics [2]. Therefore, post-bloom applications should be implemented based on weather conditions and disease dynamics. To ensure field control efficacy, field trials were conducted in pear orchards in Korla City in 2023. WCH05 was sprayed twice, once at the initial bloom stage (30% flowering) and again at the petal fall stage (80% petal fall). In the first field survey conducted on May 4, fermentation broth of strain WCH05 achieved a control efficacy of 83.3%. From May 5 to May 7, Korla City experienced a sudden temperature drop accompanied by sleet (Fig. 5A–C). To prevent potential exacerbation of fire blight due to frost damage, WCH05 fermentation broth was applied again on May 9. In the second field survey on May 18, the control group showed a marked increase in disease incidence and severity, likely due to the cold and rainy weather, whereas the WCH05-treated group maintained a control efficacy of 81.5%. In 2024, temperatures in Korla were relatively stable and rainfall was low, leading to a gradual reduction in fire blight in the control group. Accordingly, WCH05 fermentation broth was applied only once at the initial bloom and once at the petal-fall stages. Over two consecutive months of monitoring, the control efficacy of WCH05 remained above 81.0%. In early June 2024, increased rainfall in Zhangye City (Fig. 5B) prompted another application of WCH05 fermentation broth on June 8. The third field survey on June 10 showed that WCH05 achieved a control efficacy of 89.7%. By the fourth survey on June 24, disease severity had increased, likely due to prior rainfall, resulting in a slight reduction in WCH05 efficacy, which remained at 82.5%. These results indicate that fluctuations in temperature and humidity are major factors influencing the field performance of biocontrol agents [52]. Across two years of trials in three pear orchards, despite differences in regional climate, cultivar, and planting practices, WCH05 fermentation broth (50-fold dilution) consistently and significantly reduced disease incidence, maintaining a stable control efficacy above 80%. The control efficacy against fire blight was superior to Kasugamycin and comparable to the biocontrol strain Pantoea agglomerans RK-84 and the commercial biocontrol product Serenade Optimum™ (Bacillus subtilis QST713) [53]. These results not only demonstrate the application potential of myxobacterial biocontrol agents in pear production but also provide a valuable reference for developing technical guidelines for the application of myxobacterial agents for fire blight control in the future.

Although strain WCH05 has demonstrated strong potential for fire blight biocontrol, the tendency of myxobacteria to aggregate into clumps during growth somewhat limits their practical application and large-scale production. Therefore, enhancing cell dispersion during myxobacterial growth is a critical challenge to address in future research. Furthermore, in-depth investigations into its persistence, environmental adaptability, and impact on the host microbiome will contribute to the development of green, efficient, and sustainable fire blight management strategies.

Conclusion

This study aimed to enhance the biomass production of strain WCH05 by optimizing the liquid fermentation process through single-factor experiments, Plackett-Burman screening, and Box–Behnken design response surface methodology. The optimized medium composition for strain WCH05 was determined to be: 8.0 g/L soluble starch, 4.0 g/L yeast extract, and 1.2 g/L MgSO₄. The optimal cultivation conditions were an initial pH 7.0, a working volume of 40% (100 mL/250 mL), a shaking speed of 200 r/min, an incubation temperature of 30 °C, an inoculum size of 7%, and a cultivation time of 72 h. Under these optimized conditions, the dry cell weight of strain WCH05 reached 3.25 g/L, representing a 2.5-fold increase compared to the pre-optimization level of 1.30 g/L. In pot assays using P. betulifolia seedlings, the protective efficacy of the strain WCH05 fermentation broth against fire blight was 86.22% (7 dpi) and 82.57% (14 dpi), both significantly higher than that of the pre-optimized broth. Furthermore, this study demonstrated the field efficacy of strain WCH05 in controlling fire blight in pear orchards, consistently achieving control efficacy exceeding 80%. These findings strongly suggest that strain WCH05 holds considerable promise as a viable biocontrol agent for fire blight management.

Authors’ contributions

WJ: Investigation, analysis, draft and editing. ZD: Field trials. ML: Funding and resources. BF: Analysis, review and editing. QS: Field trials and resources. JH: Conceptualization, Writing- original draft and review.

Funding

Autonomous region Key R & D Program of Xinjiang, China (Grant No. 2024B04030).

Key Project of Natural Science Foundation of Xinjiang Uygur Autonomous Region (Grant no. 2021D01D12).

National Key R&D Program of China (Grant no. 2021YFD1400200).

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Competing interests

The authors declare no competing interests.