Soil samples were obtained from tobacco fields in Xuan’en County, Hubei Province (29.97°N, 109.38°E). These fields had a history of continuous cultivation of tobacco (Yunyan 87) for more than 15 years. Each area consisted of one block of suppressive soil (SS) and one block of conducive soil (CS). The rhizosphere soil of tobacco plants was collected using the five-point sampling method, 70 days after tobacco transplantation. A total of 30 soil samples were collected from the different areas. After collection, the samples were mixed thoroughly and transported back to the laboratory on dry ice to maintain their freshness. Subsequently, the samples were stored in a -80°C freezer for further experiments, including PCR amplification and high-throughput sequencing of soil bacteria. The rhizosphere soil was sent to Majorbio Gene Co., Ltd (Shanghai municipality, China) for sequencing analysis. Total DNA was extracted from the soil using the DNeasy PowerSoil Pro Kit, and this DNA was used as a template for further analysis (The raw data has been uploaded to NCBI, https://www.ncbi.nlm.nih.gov/, BioProject Number: PRJNA1089359). The specific sequencing methods and data processing are in the Supplementary Materials and Methods S1

First, a 10g sample of field tobacco rhizosphere soil was weighed and placed in a triangular bottle containing 90 mL of sterile water. The mixture was then shaken at 28°C and 150 r/min for 20 minutes, resulting in the preparation of a soil suspension stock (Cui et al., 2020). This stock was further diluted to different concentrations (10^-2, 10^-3, 10^-4, 10^-5) using a 10-fold gradient. Next, 100 μL of the soil suspensions at different concentrations were absorbed and coated onto 2,3,5-triphenyl tetrazolium chloride (TTC) agar (Kelman, 1954), which had been pre-mixed with R. solanacearum (GenBank: OR711027) obtained from the Research Laboratory of Plant-Microbial Interaction in the College of Agriculture, Yangtze University, Jingzhou, China. Each concentration was treated three times to ensure accuracy and reliability. The coated plates were incubated in the dark at 28°C for 2 days. After incubation, the plates were examined for the presence of an inhibitory zone. BCAs that exhibited inhibitory activity, as indicated by the presence of an inhibitory zone, were selected as the test strains for further investigations.

First, the pH of the nutrient broth (NB) was titrated to 4.0, 5.0, 6.0, and 7.0 using an acid-base buffer. The medium was then sterilized at 121°C for 20 minutes. Next, the antagonistic strains were inoculated into NB with different pH values, while R. solanacearum was inoculated into NB (pH 7.0). The cultures were incubated with shaking at 28°C and 150 r/min for 48 h. The concentration of BCAs and R. solanacearum fermentation broth was adjusted to 10⁸ CFU/mL. To assess the inhibitory effect of the fermentation broth on R. solanacearum, 200 µL of R. solanacearum fermentation broth was mixed with 100mL (50°C) of TTC medium using the agar diffusion method (Ma et al., 2018). The mixture was thoroughly mixed and poured into plates. Using a hole puncher, a 5 mm diameter hole was made in the center of each plate. Each hole was then filled with 200 µL of antagonistic bacterial fermentation broth. This process was repeated three times for each treatment, with an equal amount of NB used as a control. The plates were incubated at 28°C for 48 h, and the diameter of the inhibition zone was measured. The width of the inhibition zone determined the inhibitory effect of the antagonistic bacterial fermentation broth at different pH levels on R. solanacearum.

To further investigate the antibacterial activity of the antagonistic strains, the fermentation filtrate (FL) was tested for its inhibitory effect under acidic conditions. The fermentation broths of the antagonistic strains, prepared as described earlier with different pH values, were centrifuged at 8000 r/min for 5 minutes at 4°C. The resulting supernatant was then filtered through a microporous filter (0.22 mm) to remove any bacterial cells, obtaining a sterile filtrate. The inhibitory effect of the FL on R. solanacearum was determined by measuring the width of the inhibition zone, following the same procedure mentioned earlier for the fermentation broth bacteriostatic method.

