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Article

Genetic Characteristics and Enzymatic Activities of Bacillus velezensis KS04AU as a Stable Biocontrol Agent against Phytopathogens

by
Roderic Gilles Claret Diabankana
1,2,*,
Elena Urievna Shulga
1,
Shamil Zavdatovich Validov
1 and
Daniel Mawuena Afordoanyi
1,3,4
1
Laboratory of Molecular Genetics and Microbiology Methods, Kazan Scientific Center of Russian Academy of Sciences, 420111 Kazan, Russia
2
Centre of Agroecological Research, Kazan State Agrarian University, 420015 Kazan, Russia
3
Tatar Scientific Research Institute of Agricultural Chemistry and Soil Science, FRC Kazan Scientific Center, Russian Academy of Sciences, 420111 Kazan, Russia
4
Laboratory of Structural Biology, Institute of Fundamental Medicine and Biology Kazan (Volga Region) Federal University, 420021 Kazan, Russia
*
Author to whom correspondence should be addressed.
Int. J. Plant Biol. 2022, 13(3), 201-222; https://doi.org/10.3390/ijpb13030018
Submission received: 23 June 2022 / Revised: 10 July 2022 / Accepted: 14 July 2022 / Published: 18 July 2022
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Abstract

:
Bacillus velezensis has a broad application in the agricultural and industrial sectors for its biocontrol properties and its potential active secondary metabolites. The defined phenotypic characteristics of a strain vary according to its ecosystem. We report the complete genomic analysis of B. velezensis KS04AU compared to four strains of B. velezensis (SRCM102752, ONU-553, FZB42, and JS25R) and two closely related Bacillus amyloliquefaciens (LL3 and IT-45). A total of 4771 protein coding genes comprises the KS04AU genome, in comparison with 3334 genes core genes found in the six other strains and the remaining 1437 shell genes. Average nucleotide identity of the target strain to the six other strains showed 99.65% to B. velezensis ONU-553, sharing 60 orthologous genes. Secondary metabolite gene cluster analysis of all strains showed that KS04AU has a mersacidin cluster gene, which is absent in the genome of the other strains. PHASTER analysis also showed KS04AU harboring two phages (Aeribacllus AP45 NC_048651 and Paenibacillus_Tripp NC_028930), which were also unique in comparison with the other strains. Analysis on anti-microbial resistance genes showed no difference in the genome of KS04AU to any of the other genomes, with the exception of B. amyloliquefaciens IT-45 which had one unique small multidrug-resistance antibiotic efflux-pump gene (qacJ). The CRISPR-Cas systems in the strains were also compared showing one CRISPR gene found only in KS04AU. Hydrolytic activity, antagonistic activity against phytopathogens (Fusarium oxysporum, Fusarium graminearum, Alternaria alternata and Pseudomonas syringae) and biocontrol against tomato foot and root rot experiments were carried out. B. velezensis KS04AU inhibits the growth of all phytopathogens tested, produces hydrolytic activity, and reduces Fusarium oxysporum f.sp. radicis-lycopersici (Forl) ZUM2407 lesions up to 46.02 ± 0.12%. The obtained results confirm B. velezensis KS04AU as a potential biocontrol strain for plant protection.

