Skip to main content

Complete genome sequence of Bacillus velezensis strain Ag109, a biocontrol agent against plant-parasitic nematodes and Sclerotinia sclerotiorum

Abstract

Soybean is the main oilseed cultivated worldwide. Even though Brazil is the world’s largest producer and exporter of soybean, its production is severely limited by biotic factors. Soil borne diseases are the most damaging biotic stressors since they significantly reduce yield and are challenging to manage. In this context, the present study aimed to evaluate the potential of a bacterial strain (Ag109) as a biocontrol agent for different soil pathogens (nematodes and fungi) of soybean. In addition, the genome of Ag109 was wholly sequenced and genes related to secondary metabolite production and plant growth promotion were mined. Ag109 showed nematode control in soybean and controlled 69 and 45% of the populations of Meloidogyne javanica and Pratylenchus brachyurus, respectively. Regarding antifungal activity, these strains showed activity against Macrophomia phaseolina, Rhizoctonia solani, and Sclerotinia sclerotiorum. For S. sclerotiorum, this strain increased the number of healthy plants and root dry mass compared to the control (with inoculation). Based on the average nucleotide identity and digital DNA-DNA hybridization, this strain was identified as Bacillus velezensis. Diverse clusters of specific genes related to secondary metabolite biosynthesis and root growth promotion were identified, highlighting the potential of this strain to be used as a multifunctional microbial inoculant that acts as a biological control agent while promoting plant growth in soybean.

Peer Review reports

Introduction

Soybean (Glycine max (L.) Merr.) is considered the main oilseed cultivated in the world, with a total of 375 Mt of grain produced in 2023 (USDA – United States Department of Agriculture). Brazil produced approximately 142 Mt, with an increase of ~ 7.12 Mt year−1 and 91.41 kg ha year−1 during the last ten years (CONAB – Companhia Nacional de Abastecimento 2023). However, even with this favorable scenario, soybean yield and its expansion to new areas are severely affected by the restrictions imposed by biotic and abiotic factors [1,2,3].

Plant-parasitic nematodes are significant constraints to soybean production worldwide, accounting for a projected loss of $78 billion annually worldwide, with an average yield loss of 10–15% in soybean [4]. In Brazil, the main nematodes species that attack the soybean crop are root-knot nematodes (Meloidogyne javanica and M. incognita), cyst nematodes (Heterodera glycines), reniform nematodes (Rotylenchulus reniformis), and the root lesion nematode (Pratylenchus brachyurus) [5,6,7]. Other soilborne pathogens have also caused significant damage, such as white mold (Sclerotinia sclerotiorum) [8], root rot (Rhizoctonia solani) [9], charcoal rot (Macrophomina phaseolina (Tassi) Goid) [10], and sudden death syndrome (Fusarium sp.) [11]. It is estimated that approximately 30% of the Brazilian soybean area (~ 10 million ha) is infested with S. sclerotiorum, causing annual economic losses estimated at US$ 1.47 billion due to yield reduction and fungicide costs [12].

Controlling soil diseases poses significant challenges due to their diverse pathogens, resilient survival mechanisms, and dependence on complex soil ecology and environmental factors, necessitating multifaceted and adaptive management strategies for effective mitigation. Therefore, it is essential to carry out integrated management, which includes the rotation or succession of non-host crops, resistant or tolerant cultivars, and chemical and biological controls [13,14,15]. Biological control is increasingly favored for mitigating soil pathogens, owing to its effective suppression capabilities, minimal environmental footprint, and beneficial impacts on plants, including the induction of both local and systemic resistance as well as promotion of plant growth [16,17,18]. Furthermore, developing a commercial biological product costs 75 times less than developing a synthetic chemical [19].

In Brazil, there is a remarkably growth in the number of biological products for plant disease control, highlighting the genus Bacillus (https://agrofit.agricultura.gov.br/agrofit_cons/principal_agrofit_cons). Bacillus spp. represent a large group of gram-positive bacteria that belong to the phylum Firmicutes. It has been prominent in agriculture due to its diverse secondary metabolism and ability to produce various antagonist substances with different structures [20, 21]. For example, B. velezensis FZB42 has approximately 8% of its genome related to secondary metabolite production, including bacteriocins, antimicrobial peptides and lipopeptides, polyketides, and siderophores, which show plant growth-promoting properties [22, 23].

Considering the advances in biological control in recent years and the increased demand for these products in the market, this study aimed to evaluate the potential of the isolate Bacillus velezensis Ag109 as a biocontrol agent against soil pathogens in soybean, especially M. javanica, P. brachyurus e S. sclerotiorum. In addition, we sequenced the genome of Ag109 and mined the genes related to secondary metabolite synthesis and plant growth promotion.

Material and methods

Origin of the Ag109 strain

The bacterial strain Ag109 belongs to the AgBio company’s collection of microorganisms. The bacterium was isolated from the rhizospheric soil of maize harvested in Italva, Rio de Janeiro, Brazil. Its selection for this study was informed by earlier screenings among various bacterial isolates, which identified its antifungal activity and swarming ability.

In vivo studies against Meloidogyne javanica and Pratylenchus brachyurus under greenhouse conditions

To evaluate the biocontrol activity of Ag 109 against M. javanica and P. brachyurus, two experiments were conducted for each pathogen at the Institute of Rural Development of Paraná (IDR-Paraná). For these experiments, seeds of the soybean cv. Bônus were used. The seeds were disinfected by immersion in 1% (v:v) sodium hypochlorite solution for 1 min. Then, they were subjected to triple washing by immersion in sterile distilled water and dried in a safety cabinet for four hours. Then, they were treated with biological and chemical products, as follows:

  1. 1.