Tobacco seeds (Yunyan 87) were planted in plastic pots filled with tobacco field soil in Xuan’en County, Enshi City, Hubei Province. Once the tobacco seedlings reached the 3-leaf stage and showed consistent growth, they were transplanted into new plastic pots and continued to be cultivated until the 6-8 leaf stage for experimental treatment. The B4-7 fermentation broth was diluted with NB to concentrations of 1×10⁸ CFU/mL (P₃), 1×10⁷ CFU/mL (P₂), and 1×10⁶ CFU/mL (P₁). Then, 20 mL of the B4-7 fermentation broth was inoculated into the rhizosphere of the seedlings using the root irrigation method. Each treatment consisted of 30 tobacco plants, and the experiment was repeated 3 times. As a positive control, 20 mL of Streptomycin (100 mg/L, Solarbio) was inoculated, while 20 mL of NB was used as a negative control. Two days after the application of the B4-7 fermentation broth, 20 mL of R. solanacearum fermentation broth (1×10⁸ CFU/mL) was irrigated in the rhizosphere of the tobacco seedlings. All the tobacco seedlings were then placed in a greenhouse with a relative humidity of 70-80% and a temperature of 30 ± 2°C for further cultivation. After 14 and 21 days of inoculation with R. solanacearum, the disease severity of the TBW was assessed based on the rating scale developed by Li et al. (2020). Disease index (DI) was calculated using the formula DI = Σ(r × n)/(N × 9)×100. Here, ‘r’ represents the rating scale of disease severity, ‘n’ represents the number of infected tobacco plants with a rating of ‘r’, and ‘N’ represents the total number of tobacco plants tested. To determine the biocontrol efficiency (BE) of the treatment, the formula [(Disease index of control - Disease index of treated group)/Disease index of control]×100% was used.

This study aimed to determine the growth promotion effect of antagonistic strains on tobacco under indoor pot conditions. Tobacco field soil was mixed with the fermentation broth B4-7 to achieve bacterial concentrations of 1.0×10⁸ CFU/g (Q₃), 1.0×10⁷ CFU/g (Q₂) and 1.0×10⁶ CFU/g (Q₁). The tobacco seedlings were cultivated using the described method until they reached the three-leaf stage, and seedlings with the same size and growth were selected for transplantation. Each treatment was replicated three times, with each replicate consisting of 20 tobacco seedlings. Soil mixed with NB served as the control, while Bacillus amyloliquefaciens YZU-SG146 was used as a positive control (Liu et al., 2023). The tobacco seedlings were placed in a greenhouse with a relative humidity of 70~80% and a temperature of 30 ± 2°C for continuous cultivation, and their growth was monitored daily. Measurements of growth parameters, including plant height, root length, fresh weight, dry weight, stem diameter, and chlorophyll content (Chlorophyll analyzer TYS-3N; Beijing Zhongke Weihe Technology Development Co., LTD), were recorded after 10, 20, and 30 d.

The experiment was conducted in Xuan ‘en County, Enshi City, Hubei Province, at a tobacco field severely affected by bacterial wilt (29.97°N, 109.38°E). The experimental site consisted of three blocks, each covering an area of 260 m². Within each block, there were two plots measuring 130 m² each, following a completely randomized block design. One plot represented the B4-7 treatment, while the other served as the control. Tobacco plants were grown in a monocropping system, with a spacing of 0.55 m between plants within a row and 1.2 m between rows. Healthy tobacco seedlings were cultivated in a greenhouse until they reached the nine-leaf stage, after which they were transplanted into the field. The seedlings were inoculated with B4-7 fermentation broth, containing a concentration of 1×10⁸ CFU/mL, at 30 and 45 d after transplanting. Each plant was irrigated with 100 mL of the B4-7 fermentation broth, while the control group received NB as the irrigation solution. At 60 and 75 d after transplanting, the severity of TBW was assessed using a disease severity rating scale, and the disease index was calculated accordingly referred to Section 2.5. After the tobacco plants were harvested, yield data were collected for all plots. The actual yield of each plot was determined by weighing the dry tobacco leaves.