1. Introduction

Bacteria strains from the genus Bacillus are aerobic or facultative anaerobic endospore-forming bacteria, known to produce secondary metabolites that are antagonistic to most phytopathogens [1]. As an endospore-forming rhizobacteria and possessing the ability to grow under extreme abiotic conditions, strains of B. velezensis can be stored for a long period and are suitable for application in any type of soil [2,3]. Its antimicrobial, plant-growth-promoting ability including the ability to induce plant resistance (ISR); their probiotic ability in animals were also reported in several scientific manuscripts [4,5,6]. The main mechanism of B. velezensis as a biocontrol agent in wheat blight is due to its secondary metabolites that include polyketides and lipopeptide surfactins [7].
Recently, the systematic classification of B. velezensis by association or relation with one organism varied since its isolation from the River Vélez [3]. The origin of B. velezensis was said to be a latter heterotypic species of Bacillus amyloliquefaciens but genomic comparison of B. velezensis strain NRRL B-41580T, based on DNA–DNA relatedness calculation, showed it to be synonymous to Bacillus methylotrophicus [8]. The researchers suggested B. methylotrophicus KACC 13015, B. amyloliquefaciens subsp. plantarum FZB42 (recently B. velezensis FZB42), and B. oryzicola KACC 18228 to be reclassified since the B. velezensis strain NRRL B-41580 was published earlier [9]. These problems are frequently met in GenBank sequence database during identification of bacteria species based on 16S rRNA, which might differ from the full genome sequence.
The other importance of characterizing strains of the same species is based on their variations due to abiotic stress and biotic population bringing about mutations in the strains. A study by Kaltz and co-workers statistically proved that evolutionary factors (mutation rate, selection) and ecological factors (abiotic, biotic) affected the variance of population density obeying Taylor’s law [10]. An in-depth work on the phylogenomic interrelations, agricultural, industrial, and environmental applications of B. velezensis was well documented [11]. In their study, although the similarity of 17 B. velezensis was ≥98%, the NWUMFkBS10.5 strain had distinctive genes also found in several other unique strains.
In our work, a rhizobacterium strain of Senna occidentalis, a native weed plant to Africa, was identified as B. velezensis by 16S rRNA sequence; this was followed by a whole genome sequence analysis and comparison. The complete genome comparison was performed against five B. velezensis strains and two B. amyloliquefaciens, including genes responsible for secondary metabolites clusters, prophage regions, CRISPR–Cas system, antimicrobial resistance (ARM) genes, and insertion sequence (IS) elements. The strain was further characterized by enzymatic assay and antagonist activity against Fusarium graminearum and Alternaria alternata.

2. Materials and Methods

2.1. Genome Sequencing, Assembly, Genome Annotation and Gene Prediction

Total DNA was isolated from an overnight culture of B. velezensis KS04AU grown on Luria-Bertani (LB) broth (Tryptone, 10 g; Yeast Extract, 5 g; NaCl, 10 g) using TRIzol reagent (Thermo Fisher, Waltham, MA, USA) according to the manufacturer’s protocol. The whole genome was sequenced by the Genotek company (Moscow, Russia) on the Illumina HiSeq 2500 with 2 × 125 bp paired-end reads. Sequencing quality was analyzed using FastQC (v. 0.11.2) [12]. To remove adapters and low-quality reads, sequencing reads were trimmed using Trimmomatic v. 0.36 [13]. The genome was de novo assembled using the Unicycler v. 0.5.0 [14]. The quality of the assembled genomes was evaluated using QUAST [15]. ANI (average nucleotide identity) was used to select the close-related reference strain by measuring nucleotide-level similarity between the coding regions of genomes. For this purpose, the 16S rRNA gene of Bacillus velezensis KS04AU (GenBank: MW350014.1) was blasted on NCBI BLAST. The first seven closest-related genome species of KS04AU with their respective accession numbers (Table 1) downloaded from NCBI genome database were used for the Pairwise Analysis of ANIb (average nucleotide identity based on BLAST) analysis. We included only full chromosome-level assembly genomes to minimize mismatch data which can induce uncompleted genomes. Pairwise ANIb was performed using the Web server program tool JSpeciesWS (https://jspecies.ribohost.com/jspeciesws/#home, accessed on 22 June 2022), where ANI values >95% were considered the threshold for species delimitation [16]. Mauve Contig Mover [17] was later used to reorder contigs based on comparison with the complete reference genome. Gaps within the scaffolds were filled and closed using GAPPadder, v. 1.10 [18].