    Treatment 1: Control

  2. 2.

    Treatment 2: Avicta 500 FS (active ingredient: Abamectin, applied at 50 mL/50 kg of seeds)

  3. 3.

    Treatment 3: Presence (Bacillus subtilis FMCH002 and Bacillus licheniformis FMCH001 applied at 75 g/50 kg of seeds)

  4. 4.

    Treatment 4: Votivo Prime (active ingredient: Bacillus firmus I-1582, applied at 200 mL/50 kg of seeds)

  5. 5.

    Treatment 5: Ag109 (active ingredient: Bacillus velezensis Ag109, applied at 200 mL/50 kg of seeds). The Ag109 was prepared from pure colonies suspended in saline solution (0.85% NaCl), and the turbidity was adjusted to 0.5 on the McFarland nephelometric scale. The inoculum was prepared from 30 µL of this bacterial suspension, which was transferred to a 125 mL Erlenmeyer flask containing 30 mL of LB broth and incubated at 28 °C for 24 h at 180 rpm in an orbital shaker incubator (Tecnal—TE 422, Brazil). For fermentation, an Erlenmeyer flask containing 400 mL of culture medium (20 g L−1 glucose, 5 g L−1 yeast extract, 5 g L−1 tryptone, 1 g L−1 monobasic potassium phosphate, 0.5 g L−1 dibasic potassium, 0.5 g L−1 magnesium sulfate, 0.5 g L−1 iron sulfate, 0.5 g L−1 calcium chloride, and 0.5 g L−1 sodium chloride) was inoculated with a 4 mL aliquot of the bacterial inoculum and incubated at 28 °C for 72 h at 180 rpm in an orbital shaker incubator (Tecnal—TE 422, Brazil). The fermentation of Ag109 was carried out as previously described, standardized for 1 × 109 endospores mL−1.

The seeds were sown in 945-mL Styrofoam pots containing a mixture of sand and soil (81% sand, 14% clay, and 5% silt) previously sterilized (160° / 5 h). At planting, 3 g of Osmocote® (15% N, 9% P2O5, 12% K2O, 1% Mg, 2.3% S, 0.05% Cu, 0.45% Fe, 0.06% Mn, 0.02% Mo) was added per pot. Seven days after sowing (DAS), plants were inoculated with 1 mL of a suspension containing 1000 eggs of M. javanica or 500 eggs and juveniles/adults of P. brachyurus, which were extracted according to [24], without the use of sodium hypochlorite for P. brachyurus, and quantified in Peter’s slide under a light microscope. Sixty DAS, plant roots were washed free of soil in tap water, dried on absorbent paper, and weighed to obtain the fresh root mass (FRM). Subsequently, they were processed according to [24], and the eggs and juveniles were quantified in Peter’s slide under a light microscope. The nematode reproduction factor (RF = the number of nematodes in the sample/number of inoculated nematodes) and the number of nematodes per gram of roots (NGR) (the number of nematodes in the sample/ FRM) were determined. A completely randomized experimental design was adopted with ten replications.

Activity of Ag109 against fungal soil-borne pathogens

Direct antagonism test by double culture

The fungi Rhizoctonia solani, Sclerotinia sclerotiorum, and Macrophomina phaseolina were provided by the GDM® company, Cambé, Paraná state, Brazil. To prepare the inoculum, the fungal strains were subcultured in Petri dishes containing potato dextrose agar (PDA) culture medium and incubated at 25 °C for two to five days, according to the fungus growth rate.

To prepare the bacterial inoculum, the Ag109 strain was spread over the agar surface of Luria Bertani (LB) culture medium in a Petri dish, incubated at 28 °C for 24 h, and subjected to a second cultivation under the same conditions. Three to five colonies were suspended in saline solution (0.85% NaCl), and the turbidity was adjusted to 0.5 on the McFarland nephelometric scale.

A 5 µL aliquot of the Ag109 inoculum was spread in a line using a bacteriological loop at 0.5 cm from the end of the Petri dishes containing PDA culture medium. Then, a 6 mm-diameter mycelial disc of the fungus (R. solani, S. sclerotiorum, or M. phaseolina) was inoculated at the opposite end of the bacterial inoculum. Plates with only the fungus were used as controls. The evaluation was carried out at different times, according to the growth rate of each fungus, 48 h for R. solani and 96 h for S. sclerotiorum and M. phaseolina. The mycelial growth of the fungi (in mm) was measured using a caliper, and the percentage of inhibition was calculated.

Activity of the autoclaved fermentation broth and cell-free supernatant of Ag109 on the mycelial growth of Sclerotinia sclerotiorum

The fermentation of Ag109 was carried out as previously described, standardizing for 1 × 109 endospores mL−1. The fungus S. sclerotiorum was cultivated in PDA medium in a 90 mm-diameter Petri dish for five days at 25 °C. A 6 mm-diameter mycelial disc was taken from this culture and placed in the center of three Petri dishes containing BDA. Six mm-diameter wells were perforated at the two edges. In one of the wells, 200 µL of cell-free supernatant was added, while in the opposite well, 200 µL of autoclaved fermentation broth was added. Three plates inoculated only with a fungal mycelial disc were used as controls. After 96 h, the mycelial growth of the fungus was measured (in mm) with a caliper, and the percentage of inhibition was calculated.