Strain B4-7 was activated on nutrient agar (NA) plate, inoculated into 50 mL NB, incubated at 28°C at 130rpm for 24h, and sent to Benagen corporation (Wuhan, Hubei, China) for whole genome sequencing (GenBank ID: CP080760). The experimental process was carried out according to the standard protocol provided by Oxford Nanopore Technologies (ONT), including sample quality inspection, library construction, library quality inspection and library sequencing. Sequencing was performed using Next-Generation sequencing (NGS) from the Illumina MiSeq sequencing platform and real-time electrical signal sequencing from Nanopore sequencing technology. After filtering the raw data, short fragments and low quality data, the filtered reads were assembled using unicycler(0.4.8) software. The prediction of coding genes was carried out by prokka software, which used prodigal to predict coding genes, including tRNA, rRNA, miscRNA, and the preliminary annotation was completed after the summary of various predicted genetic elements. The Genome BLAST Distance Phylogeny approach (GBDP) between B4-7 and homologous strains was calculated based on the B4-7 16S rDNA gene (GenBank ID: OM370806), and a phylogenetic tree was constructed using FastME 2.1.6.1 software. digital DNA-DNA hybridization (dDDH) values of B4-7 and other homologous strains were calculated using GGDC3.0 software. Through online services JSpeciesWS platform (https://jspecies.ribohost.com/jspeciesws/#home) B4-7 compare with other genome Average Nucleotide Identity (ANI) (Chun et al., 2018). The predicted gene sequences were BLAST compared with the functional databases of Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Clusters of Orthologous Group (COG) to obtain the gene function annotation results (Ogata et al., 1999; Tatusov et al., 2000). Using circlize in the R package, the predicted genomic information, such as sequencing depth, GC distribution and genome structure annotation were mapped into the genome circle. Biosynthetic gene clusters (BGCs) were identified by the online antiSMASH software (Weber et al., 2015).

At 60 and 75 days after transplanting, rhizosphere soil samples were collected from five separate sites within each plot to evaluate disease severity. A total of six soil samples, each weighing 150~200 g, were collected by mixing the samples from the five sites within each plot. Each set of soil samples was then divided into two sub-samples for further analysis. One sub-sample (only the soil samples from 75 days) was sent to Majorbio Gene Co., Ltd for sequencing analysis of fungi and bacteria (BioProject Number: PRJNA1093021). The specific sequencing methods and data processing are in the Supplementary Materials and Methods S1 . The other sub-sample was used for quantitative real-time (qPCR) to quantify the presence of R. solanacearum by specific primers specific primer combination of 199F (5’-AGTAACTCGGCTGTTTTTTT-3’) and 199R (5’-TATTGCTTGACCTATAA-3’). The specific methods is in the Supplementary Materials and Methods S2 .

After inoculating the tobacco plants with the R. solanacearum in a greenhouse, the third to fifth unfolded leaves of each plant were collected from top to bottom every 48 hours, for a total of three collections. The collected leaves were immediately stored at -80°C for further analysis. The activities of several defense enzymes, including phenylalanine ammonia-lyase (PAL), peroxidase (POD), catalase (CAT), polyphenol oxidase (PPO), and superoxide dismutase (SOD), in the leaves under each treatment were determined. For comparison, the treatments included inoculation with the pathogenic bacteria as a disease control group, inoculation with NB as a healthy control group. The extraction of the defense enzyme solution and the determination of its activity were conducted using a kit from Solarbio, following the instructions provided (Zhao et al., 2020).

1L FL of B4-7 was prepared referred to Section 2.3. After the supernatant of B4-7 was freeze-dried, resulting in a flocculent solid, the solid was dissolved by adding 100 mL of sterile distilled water to the mixture. The mixture was then transferred to a liquid separation funnel, and an equal amount of ethyl acetate was added. The mixture was shaken and mixed thoroughly. The mixture was left undisturbed to allow complete stratification. During this process, a clear separation occurred between the upper organic phase and the lower aqueous phase. The upper organic phase was carefully collected, while the lower aqueous phase was retained. The lower aqueous phase was subjected to further extraction by adding ethyl acetate. This extraction process was repeated three times, with each extraction carried out for approximately 12 hours. The organic phases obtained from the three extractions were combined, resulting in a merged organic phase. The merged organic phase was then concentrated using a rotary evaporator set at 50°C. The rotary evaporation process removed the solvent, leaving behind a dried crude extract. After the solvent has been completely removed, the dried crude extract was dissolved in a small amount of chromatograph-grade methanol. Finally, the dissolved crude extract was stored in a refrigerator at 4°C for future use.

After the FL of B4-7 was processed and the crude extract was obtained, the extract was further diluted with methanol to several concentrations: 50μg/mL, 100μg/mL, 200μg/mL, and 500μg/mL. To evaluate the antimicrobial activity of the crude extract, a TTC agar was prepared by adding 200µL of R. solanacearum fermentation broth into 100mL of TTC agar at 50°C. The medium was then cooled. Symmetrical holes with a diameter of 5 mm were created at a distance of 25mm from the center of the TTC medium plate. Each hole was injected with 150 µL of the different concentrations of the crude extract solutions. This procedure was repeated three times for each treatment. Methanol was used as a control. All the TTC plates, including the control, were transferred into a 28°C incubator. After two days of incubation, the diameter of the inhibition zones, which indicates the growth inhibition of pathogens, was measured using a vernier caliper.