2.2. Genome Annotation, Gene Prediction and Comparative Genomic Analysis

The complete genome sequence analysis of strain KS04AU was performed to identify genes and sequence motifs of interest based on different databases. Genome annotation of B. velezensis strain KS04AU was carried out using Rapid prokaryotic genome annotation (Prokka) [19] and the Prokaryotic Genome Automatic Annotation Pipeline (PGAAP) provided by NCBI [20]. GeneMarkS was used to predict the open reading frame [21]. The potential antibiotic resistance genes were identified based on a homology search using the Comprehensive Antibiotic Resistance Database (CARD) [22]. The Kyoto encyclopedia of genes and genomes (KEGG) database was also used to examine the high-level functionality of B. velezensis KS04AU. The presence of prophage was performed using the PHAge SearchTool (PHAST) according to Zhou et al. [23]. Secondary metabolite biosynthetic gene clusters (BGC) were analyzed using AntiSMASH 6.1.1 [24]. Circular genome of KS04AU was plotted using DNAplotter [25].
In order to compare the genomic diversity, relationships and biochemical diversity between B. velezensis KS04AU and its closely related species, we first constructed a phylogenetic tree using MEGA-11 analysis software [26] by the Maximum Likelihood (ML) method using the JTT matrix [27], to determine the distance between genomes. Pangenome analysis was performed using Roary (which uses the annotated assemblies produced by Prokka), while the identified genes were classified into core, shell, and cloud genes, in which core gene families refer to gene families that are more than 95% identical in 7 genomes; shell gene families refer to genes that are more than 95% identical in more than one genomic gene family, and cloud gene families refer to gene families only present in one genome of aligned genomes. For fully genomic comparison, several complementary approaches were also used. OrthoVenn2 [28] was used for whole genome comparison and annotation of orthologous clusters. The web tool CRISPR Finder was used to identify and compare the CRISPR–Cas systems in Bacillus genomes [29,30]. AntiSMASH was used for the secondary metabolite comparison gene cluster. ISfinder was used to explore bacterial insertion sequences among strains [31]. The PHAge SearchTool (PHAST) [23] was used for the genomic comparison of prophages. The potential antibiotic resistance genes were identified based on a homology search using the Comprehensive Antibiotic Resistance Database (CARD) [22]. RAST and SEED [32] servers were used to compare the subsystem distribution statistics among selected bacterial strains. The BLAST Ring Image Generator (BRIG) was used to visualize the comparison of the whole genome sequence.

2.3. Antagonistic and Hydrolytic Activities

2.3.1. Bacterial Suspension Preparation

The bacterial suspensions were obtained by centrifuging the bacterial cultures at 8000 rpm at 4 °C for 15 min of the strains (B. velezensis KS04AU, P. putida PLC1760, and B. mojavensis PS17) grown overnight at 190 rpm in LB broth. Furthermore, the pellets were rinsed three times with phosphate buffered saline (PBS) (VWR, Radnor, PA, USA) and diluted to an optical density of 0.1 at 595 nm.

2.3.2. Hydrolytic Activities

The ability of B. velezensis KS04AU to produce hydrolytic enzymes, such as amylase, protease, cellulase, lipase, and chitinase was tested by pipetting 10 μL of cell suspension into basal medium amended with 1% of starch, milk powder, sodium carboxymethyl cellulose (Na-CMC), tween-80, and colloidal chitin, respectively. After incubating at 30 °C for 4 days, for cellulase and chitinase activity, plates were stained with 0.2% Congo red solution for 15 min and destained with 1 N NaCl [33]. For amylase activity, plates were stained with Gram’s iodine. Phytase activity was tested on phytate agar medium according to [34]. The appearance of hydrolysis or the formation of halo zones around colonies was considered as an enzymatic activity.