In vivo studies against Sclerotina sclerotiorum under greenhouse conditions

For this experiment, seeds of the soybean cv. Bônus were used. The seeds were disinfected by immersion in 1% (v:v) sodium hypochlorite solution for 1 min. Then, they were subjected to triple washing by immersion in sterile distilled water and dried in a safety cabinet for four hours. Subsequently, the seeds were treated with biological and chemical products, as follows:

  1. 1.

    Treatment 1: Control

  2. 2.

    Treatment 2: Certainty (active ingredient: Thiophanate + Fluazinan, applied at 100 mL/50 kg of seeds)

  3. 3.

    Treatment 3: Serenade (active ingredient: Bacillus subtilis QST 713, applied at 200 mL/50 kg of seeds)

  4. 4.

    Treatment 4: Ag109 (active ingredient: Bacillus velezensis Ag109, applied at 200 mL/50 kg of seeds). The fermentation of Ag109 was carried out as previously described, standardizing for 1 × 109 endospores mL−1.

Some of the control seeds and the seeds treated with biological and chemical products were inoculated with the fungus Sclerotinia sclerotiorum, according to Machado et al. [25]. Soybean seeds were kept for 24 h in Petri dishes containing the fungus grown in a culture medium at 25 °C. The seeds were sown in 32-cell trays (0.23 L per cell) containing sterile Carolina Soil substrate and kept in a greenhouse. One seed was sown per cell. Each tray was considered a plot, with four replications totaling 128 seeds per treatment. A completely randomized experimental design was used. Germination evaluations were performed at seven and 26 DAS. At 26 DAS, shoot and root dry mass per plant were quantified. For the experiment, the average temperature of the greenhouse was 25 ºC ± 2 ºC.

Ag109 genomic sequencing and prediction of secondary metabolites

Ag109 was grown in LB at 150 rpm at 28 °C for 48 h for complete genome sequencing. DNA extraction was performed using a PureLinkTM Microbiome DNA Purification kit (Invitrogen, Thermo Fisher Scientific, Waltham, Massachusetts, USA). DNA integrity was verified using a 1% agarose gel and the DNA was quantified by spectrophotometry in a NanoDrop 2000/2000c (Thermo Fisher Scientific, Wilmington, Delaware, USA). Sequencing was performed on the Illumina NovaSeq 6000 platform at the Institute for Cancer Research (IPEC), Guarapuava, Paraná, Brazil.

The quality of the readings and the cutoff parameters were considered and chosen using FastQC (Andrews 2010 [26]). Then, using the Trimmomatic program [27], the raw readings were filtered based on the parameters defined by FastQC. Finally, the quality of the readings was verified after the filters to ensure that the chosen parameters were adequate.

A series of de novo assemblies were performed with different software (SPAdes and IDBA hybrid) [28], testing diverse assembly parameters. Then, the results were compared with the QUAST program [29]. The best assembly was selected based on key metrics like total alignment size, contig count, largest contig, N50 values, and gene count, as per QUAST’s reference genome. Best-assembled contigs were aligned with the B. velezensis NKG-1 reference genome using the Contiguator webserver to create scaffolds [30]. Gaps were filled manually with Bowtie2 for mapping and CLC Genomics Workbench 12 for gap-filling [31]. The genome’s start point was identified by comparing it with a reference strain genome, using dnaA as the starting gene.

The genome of Ag109 was represented circularly and compared with other reference genomes using BRIG (BLAST Ring Image Generator). To determine the species, the ANI (Average Nucleotide Identity) values were verified with other species of Bacillus using OrthoANI [32]. The orthoANI matrix data and information generated by the software were exported and used to create the heatmap in the R program using the ggplot2 package. The hierarchical cluster analysis used was the UPGMA.

Using different genetic databases, the Glimmer 3.02 program was used to predict genes related to plant growth promotion. The identification of possible biosynthetic gene clusters (BGCs) was performed using the antiSMASH 4.0 web server [33], which combines different genetic databases, antimicrobial molecules, and BGCs to predict the position and possible function of the clusters [34]. In addition to Ag109, the genome of Bacillus subtilis QST 713 and Bacillus velezensis FZB42 was analyzed by antiSMASH for further comparisons.

Data analysis

The data from the greenhouse trials were subjected to variance analysis. When the assumptions were met, they were subjected to Tukey’s means comparison test (p < 0.01). Data were analyzed by the R program using the AgroR package [35].

Results

Nematicidal activity

By the variance analysis, a significant effect (p < 0.01) of treatments for the variables reproduction factor (RF) and number of nematodes per gram of roots (NGR) was observed in both experiments with M. javanica and P. brachyurus. For M. javanica, the treatments with Avicta, Presence, and Ag109 showed the lowest values for RF and NGR in experiment I. In experiment II, the lowest value was observed in Ag109 for RF and in Avicta, Presence, and Ag109 for NGR (Table 1). In these experiments, Ag109 allowed average reductions of 59 and 63% for RF and NGR, respectively.

Table 1 Effect of biological and chemical treatments for the biocontrol of Meloidogyne javanica and Pratylenchus brachyurus in soybean in vivo

For P. brachyurus, Ag109 showed the lowest values of RF and NGR in experiment I, with 60 and 44% reductions, respectively, compared to the control. For experiment II, the lowest RF values were obtained in the treatments Ag109 and Votivo Prime, while for NGR, with Ag109. Ag109 reduced the RF and NGR by 30 and 43%, respectively, in this experiment.