In addition to evaluating the antimicrobial activity of the crude extract at different concentrations, further experiments were conducted to investigate the effect of different temperature treatments on the extract’s potency. The crude extract, prepared at a concentration of 500 μg/mL, was divided into several equal parts and subjected to various temperature treatments: (a) Water bath at 25°C for 30 min; (b) Water bath at 40°C for 30 min; (c) Water bath at 60°C for 30 min; (d) Water bath at 80°C for 30 min; (e) Water bath at 100°C for 30 min; (f) Treatment with a sterilized pot at 121°C for 30 min. Perforated plates were prepared using the same method as before, and each hole was injected with 150 μL of the crude extract solution that underwent a different temperature treatment. This process was repeated three times for each treatment. All the plates, including the control, were then incubated at 28°C. After two days of incubation, the diameter of the inhibition zones was measured using a vernier caliper.

The composition of lipopeptide-producing active substances of strain B4-7 was analyzed using high-resolution liquid chromatography-mass spectrometry (LC-MS). The specific methods is in the Supplementary Materials and Methods S3 .

To compare the bacterial communities between suppressive soil (SS) and conducive soil (CS), rhizosphere soil samples were collected from fields in Enshi county. Illumina MiSeq sequencing was conducted to analyze the soil microbiome. Rarefaction curve analysis was performed to evaluate the reasonableness of the sequencing depth. As shown in Supplementary Figure S1A , although the curve did not reach a final plateau, it flattened out when the sequencing depth reached 40,000, indicating that increasing the sequence number would not result in the emergence of new Operational Taxonomic Units (OTUs). The sequencing depth was sufficient to represent the microbial community in these environments. According to Venn analysis, there were 1,964 bacterial OTUs shared by both SS and CS, with 1,017 endemic OTUs found in SS and 441 endemic OTUs in CS. The number of endemic OTUs in SS was 2.31 times higher than that in CS ( Figure 1D ). According to Shannon and Chao indices, the richness of bacteria in SS increased significantly compared with CS, but there was no significant difference in diversity ( Figures 1A, B ). Based on the results of the PCoA with the Bray-Curtis measures, SS and CS explained 82.32% of the total bacterial community variation in PC1 and PC2. Although there was significant separation on PC1 axis, combined with Beta diversity difference analysis. (Student′s t-test, p < 0.05), there was no significant difference in species diversity between SS and CS ( Figure 1E ).

The relative species abundance at the taxonomic level of SS and CS phylum is shown in Figure 1C , the dominant microflora at the phylum level in SS includes Proteobacteria (40.59%), Actinobacteriota (22.11%), Chloroflexi (10.92%), Bacteroidota (7.82%), Firmicutes (5.59%), Acidobacteriota (3.63%), Patescibacteria (2.23%), Gemmatimonadota (2.17%) and Cyanobacteria (1.79%). In CS, the dominant microflora at the phylum level consists of Proteobacteria (41.1%), Actinobacteriota (22.77%), Chloroflexi (9.97%), Bacteroidota (11.56%), Firmicutes (3.34%), Acidobacteriota (2.47%), Patescibacteria (2.74%) and Gemmatimonadota (1.07%). These results indicate clear differences in the abundance of Bacteroidota, Acidobacteriota, Firmicutes, and Gemmatimonadota between SS and CS. Compared to CS, the relative abundance of Firmicutes, Acidobacteriota, and Gemmatimonadota in SS increased by 67.19%, 46.52%, and 108.16%, respectively. The relative abundance of Bacteroidota in SS decreased by 32.38%. In the Heatmap ( Supplementary Figure S2 ), the relative abundance of soil bacterial communities is depicted using a color gradient from red to white to blue, indicating high to low abundance, respectively. Compared with CS, the abundance of Sphingobacterium (p < 0.05), Bacillus (p < 0.001), Streptomyces (p < 0.05), Chujaibacter (p < 0.01), and Sporosarcina (p < 0.001) increased significantly, while the abundance of Ralstonia (p < 0.05), Chryseobacterium (p < 0.01), Achromobacter (p < 0.05), Pseudomonas (p < 0.001), and Paenibacillus decreased significantly.