2.3.3. Antagonistic Activity

The ability of strain KS04AU to inhibit the growth of phytopathogenic fungi (Forl ZUM2407, F. graminearum, and A. alternate) and bacterium (Pseudomonas syringae) was tested using the confrontation assay in solid media in a Petri dish. For this purpose, phytopathogenic fungi were inoculated in the center of the plate and allowed to grow for one day. The bacterial strains were then co-inoculated on the same agar plate at a distance of 2.5 cm from the fungal strains. P. putida PLC1760 and B mojavensis PS17 were used as positive and negative controls, respectively. Antagonistic activity of KS04AU against P. syringae was assayed by spreading100 μL of overnight P. syringae culture with an optical density (595 nm) 0.5 on to LB agar medium using a plate spreader. Further, 5 µL of bacterial suspensions KS04AU, PS17 and PCL1760 were inoculated into the same plates. Plates were incubated at 28 °C for 3 days. The formation of halo zones around colonies was considered as antagonistic activity.

2.4. Biocontrol Ability of B. velezensis KS04AU to Suppress Tomato Foot and Root Rot

The biocontrol ability of B. velezensis KS04AU to suppress tomato foot and root rot caused by Forl ZUM2407 was performed under controlled laboratory conditions, in a pot (41 cm × 14 cm × 8 cm) containing a mineral wool presoaked with the mixture of plant nutrient solution (PNS[(PNS: 1.25 mM Ca(NO3)2; 1.25 mM KNO3; 0.50 mM MgSO4; 0.25 mM KH2PO4 and trace elements (0.75 mg/L KI; 3.00 mg/L H3BO3; 10.0 mg/L MnSO4.H2O; 2.0 mg/L ZnSO4.5H2O; 0.25 mg/L Na2MoO4.2H2O; 0.025 mg/L CuSO4.5H2O; 0.025 mg/L CoCl2.6H2O)] with spores of Forl ZUM2407 to a final concentration of 1 × 103 spores/mL. The bacterial suspensions were prepared as described above with a little modification. In this case, bacterial suspensions were obtained by centrifuging overnight bacterial cultures of B. velezensis KS04AU and P. putida PLC1760 at 8000 rpm at 4 °C for 15 min. After rinsing three times with PBS, the obtained aliquots were diluted in 1% Na-CMC to an optical density of 0.3 at 595 nm. The tomato seeds were inoculated with the bacterial suspensions for 15 min, then dried in laminar hoods. Pots were incubated for up to 21 days after sowing, with a 16–8 h day–night light cycle, constant humidity and temperatures not exceeding 70% and 26 °C, respectively. In total, 65 plant seeds in each group were maintained for statistical viability of the experiment. The biocontrol ability of B. velezensis KS04AU in planta against Forl ZUM2407 was determined using a visual scoring of the intensity of disease development (DI) as follows:
DI = (n0 × 0 + n1 × 1 + n2 × 2 + n3 × 3 + n4 × 4)/(n0 + n1 + n2 + n3 + n4)
in which n0, n1, n2, n3 and n4 are the number of plants with the indexes 0, 1, 2, 3 and 4, respectively.
Statistical analysis was performed using the statistical program package originLab pro SR1 b9.5.1.195 (OriginLab Corp., Northampton, Northampton, MA, USA). The significant difference between groups was analyzed using one-way ANOVA and post hoc Tukey’s honestly significant difference test at p < 0.05.