Antifungal activity

The Ag109 strain showed antifungal activity against M. phaseolina, R. solani, and S. sclerotiorum, with mycelial growth control percentages of 40.01, 30.03, and 43.07%, respectively (Fig. 1a). No contact was observed between Ag109 and the fungi, showing that mycelial growth was paralyzed before reaching the bacterial culture and indicating antagonistic activity of the bacterial strain.

Fig. 1
figure 1

Effect of Bacillus velezensis strain Ag109 in relation to different phytopathogenic fungi. A Inhibition of mycelial growth (%) for Macrophomina phaseolina, Rhizoctonia solani, and Sclerotinia sclerotiorum through direct antagonism, B Inhibition of mycelial growth (%) of Sclerotinia sclerotiorum using the crude autoclaved (15 min, 120 °C) and cell-free (filtered) supernatants

When analyzing the cell-free culture filtrate of Ag109 against S. sclerotiorum, a high percentage (64.10%) of growth inhibition was also observed (Fig. 1B). In addition, the autoclaved crude supernatant was also evaluated against S. sclerotiorum to verify the stability of the molecules. In this case, 55.9% of inhibition was detected, indicating the high control potential of the metabolites produced by Ag109.

In the experiment of S. sclerotiorum infection in soybean seeds, a significant effect (p < 0.01) of treatments was observed for most traits, except for dry shoot mass. For the germination percentage of healthy plants (7 and 26 DAS), the treatments Certeza N and Control (without infection) showed the highest values, followed by Serenade and Ag109 (Fig. 2). The biological treatments showed an increase in healthy seedlings of 27 and 24%, respectively, in relation to the control (with infection), while the chemical treatment increased this trait by 68%. For root dry mass, the highest values were observed for biological treatments (Ag109 and Serenade) and the control (without infection). The chemical treatment showed the lowest value for root dry mass.

Fig. 2
figure 2

Germination percentage and root and shoot dry mass of soybean inoculated with different products and later infected with Sclerotinia sclerotiorum. Treatments with the same letter did not differ statistically by Tukey’s test (p < 0.01)

Ag109 genome assembly and annotation

The CLC Genomics Workbench 11 and IDBA Hybrid genome assembly strategies demonstrated the best results for assembly. A BLASTN search was performed using the largest contig to find a reference genome for the CONTIGuator step. The B. velezensis strain Bac57 was selected to align the contigs and to generate scaffold. The scaffold contained 36 gaps that were first treated with GapCloser and then manually aligned using Bowtie2 and CLC Genomics Workbench 11. Then, the genome showed a 97.96% alignment rate of reads and a size of 3,954,988 bp. Genome annotation verified a GC content of 46.39% and 4052 CDSs, of which 24 were related to rRNA and 78 to tRNA sequences (GenBanK accession number CP099465).

Ag109 identification and phylogenetic analysis

Comparing Ag109 with the main species of the B. subtilis group, it was observed that the mean nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) were superior in the groups of B. velezensis isolates, with values ranging from 98.3 to 99.9% for ANI and 84.3 to 92.4% for dDDH (Table S1; Fig. 3). Compared with B. amyloliquefaciens (DSM7 and MT 45 strains), the ANI and dDDH values were 94.0 – 94.1% and 55.7%, respectively, while for B. subtilis (168 and D125 strains), they were 77.2 – 77.3% and 20.7%, respectively. The values for B. cereus (FR135 strain) were 66.3 and 38.9%, respectively. In the comparison performed with Gegenees and orthoANI/GGDC, it was observed that Ag109 is located within the cluster containing most of B. velezensis (Fig. 3). The circular genome of Ag109 is represented in Fig. 4.

Fig. 3
figure 3

Maximum likelihood phylogenetic tree based on the 10 available genomic assemblies of Bacillus velezensis, B. amyloliquefaciens, B. cereus, and B. subtilis with heatmap annotation. Average nucleotide identity (ANI) values (%) are presented in a heatmap, ranging from lower (violet) to higher sequence identity (green-yellow), and clustered according to the phylogenetic tree. The heatmap was annotated with a bar chart showing the varying sizes (Mb) of all 10 assemblies (at the top) and their respective GC (%) content (right-hand side)

Fig. 4
figure 4

Circular representation of the genome of Bacillus velezensis Ag109 using the program BRIG. From the inside to the outside, the legends are as follows: GC content, GC skew, BGC position on the genome indicated by antiSMASH: 102742, BAC 57, FZB42, NKG1, and QST 713, respectively

Genetic basis for plant growth-promoting activity

The Ag109 genome has several genes that encode proteins associated with plant growth-promoting activity (Table 2). For instance, ten putative genes (trpA, trpB, trpC, trpD, trpE, trpF, ywdH, ysnE, ywkB, and amhX) involved in the production of indole-3-acetic acid were identified. In addition, other genes related to biofilm formation, volatile compounds, glucose dehydrogenase, phenazine, trehalose, heat and cold shock, glycine-betaine, and peroxidases were identified.

Table 2 Genes detected in the Bacillus velezensis Ag109 genome predicated to be involved in plant growth-promoting activity

AntiSMASH analysis of secondary metabolites

Using the antiSMASH 5.1.0 webserver, 13 biosynthetic gene clusters (BGCs) were identified in the genome of Ag109 (Table 3). Six BGCs showed 100% similarity and are linked to the synthesis of bacilisin, bacilibactin, difficidin, fengicin, bacilaene, and macrolactin. One cluster showed 56% similarity with surfactin synthesis, and another, 7% similarity with the synthesis of butyrosine A and B. Four clusters showed no similarity with the database. The 13 gene clusters identified in Ag109 were also present in the commercial strains QST 713 and FZB42 (Fig. 5).