Forty-five isolates were obtained from disease-suppressive soil. Among these isolates, only six of them showed inhibitory effects on R. solanacearum. These six isolates were then inoculated into NB with different pH values to examine the effects of bacterial fermentation broth and fermentation filtrate (FL) on R. solanacearum in a dual-culture experiment. It was observed that compared to the other five strains, the isolate B4-7 fermentation broth exhibited the strongest antibacterial ability under different pH conditions ( Figure 2A, B ). Further analysis of the data revealed that under the conditions of pH 4.0, pH 5.0, pH 6.0, and pH 7.0, the inhibitory band widths of the fermentation broth of B4-7 against R. solanacearum were measured to be 26.36 mm, 26.61 mm, 26.48 mm, and 26.70 mm, respectively ( Figure 2C ). Similarly, the inhibitory band widths of the FL of B4-7 against R. solanacearum under these pH conditions were recorded as 20.61 mm, 20.84 mm, 20.87 mm, and 21.08 mm, respectively ( Figure 2D ). Furthermore, it was observed that under different pH conditions, the antibacterial effects of B4-7 fermentation broth and FL on R. solanacearum were not significantly different.

In the greenhouse experiment, tobacco plants were inoculated with the R. solanacearum and treated with different treatments including B4-7 fermentation broth and streptomycin. After 14 d of inoculation with R. solanacearum, the disease index of tobacco plants treated with B4-7 fermentat broth (at concentrations P₁, P₂, and P₃) ranged from 13.32 to 20.88. On the other hand, the disease index of tobacco plants treated with streptomycin was 10.08. The control effects of the B4-7 fermentation broth ranged from 43.69% to 72.82%, indicating a reduction in disease severity compared to the control group. After 21 days of inoculation, the disease index of tobacco plants treated with B4-7 fermentation broth ranged from 18.36 to 35.34. The disease index of tobacco plants treated with streptomycin was 16.92. The control effects of the B4-7 fermentation broth ranged from 45.30% to 74.03%, again showing a reduction in disease severity compared to the control group. Specifically, when the concentration of B4-7 fermentation broth was 1×10⁸ CFU/mL, there was no significant difference in its control effect compared to streptomycin ( Table 1 ; Supplementary Figure S3 ).

B4-7 can substantially promote the growth of tobacco seedlings ( Supplementary Figure S4 ). When different concentrations of B4-7 fermentation broth (Q₃, Q₂, and Q₁) were applied, the seedlings showed remarkable growth compared to the control. Specifically, the increases were as follows: plant height by 58.05%, 49.73%, and 8.76%; root length by 28.37%, 22.21%, and 2.17%; fresh weight by 36.93%, 23.48%, and 5.87%; dry weight by 86.36%, 59.09%, and 9.09%; stem diameter by 29.63%, 17.99%, and 2.65%; and chlorophyll content by 48.06%, 40.19%, and 14.12%, for Q₃, Q₂, and Q₁ respectively. The growth indices of tobacco seedlings treated with B4-7 were found to be similar to those treated with YZU-G146, showing no significant difference ( Table 2 ).

The disease index and the quantity of rhizosphere R. solanacearum were evaluated after 60 and 75 days of tobacco transplantation. The R. solanacearum DNA amplification of tobacco rhizosphere was detected using qPCR, which has a sensitivity 1000 times greater than conventional PCR ( Supplementary Figures S5A and S5C ). The dissolution curves were unimodal ( Supplementary Figure S5B ), indicating no specific amplification at each concentration. The standard curve relating the concentration of R. solanacearum and the Ct value was established based on the amplification curve and used to calculate the concentration of R. solanacearum in the soil ( Supplementary Figure S5D ). After 60 days post transplantation, the disease index of TBW following B4-7 treatment was 3.14, biocontrol efficiency (BE) of 56.27% ( Figure 3 ). Furthermore, the concentration of rhizosphere R. solanacearum was 2.07×10³ CFU/g, a drop of 78.81% in comparison to the control ( Figure 4 ). After 75 days post transplantation, the disease index of TBW following B4-7 treatment was 23.18, with a control effect of 46.88% ( Figure 3 ). The concentration of rhizosphere R. solanacearum stood at 1.32×10⁵ CFU/g, representing a reduction of 96.91% relative to the control ( Figure 4 ). At the time of tobacco harvest, the yield of tobacco treated with B4-7 root irrigation was 326 kg/ha, representing an enhancement in yield by 35.27% compared to the control ( Figure 3 ).