3. Result

3.1. Genome Sequencing, Assembly and Comparison

The sequenced complete genome of B. velezensis KS04AU comprised a circular chromosome of 4,063,541 bp in length, with an average G + C content of 46.5%; it did not contain any plasmids (Table 2; Figure 1). The whole genome of KS04AU was predicted to contain a total of 4028 genes with 3941 potential CDS, 3860 of which being CDS-encoding (CDS with proteins). KS04AU contains 87 genes (RNA), 79 of which are transfer ribonucleic acid (tRNA), 5 are non-coding RNA (ncRNA), and 81 pseudogenes. The obtained genome assembly was submitted to the NCBI genome Refseq database under accession number: CP092750.1.
The Prokaryotic Genome Automatic Annotation Pipeline (PGAAP) of the KS04AU genome revealed that 95.82% of CDS are assigned putative biological functions, while 4.18% are genes of hypothetical proteins with unknown functions. This compares with its related genomes SCRM102752, JS25R, FZB42, ONU553, LL3 and IT-45, which have, respectively, 95.29%, 95.80%, 94.98%, 98.27%, 94.98%, and 95.05% CDS associated with putative biological functions (Table 2). Among these strains, KS04AU was predicted to have the largest genome size (Table 2), while their percentages of the total C+ G content in the total genomic nucleotides were approximately equal. Pseudogenes are more present in LL3 and less present in JS25R. Each genome contains more than 79 tRNA, except strain LL3 which carries 72 tRNA. Genes (RNA) are less predicted in KS04AU, compared with other genomes. Among the content of ncRNA (noncoding RNAs), genome FZB42 was predicted to have a smaller number compared with other genomic assemblies (Table 2).
The phylogenetic tree relationship based on the 16S rRNA of B. velezensis KS04AU with other species is represented in Figure 2. The result shows that the 16S rRNA of strain KS04AU is 98.84% (maximal score) identical to B. amyloliquefaciens (GenBank accession no. KU161297.1) and 98.90% (percent identity) to B. subtilis (GenBank accession no. EU489517.1) when blasted on NCBI Blast.
ANI nucleotide analysis revealed that the genome KS04AU is closely related to B. velezensis ONU-553 (Table 3; Figure 3 and Figure 4), with an average nucleotide identity of 99.65% and an average aligned nucleotide of 97.83%, compared to B. velezensis strains JS25R, FZB42, ONU-553, SRCM102752, and B. amyloliquefaciens strains LL3 and IT-45, whose average nucleotide identity and average aligned nucleotide were less than 99.0% (Table 3). In addition, the results showed that B. amyloliquefaciens LL3 is not closely related to the other six strains, since its similarity with other strains was less than 94%.
RAST, the analysis of subsystem distribution followed by comparison among genomes, revealed in the B. velezensis KS04AU genome the presence of 44 genes associated with the control of bacterial mobility and Chemotaxis; 81 genes associated with the cell wall and capsule; 36 genes responsible for virulence, diseases and defense; and 215 for carbohydrates (Figure 5). The KS04AU strain also encodes numerous pathways that are related with the utilization of plant-derived molecules, the production of enzymes, and plant-growth substances. Genes responsible for xenobiotic degradation, such as membrane transport and signal transduction, terpenoids and polyketide metabolism, carbohydrate, lipid, and amino acid metabolic functional genes, translation and metabolism of cofactors such as Fe, P, vitamins, and cell motility were also found in B. velezensis KS04AU.
Identical subsystem features show the presence of all genes, with the exception of FZB42, without phages, prophages, transposable elements, and plasmid genes. However, a difference was observed in the number of genes contained in each subsystem (Figure 6). For example, compared with KS04AU, strain ONU-553 and SCRM102752 have 77 genes involved, respectively, in cell and capsules; 43 and 42 genes associated with control of bacterial mobility and Chemotaxis; 36 and 39 in genes in virulence, diseases and defense; and 215 and 212, respectively, involved in carbohydrates (Table S1).