Table 3 Biosynthetic gene clusters (BGCs) found within the Bacillus velezensis Ag109 genome using the webserver antiSMASH 5.1.0 and comparison with strains QST713 and FZB42
Fig. 5
figure 5

Comparison of gene clusters between Bacillus velezensis Ag109 with Bacillus subtilis QST 713 and Bacillus velezensis FZB42. Cluster no.12 in QST 713 genome not presented in the other genome

Discussion

Plant diseases caused by soil-transmitted pathogens are considered one of the leading causes of yield loss in various crops [14, 36]. Consequently, a variety of control strategies have been suggested. Among them, biocontrol agents are an essential strategy for controlling soil pathogens. These agents can act through parasitism, antibiosis, competition for the host and nutrients, and induction of plant resistance [37]. Bacillus is considered an important biocontrol agent and has been widely used against several pathogens in different crops [18, 38,39,40]. The current study identified a bacterial strain, Ag109, from maize rhizospheric soil that exhibits a strong antagonistic effect against S. sclerotiorum. This strain was further investigated to evaluate its potential as a biocontrol, for M. javanica and P. brachyurus, and Ag109 showed significant suppression. These nematode species are considered a crucial obstacle to soybean cultivation in Brazil. P. brachyurus is a migratory endoparasite that causes lesions on the root cortex, leading to root deterioration. This pathogen is highly polyphagous and commonly found in tropical regions, mainly in soybean-corn crop succession systems under no-tillage [41]. Likewise, many root-knot nematodes, mainly M. javanica and M. incognita, can be found in practically all soybean production fields. The parasitism caused by this nematode leads to hypertrophy and hyperplasia of root cells, compromising plant development [5].

Furthermore, Ag109 showed a significant suppression effect against the primary soil fungi in soybean. For S. sclerotiorum, this strain increased the number of healthy seedlings and root dry mass relative to the control, indicating the potential for promoting root growth. Several studies have indicated the multifunctional potential of some Bacillus species/strains for plant protection against phytopathogenic microorganisms and their growth-promoting action on plants [42,43,44,45]. Bacillus can improve soil nutrient availability through improved nitrogen supply, phosphate and potassium solubilization, and siderophore production. In addition, these bacteria secrete hormones and volatile organic compounds associated with root development, improving plant nutrient uptake. Associated with these characteristics, Bacillus can improve plant resistance against soil pathogens through competition for niches and nutrients, production of antagonist compounds, and induction of systemic plant resistance [44, 45].

By genomic analysis, Ag109 was identified as B. velezensis and clusters of specific genes related to secondary metabolite biosynthesis and root system promotion were identified. B. velezensis is an important biocontrol agent and plant growth promoter in several crops of economic importance [17, 22, 45,46,47,48,49]. For instance, the FZB42 isolate, which has already been published in over 140 articles, has been related to the identification of antimicrobial compounds responsible for biocontrol, the expression of genes involved in plant-bacteria interactions, the study of small regulatory RNAs (sRNAs), and the modification of enzymes involved in the synthesis of antimicrobial compounds. This information is deposited in the ‘AmyloWiki’ database (http://amylowiki.top/) [22]. The QST 713 strain, present in a commercial product, which performed well in the tests, share the same clusters as Ag109 with exception for a single cluster present only in QST 713.

In the Ag109 strain, lipopeptides (LPs) (surfactin and fengycin) were identified, which have an essential effect on pathogen suppression, stimulation of plant defense mechanisms, and biofilm formation – a key factor for the successful colonization of biological control agents [50,51,52]. Its mode of action in antifungal activity is related to its amphiphilic nature and its interaction with the target cell membrane, resulting in changes in structure and permeability [51,52,53]. In this context, this class of metabolites may be directly related to the antifungal activity of Ag109 in vitro and in vivo assays against phytopathogenic fungi. It may be the target of future in silico and downstream studies. For nematodes, Kavitha et al. [54] found that the LPs surfactin and iturin produced by B. subtilis were responsible for suppressing the hatching of M. incognita eggs and played an essential role in juvenile mortality.

Another large class of secondary metabolites identified in Ag109 were polyketides (PKS) (difficidin, bacillaene, and macrolactin), which play an essential role in antimicrobial activity, acting in the selective inhibition of protein synthesis [55, 56]. Chen et al. [57] found that difficidin produced by the FZB42 isolate had a significant antagonistic effect on Erwinia amylovora, which causes fire blight in fruit trees. In turn, Yuan et al. [58] demonstrated that the macrolactin produced by the NJN-6 isolate (B. amyloliquefaciens) affects the control of Ralstonia solanacearum, an important soil pathogen. In this context, the Ag109 strain can potentially control soil bacterial diseases that have not yet been explored.

From the 13 clusters identified in the Ag109 genome, four had no similarity to the database, so their products still need to be identified and described, opening opportunities for further studies. Likewise, Teixeira et al. [17] mined the genome of B. velezensis CMRP 4490 and failed to identify five of the 13 clusters of secondary metabolites, indicating new clusters of these metabolites.