After sequencing and assembly, the genome of B. velezensis B4-7 consisted of 3,926,832 bp and had 46.5% of GC content. The genome contained 27 rRNA genes, 86 tRNA genes, and 3743 coding sequences ( Supplementary Figure S6 ). By using the Type Strain Genome Database (https://gctype.wdcm.org/), 13 strains homologous to B4-7 were obtained. The ANI value of B4-7 only exceeds 95% with that of B.velezensis FZB42 and B. velezensis NJN-6, indicating that B4-7 belongs to B. velezensis ( Supplementary Figure 7 ). By annotation, 55.29%, 74.87% and 63.73% of genes were assigned to three categories of KEGG, GO, and COG, respectively. KEGG Pathway is the most commonly used KEGG database, and the number of genes matched by B4-7 in the KEGG pathway is 1177, accounting for 29.81%. The collection of metabolic pathways of B4-7 mainly includes five categories: cellular processes, environmental information processing, genetic information processing, melabalism and organismal systems ( Supplementary Figure S8 ). Among them, 387 and 283 genes were involved in carbohydrate metabolism and amino acid metabolism, and 189 genes were involved in the metabolism of lipid, terpenoids and polyketides, as well as the biosynthesis of other secondary metabolites, including genes related to the biosynthesis of antibacterial active substances secreted by this strain. For COG annotation, the five groups with the largest proportion of genes are 263 genes involved in amino acid transport and metabolism [E], 202 genes involved in translation (ribosomal structure and biogenesis) [J], 199 genes involved in carbohydrate transport and metabolism [G], 183 genes involved in transcription [K], and 219 genes involved in general function prediction only [R]. Notably, 184 of genes were clustered into unknown function category [S] ( Supplementary Figure S9 ). A total of 2956 genes were annotated into biological process (1,098), cellular component (2,168), and molecular function (1,989) using the GO database ( Supplementary Figure S10 ).

The antiSMASH software was used to predict the gene clusters encoding secondary metabolites in the genome of strain B4-7. The predicted 12 BGCs included NRPS (non-ribosomal peptide synthetase), PKS (polyketide synthase), terpene, lanthipeptide-class-ii ( Supplementary Table S1 ). Six BGCs showed more than 100% of similarity with macrolactin H, bacillaene, fengycin, difficidin, bacillibactin and bacilysin. One BGC showed more than 80% of similarity with surfactin ( Figure 5 ). In addition, four unknown BGCs suggests that several novel secondary metabolites could be produced by strain B4-7.

Post freeze-drying, organic solvent extraction, and rotary evaporation, the lipopeptide active substances produced by the B4-7 strain were acquired. The antibacterial activity of these active substances was tested after they were dissolved in methanol. The findings revealed that the B4-7 strain’s lipopeptide active substances had robust antibacterial activity. The antibacterial bandwidths at concentrations of 50 μg/mL, 100 μg/mL, 200 μg/mL, 500 μg/mL, and 1000 μg/mL were 15.81 mm, 18.22 mm, 21.32 mm, 22.91 mm, and 24.02 mm, respectively ( Figure 6 ). The crude extract’s concentration was adjusted to 500 µg/mL; it underwent temperature treatment by water bath heating and sterilization at 121°C. The crude extract’s antibacterial effects at various temperatures post treatment with the B4-7 active substance were tested using a plate drilling experiment. The results suggested that the antibacterial zone diameter of the crude extract did not markedly change when the temperature was set between 25°C and 80°C, averaging at 22.75 mm. However, when the temperatures were raised to 100°C and 121°C, the inhibition zone diameters were 19.87mm and 16.35mm, respectively ( Figure 6 ).

The findings of the LC-MS analysis revealed that the crude extract of the B4-7 strain consisted of various organic compounds. Among these, the compounds with a high match degree were found to include microlactin (microlactin A, microlactin E), difficidin, bacilysin, surfactin (surfactin A, surfactin B, and surfactin C), bacillaene, Pachymic acid, Benzoylmesaconine, Troxerutin, and 3,4’,5-Trimethoxy-trans-stilbene, among others ( Table 3 ; Supplementary Figure S9 ).