The PHASTER analysis of the B. velezensis KS04AU genome revealed the presence of four phages in its genome (Table 4 and Figure S1). Two phages were scored as intact (score > 90), one as incomplete (score < 90), and one as questionable (score = 70–90). These two intact prophages (2 and 4) were predicted as phage Aeribacllus AP45 NC_048651 and phage Paenibacillus_Tripp NC_028930, respectively. The incomplete phage was predicted to be Bacillus spp. NC_004166 and the questionable phage Brevibacillus Jimmer NC_041976.
The prophage comparative analysis is presented in Table 5. As can be observed, an incomplete phage (Brevibacillus Jimmer NC_041976) was found in the genomes of KS04AU, ONU-553 and SCRM102752. Among prophages (PHAGE_Bacill_phi105_NC_004167, PHAGE_Brevib_Osiris_NC_028969, and PHAGE_Thermu_OH2_NC_021784) present in LL3, only PHAGE_Brevib_Osiris_NC_028969 was predicted in the JS25R strain, and absent in strains SCRM102752 KS04AU, FZB42, ONU553, KS04AU, and IT-45. PHAGE_Bacill_SPP1_NC_004166 is present only in the KS04AU and ONU 553 strains. PHAGE_Aeriba_AP45_NC_048651 and PHAGE_Paenib_Tripp_NC_028930 are present only in KS04AU.
The prediction of gene clusters involved in synthesizing polyketides and bacteriocins using antiSMASH showed that strain KS04AU possesses 13 gene clusters (Table 6). A comparison to the majority of known gene clusters revealed that these three gene clusters are involved in NRPS (Non-Ribosomal Peptide Synthetase), three transATPKS (trans-Acyl Transferase Polyketide Synthetase), two terpenes, one lantipeptide, two T3PKS, one other KS, and one lantipeptide class-II. Eight clusters were clearly identified as being involved in the synthesis of surfactin, macrolactin, bacillaene, fengycin, difficidin, bacilysin, bacillibactin (siderophore), and mersacidin. This analysis revealed the presence of gene clusters in B. velenzensis KS04AU responsible for the biosynthesis of antimicrobial compounds, regulation, and transport of mineral elements. However, four biosynthetic gene clusters (two terpene, one T3PKS, and one NRPS) failed to match pathways for most known secondary metabolites (Table 6).
Comparative analysis shows that twelve regions are present in B. Velezensis SRCM102752, B. amyloliquefaciens IT-45, and Bacillus velezensis ONU-553; ten regions in B. amyloliquefaciens LL3; thirteen regions in B. velezensis FZB42, B. velezensis JS25R, and B velezensis KS04AU; four regions with non-encoding synthesis metabolites (two regions of terpene, one T3PKS, and NRPS) are present in B. velezensis KS04AU and B. velezensis FZB42; four regions (two terpenes, T3PKS and lanthipeptide-class-II) in B.amyloliquefaciens LL3 and IT-45; and three regions (2 terpene regions and T3PKS) in genomic strains ONU-553, SRCM102752, and JS25R. As shown in (Table 7), the cluster precursor peptide recognition element (RRE) containing LAP responsible for the synthesis of plantazoticin present in B. velezensis FZB42 was absent in KS04AU, SRCM102752, ONU553, JS25R, LL3 and IT-45. The NRPS, transAT-PKS gene cluster responsible for the synthesis of rhizoctocin A present in the SCRM102752 genome was absent in KS04AU, FZB42, ONU553, JS25R, LL3 and IT-45. The gene cluster responsible for synthesis kijanimicin (with 4% of similarity) present in genome SCRM102752 is absent in the other genomes. The class II cluster lanthopeptide responsible of synthesis of meracidin was present only in the genome KS04AU. The transAT-PKS, T3PKS, NRPS gene clusters responsible of synthesis of macrolactin H are absent only in genome strains SCRM102752 and LL3. Gene clusters transAT-PKS and NRPS responsible of synthesis of fengycin and difficidin are not present in the two genomes of Bacillus amyloliquefaciens.