In addition to producing antimicrobial metabolites, the Ag109 genome has genes related to plant growth-promoting activity. Several genes identified are functionally linked to auxin synthesis and play important roles in the stimulation of plant development [59, 60]. In addition, genes related to spermidine and polyamine production were found, which are suggested to have a role in plant development and growth promotion, involving the production of active metabolites such as steroids, vitamin D3, cholesterol, cytokinin, statins, and terpenes [60]. This strain also has biofilm formation, development, and regulatory genes. Bacterial biofilms are a collective way of life that confer emergent properties on the inhabitants of these communities, influencing plant growth and behavior and directly protecting against soil pathogens through the secretion of compounds [61]. Thus, the Ag109 strain has excellent potential for developing a multifunctional microbial inoculant that combines the ability to biocontrol various soil pathogens (fungi and nematodes) and promote soybean growth.

Conclusion

Ag109 strain shows considerable promise as the basis for a multifunctional microbial inoculant designed for soybeans. This inoculant would offer biological control and enhance plant growth, with particular efficacy in suppressing nematodes like M. javanica and P. brachyurus. Future studies should explore the mechanisms behind Ag109’s antagonistic effects and growth-promotion properties and its performance in field conditions against a broader spectrum of pathogens and under varying environmental conditions. This would pave the way for developing more effective, environmentally friendly plant protection and enhancement strategies, contributing significantly to the sustainability and productivity of soybean cultivation.

Availability of data and materials

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

References

  1. Hartman GL, Rupe JC, Sikora EJ, Domier LL, Davis JA, Steffey KL. Compendium of soybean diseases, 5th edn. St. Paul, Minnesota: American Phytopathological Society; p 201.

  2. Reis RR, Mertz-Henning LM, Marcolino-Gomes J, Rodrigues FA, Rockenbach-Marin S, Fuganti-Pagliarini R, et al. Differential gene expression in response to water deficit in leaf and root tissues of soybean genotypes with contrasting tolerance profiles. Genet Mol Biol. 2020;43(2):e20180290.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Lin F, Chhapekar SS, Vieira CC, Da Silva MP, Rojas A, Lee D, et al. Breeding for disease resistance in soybean: a global perspective. Theor Appl Genet. 2022;135(11):3773–872.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Lima FS, Correa VR, Nogueira SR, Santos PR. Nematodes affecting soybean and sustainable practices for their management. In: Kasai M (ed) Soybean, The basis of yield, biomass and productivity. Intech Rijeka Croatia. 2017. p. 95–110.

  5. Dias WP, Garcia A, Silva JFV, de Carneiro GES. Nematóides em soja: identificação e controle. 2010.

    Google Scholar 

  6. Machado ACZ. Current nematode threats to Brazilian agriculture. Curr Agric Sci Technol. 2014;20(1):26–35.

  7. de Oliveira CM, Almeida NO, de Côrtes MVCB, Júnior ML, da Rocha MR, Ulhoa CJ. Biological control of Pratylenchus brachyurus with isolates of Trichoderma spp. on soybean. Biol Control. 2021;152:104425.

    Article  Google Scholar 

  8. Willbur J, McCaghey M, Kabbage M, Smith DL. An overview of the Sclerotinia sclerotiorum pathosystem in soybean: impact, fungal biology, and current management strategies. Trop Plant Pathol. 2019;44(1):3–11.

    Article  Google Scholar 

  9. Blanco AJV, Costa MO, do Silva RN, de Albuquerque FS, de Melo ATO, Lopes FAC, et al. Diversity and pathogenicity of rhizoctonia species from the Brazilian cerrado. Plant Dis. 2018;102(4):773–81.

    Article  PubMed  Google Scholar 

  10. Reis EM, Boaretto C, Danelli ALD. Macrophomina phaseolina: density and longevity of microsclerotia in soybean root tissues and free on the soil, and competitive saprophytic ability. Summa Phytopathol. 2014;40(2):128–33.

    Article  Google Scholar 

  11. Costa SS, Matos KS, Tessmann DJ, Seixas CDS, Pfenning LH. Fusarium paranaense sp. nov., a member of the Fusarium solani species complex causes root rot on soybean in Brazil. Fungal Biol. 2016;120(1):51–60.

    Article  CAS  PubMed  Google Scholar 

  12. Lehner MS, Pethybridge SJ, Meyer MC, Del Ponte EM. Meta-analytic modelling of the incidence–yield and incidence–sclerotial production relationships in soybean white mould epidemics. Plant Pathol. 2017;66(3):460–8.

    Article  Google Scholar 

  13. Katan J. Diseases caused by soilborne pathogens: biology, management and challenges. J Plant Pathol. 2017;(17)305–15.

  14. Panth M, Hassler SC, Baysal-Gurel F. Methods for management of soilborne diseases in crop production. Agriculture. 2020;10(1):16.

    Article  CAS  Google Scholar 

  15. Elnahal ASM, El-Saadony MT, Saad AM, Desoky ESM, El-Tahan AM, Rady MM, et al. The use of microbial inoculants for biological control, plant growth promotion, and sustainable agriculture: a review. Eur J Plant Pathol. 2022;162(4):759–92.

    Article  Google Scholar 

  16. Syed AB, Rahman SF, Singh E, Pieterse CMJ, Schenk PM. Emerging microbial biocontrol strategies for plant pathogens. Plant Sci. 2018;267:102–11.

    Article  Google Scholar 

  17. Teixeira GM, Mosela M, Nicoletto MLA, Ribeiro RA, Hungria M, Youssef K, et al. Genomic insights into the antifungal activity and plant growth-promoting ability in Bacillus velezensis CMRP 4490. Front Microbiol. 2021;15:11.