The changes in the activities of POD, PPO, PAL, CAT and SOD content in the leaves of tobacco post B. velezensis B4-7 fermentation broth root treatment was showed in Figure 7 . The POD, PPO, PAL and CAT showed a pattern initially increasing and then declining. The defense enzymes of different concentrations of B4-7 fermentation broth were significantly more substantial than those in the healthy and diseased controls. PAL and CAT activities peaked on the fourth day post-root irrigation, while POD, PPO and SOD activities peaked on the sixth day. At the peak of the defensive enzyme activity of tobacco leaves treated with 10⁸ CFU/mL B4-7 fermentation broth, PAL activity was noted to be 106.56 U·g^-1 _·min^-1·FW, an increase of 33.42% and 81.42% compared to the disease control and healthy control respectively. CAT activity was 3.45×10³ U·g^-1 _·min^-1·FW, an increase of 121.15% and 69.19% relative to the disease control and healthy control. POD activity was 6.24×10³ U·g^-1 _·min^-1·FW, an increase of 106.22% and 36.75% compared to the disease and healthy controls. PPO activity was 135.56 U·g^-1 _·min^-1·FW, an increase of 162.66% and 40.84% compared to the disease and healthy controls. SOD activity reached 135.36 U·g^-1 _·min^-1·FW, an increase of 72.52% and 47.45% relative to the disease control and healthy control.

To explore the influence of B4-7 on the tobacco field’s rhizosphere microbial community structure, total DNA was extracted from soil and analyzed through Illumina MiSeq. The effective sequences in the B4-7 treated soil and control soil (CK) bacteria sequencing results were 5,6157 and 3,7293, respectively. The sequencing depth was sufficient to represent the microbial community in these environments ( Supplementary Figure S1B ). According to Shannon and Chao indices, the abundance of bacteria in B4-7 increased significantly compared with CK, but there was no significant difference in diversity ( Figures 8A, B ). Based on the results of the PCoA with the Bray-Curtis measures, B4-7 and CK explained 80.03% of the total bacterial community variation in PC1 and PC2. Although there was significant separation on PC1 axis, combined with Beta diversity difference analysis, there was no significant (Student’ s t-test, p > 0.05) difference in species diversity between CK and B4-7 ( Figure 8C ). The composition of soil bacteria at the phylum level showed differences between the B4-7 treatment soil and the control soil. Abundance of phyla such as Proteobacteria, Actinobacteriota, Chloroflexi, Firmicutes, and Acidobacteriota exceeded 5% in both soils. Meanwhile, the abundance of Gemmatimonadota, Bacteroidota, Myxococcota, and Patescibacteria fell within the range of 1% to 5% in both soils. Comparatively, the relative abundances of Firmicutes and Myxococcota in the CK decreased by 67.73% and 11.13% respectively ( Figure 8D ). At the Genus level, the abundances of Bacillus (p < 0.001), norank_f:Gemmatimonadaceae (p < 0.01), Anoxybacillus (p < 0.001), Brevibacillus (p < 0.001), and Streptomyces (p < 0.05) significantly increased in the B4-7 compared to the CK ( Figure 8E ).

The effective sequences in the fungal sequencing results were 86939 and 86491 for the B4-7 and CK respectively. The sequencing depth was sufficient to represent the microbial community in these environments ( Supplementary Figure S1C ). According to Shannon and Chao indices, the diversity of fungal in B4-7 increased significantly compared with CK, but there was no significant difference in abundance ( Figures 9A, B ). Based on the results of the PCoA with the Bray-Curtis measures, B4-7 and CK explained 82.26% of the total bacterial community variation in PC1 and PC2. Combined with Beta diversity difference analysis, there was significant (Student′s t-test, p < 0.05) difference in species diversity between CK and B4-7 ( Figure 9C ). At the phylum, the abundance of Ascomycota, Mortierellomycota, Basidiomycota, and unclassified_k:Fungi exceeded 1%. The abundance of Rozellomycota, Chytridiomycota, Glomeromycota, Kickxellomycota, Zoopagomycota, Monoblepharomycota in both soils was less than 1% ( Figure 9D ). At the genus level, the abundances of Mortierella (p<0.01), unclassified_f:Didymellaceae (p<0.01), Didymella (p<0.001), Lectera (p<0.01), and Gibellulopsis (p<0.01) significantly increased in the B4-7 compared to CK. The abundance of unclassified_o:Pyxidiophorales (p<0.01) and Fusarium (p<0.01) were significantly reduced in B4-7 compared to CK ( Figure 9E ).