    Google Scholar 

  18. Machado ACZ. Bionematicides in Brazil: an emerging and challenging market. Rev Anual Patol Plant. 2022;10:35–49.

    Google Scholar 

  19. Ram RM, Keswani C, Bisen K, Tripathi R, Singh SP, Singh HB. Biocontrol technology: Eco-friendly approaches for sustainable agriculture. In Omics Technologies and Bio-Engineering. Cambridge: Academic Press; 2018, pp. 177–90.

  20. Fira D, Dimkić I, Berić T, Lozo J, Stanković S. Biological control of plant pathogens by Bacillus species. J Biotechnol. 2018;285:44–55.

    Article  CAS  PubMed  Google Scholar 

  21. Horak I, Engelbrecht G, Rensburg PJJ, Claassens S. Microbial metabolomics: essential definitions and the importance of cultivation conditions for utilizing Bacillus species as bionematicides. J Appl Microbiol. 2019;127(2):326–43.

    Article  CAS  PubMed  Google Scholar 

  22. Fan B, Wang C, Song X, Ding X, Wu L, Wu H, et al. Bacillus velezensis FZB42 in 2018: the gram-positive model strain for plant growth promotion and biocontrol. Front Microbiol. 2018;16:9.

    Google Scholar 

  23. Ye M, Tang X, Yang R, Zhang H, Li F, Tao F, et al. Characteristics and application of a novel species of Bacillus: Bacillus velezensis. ACS Chem Biol. 2018;13(3):500–5.

    Article  CAS  PubMed  Google Scholar 

  24. Bonetti JI, Ferraz S. Modificações do método de Hussey & Barker para extração de ovos de Meloidogyne exigua em raízes de cafeeiro. Fitopatol Bras. 1981;6:553.

    Google Scholar 

  25. Machado JC, Oliveira JA, Vieira MGGC, Alves MC. Inoculação artificial de sementes de soja por fungos, utilizando solução de manitol. 2001;23:95–101.

  26. Andrews S. FastQC. 2010. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

  27. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Peng Y, Leung HCM, Yiu SM, Chin FYL. IDBA – a practical iterative de Bruijn Graph De Novo Assembler. 2010. p. 426–40.

    Google Scholar 

  29. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29(8):1072–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Galardini M, Biondi EG, Bazzicalupo M, Mengoni A. CONTIGuator: a bacterial genomes finishing tool for structural insights on draft genomes. Source Code Biol Med. 2011;6(1):11.

    Article  PubMed Central  Google Scholar 

  31. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Lee I, Ouk Kim Y, Park SC, Chun J. OrthoANI: an improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol Microbiol. 2016;66(2):1100–3.

    Article  CAS  PubMed  Google Scholar 

  33. Weber T, Blin K, Duddela S, Krug D, Kim HU, Bruccoleri R, et al. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters. Nucleic Acids Res. 2015;43(W1):W237-43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N, Lee SY, et al. antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 2019;47(W1):W81-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Shimizu GD, Marubayashi RY, Goncalves LS. AgroR: Experimental Statistics and Graphics for Agricultural Sciences. 2023. Available online: https://agronomiar.github.io/AgroR_package/index.html. Accessed 1 Jan 2024.

  36. De Corato U. Disease-suppressive compost enhances natural soil suppressiveness against soil-borne plant pathogens: a critical review. Rhizosphere. 2020;13:100192.

    Article  Google Scholar 

  37. Köhl J, Kolnaar R, Ravensberg WJ. Mode of action of microbial biological control agents against plant diseases: relevance beyond efficacy. Front Plant Sci. 2019;19:10.

    Google Scholar 

  38. Shafi J, Tian H, Ji M. Bacillus species as versatile weapons for plant pathogens: a review. Biotechnol Biotechnol Equip. 2017;31(3):446–59.

    Article  CAS  Google Scholar 

  39. Aloo BN, Makumba BA, Mbega ER. The potential of Bacilli rhizobacteria for sustainable crop production and environmental sustainability. Microbiol Res. 2019;219:26–39.

    Article  CAS  PubMed  Google Scholar 

  40. Dimkić I, Janakiev T, Petrović M, Degrassi G, Fira D. Plant-associated Bacillus and Pseudomonas antimicrobial activities in plant disease suppression via biological control mechanisms - a review. Physiol Mol Plant Pathol. 2022;117:101754.

    Article  Google Scholar 

  41. Miamoto A, Silva MTRE, Dias-Arieira CR, Puerari HH. Alternative products for Pratylenchus brachyurus and Meloidogyne javanica management in soya bean plants. J Phytopathol. 2017;165(10):635–40.

    Article  CAS  Google Scholar 

  42. Lopes R, Tsui S, Gonçalves PJRO, de Queiroz MV. A look into a multifunctional toolbox: endophytic Bacillus species provide broad and underexploited benefits for plants. World J Microbiol Biotechnol. 2018;34(7):94.

    Article  PubMed  Google Scholar 

  43. Poveda J, González-Andrés F. Bacillus as a source of phytohormones for use in agriculture. Appl Microbiol Biotechnol. 2021;105(23):8629–45.

    Article  CAS  PubMed  Google Scholar 

  44. Luo L, Zhao C, Wang E, Raza A, Yin C. Bacillus amyloliquefaciens as an excellent agent for biofertilizer and biocontrol in agriculture: an overview for its mechanisms. Microbiol Res. 2022;259:127016.

    Article  CAS  PubMed  Google Scholar 

  45. Mosela M, Andrade G, Massucato LR, de Araújo Almeida SR, Nogueira AF, de Lima Filho RB, et al. Bacillus velezensis strain Ag75 as a new multifunctional agent for biocontrol, phosphate solubilization and growth promotion in maize and soybean crops. Sci Rep. 2022;12(1):15284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Pan HQ, Li QL, Hu JC. The complete genome sequence of Bacillus velezensis 9912D reveals its biocontrol mechanism as a novel commercial biological fungicide agent. J Biotechnol. 2017;247:25–8.

    Article  CAS  PubMed  Google Scholar 

  47. Chen L, Heng J, Qin S, Bian K. A comprehensive understanding of the biocontrol potential of Bacillus velezensis LM2303 against Fusarium head blight. PLoS One. 2018;13(6):e0198560.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Cheffi Azabou M, Gharbi Y, Medhioub I, Ennouri K, Barham H, Tounsi S, et al. The endophytic strain Bacillus velezensis OEE1: an efficient biocontrol agent against Verticillium wilt of olive and a potential plant growth promoting bacteria. Biol Control. 2020;142:104168.

    Article  CAS  Google Scholar 

  49. Zhu Z, Peng Q, Man Y, Li Z, Zhou X, Bai L, et al. Analysis of the antifungal properties of bacillus velezensis B-4 through a bioassay and complete-genome sequencing. Front Genet. 2020;16:11.

    Google Scholar 

  50. Ongena M, Jacques P. Bacillus lipopeptides: versatile weapons for plant disease biocontrol. Trends Microbiol. 2008;16(3):115–25.

    Article  CAS  PubMed  Google Scholar 

  51. Zhao H, Shao D, Jiang C, Shi J, Li Q, Huang Q, et al. Biological activity of lipopeptides from Bacillus. Appl Microbiol Biotechnol. 2017;101(15):5951–60.

    Article  CAS  PubMed  Google Scholar 

  52. Penha RO, Vandenberghe LPS, Faulds C, Soccol VT, Soccol CR. Bacillus lipopeptides as powerful pest control agents for a more sustainable and healthy agriculture: recent studies and innovations. Planta. 2020;251(3):70.

    Article  CAS  PubMed  Google Scholar 

  53. Chavarria-Quicaño E, De la Torre-González F, González-Riojas M, Rodríguez-González J, Asaff-Torres A. Nematicidal lipopeptides from Bacillus paralicheniformis and Bacillus subtilis: a comparative study. Appl Microbiol Biotechnol. 2023;107(5–6):1537–49.

    Article  PubMed  Google Scholar 

  54. Kavitha PG, Jonathan EL, Nakkeeran S. Effects of crude antibiotic of Bacillus subtilis on hatching of eggs and mortality of juveniles of Meloidogyne incognita. Nematol Mediterr. 2012;40:203–6.

  55. Chen XH, Vater J, Piel J, Franke P, Scholz R, Schneider K, et al. Structural and functional characterization of three polyketide synthase gene clusters in Bacillus amyloliquefaciens FZB 42. J Bacteriol. 2006;188(11):4024–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Caulier S, Nannan C, Gillis A, Licciardi F, Bragard C, Mahillon J. Overview of the antimicrobial compounds produced by members of the Bacillus subtilis group. Front Microbiol. 2019;26:10.

    Google Scholar 

  57. Chen XH, Koumoutsi A, Scholz R, Schneider K, Vater J, Süssmuth R, et al. Genome analysis of Bacillus amyloliquefaciens FZB42 reveals its potential for biocontrol of plant pathogens. J Biotechnol. 2009;140(1–2):27–37.

    Article  CAS  PubMed  Google Scholar 

  58. Yuan J, Raza W, Shen Q, Huang Q. Antifungal activity of Bacillus amyloliquefaciens NJN-6 volatile compounds against fusarium oxysporum f. sp. cubense. Appl Environ Microbiol. 2012;78(16):5942–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Talboys PJ, Owen DW, Healey JR, Withers PJ, Jones DL. Auxin secretion by Bacillus amyloliquefaciens FZB42 both stimulates root exudation and limits phosphorus uptake in Triticum aestivium. BMC Plant Biol. 2014;14(1):51.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Zaid DS, Cai S, Hu C, Li Z, Li Y. Comparative genome analysis reveals phylogenetic identity of bacillus velezensis HNA3 and genomic insights into its plant growth promotion and biocontrol effects. Microbiol Spectr. 2022;10(1):e02169-21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Arnaouteli S, Bamford NC, Stanley-Wall NR, Kovács ÁT. Bacillus subtilis biofilm formation and social interactions. Nat Rev Microbiol. 2021;19(9):600–14.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

The authors thank CAPES (Coordination for the Improvement of Higher Education Personnel – financial code 01) for granting the master scholarship to the first author.

Author information

Authors and Affiliations

Authors

Contributions

SM, ACZM, and LSAG conceived the original project. SM, RTH, MM, AYH, AFN, RMG, LABR, and AK performed experiments. GDS, GMT, RA, and LSAG carried out statistical analyses. SM and LSAG wrote the first draft of the manuscript. All authors contributed to the final manuscript.

Corresponding author

Correspondence to Leandro Simões Azeredo Gonçalves.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mian, S., Machado, A.C.Z., Hoshino, R.T. et al. Complete genome sequence of Bacillus velezensis strain Ag109, a biocontrol agent against plant-parasitic nematodes and Sclerotinia sclerotiorum. BMC Microbiol 24, 194 (2024). https://doi.org/10.1186/s12866-024-03282-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12866-024-03282-9

Keywords