The results obtained by comparison to the ARM gene family (Table 8) show the similarity of the AMR genes. All genomes have the anti-microbe resistance gene family Cfr gene of 23 S ribosomal RNA methyl transferase (clbA), which provides the resistance to antibiotic binding to the ribosomal peptidyl transferase center on the ribosome, reflecting to many drug classes; tet (45) major facilitator superfamily (MFS) antibiotic efflux pump which provides resistance to tetracycline antibiotic; and three small multidrug resistance (SMR) (two gacJ and one gacG) providing bacterial resistance to disinfecting and antiseptic agents.
The comparison of the CRISPR/Cas systems is shown in Table 9. Results revealed that among these strains, CRISPR/Cas Systems are only absent in the LL3 and FZB42 strains. ONU-553, JS25R, and SRCM102752 each carry a single CRISPR element with a different Cas gene number and direction (positive and negative-sense). The Cas genes present in ONU-553 and SRCM102752 have the same direction and repeating consensus, while JS25R carries a unique repeating consensus and 13 Cas genes (where six have a positive sense and seven have a negative sense). KS04AU and IT-45 contain two CRISPR elements with 12 and 13 Cas genes, respectively. The Cas genes present in these genomes are located in different directions. The repeated consensus present in KS04AU is identical to the consensus present in SRCM102752 and ONU 553. The CRISPR/Cas systems present in all genomes are located in different positions (Table 9). Furthermore, a supplement element CAS-TypeID present in strains IT-45 and JS25R, which are located at these positions 1779683–1781929 and 2171815–217406, respectively, is absent in genomes KS04AU, FZB42, ONU-553, SRCM102752, and LL3.
To compare mobile genetic elements in genomes, we used the results obtained after performing ANI analysis. B. amyloliquefaciens strains were then excluded, since the ANIb for the pairwise comparison of these genomes against each of the five genomes of B. velezensis strain was less than 98.00%. Analysis of mobile genetic elements in genomes B. velezensis KS04AU, JS25R, FZB42, ONU-553, and SRCM102752 shows the number of IS-elements—47, 39, 53, 47, and 60, respectively (Table S2). Among these genomes, IS-elements were more present in SRCM102752. The comparative analysis revealed that all genomes shared 22 IS elements (Figure 7). Two IS elements (ISMetp1 and ISIlo12) are only found in KS04AU; ten IS elements (ISIse1, ISChh1, ISDpr8, ISOba2, ISAeme4, ISCysp21, ISGob7, IS231W, IS231V, IS231K) in SRCM102752; eight (ISBth19, ISPa72, ISDph1, ISShes11, ISSso4, ISM1, IS1221I, IS1221G) in FZB42; five (ISAur1, ISCosp2, ISMlo5, ISCth11, ISNg1) in JS25R; and ISSpo1 IS-element in ONU-553. Strains SRCM102752 and FZB42 shared thirteen (ISBce5, ISBce7, ISBth4, IS231Y, ISBce8, MICBce5, MICBce6, MICBth1, ISBce2, MICBce2, IS231D, ISBce4, ISOih1) IS-Elements; KS04AU and ONU-553 shared five (ISDpr6, ISDpr5, ISFnu8, ISAba5, IS1182) IS-Elements; ONU-553 and FZB42 shared one (ISRba1) IS-Elements; four IS-elements (ISPlu5, ISSsu4, ISAau4, ISRru1) are shared between ONU-553 and JS25R.
The full spectrum of the pan-genome (based on Roary analysis) contained 4771 protein-coding genes. Among these, 3334 genes are present in all seven strains (core genes), and the remaining 1437 genes belong to shell genes. Cloud and soft-core genes were not found. Analysis of orthologous gene clusters using OrthoVenn2 revealed that a core of 3371 orthologous genes is shared among seven genomes (Figure 8 and Table 10). In addition, 158, 33, 82, 137, 126, and 100 singleton gene clusters are present in KS04AU, ONU-553, FZB42, JS25R, SRCM102752, IT-45, and IT-45 (Table 10). No unique orthologue gene cluster was found in seven genomes, whereas the genomes of strains KS04AU, JS25R, FZB42, ONU-553, and SRCM102752 contained 26, 10, 7, 3, and 10 unique genes, respectively (Figure 8A). The strain KS04AU shared 2 homologous gene clusters with SRCM102752, 60 with ONU-553, 30 with JS25R, and 27 homologous gene clusters with IT-45 (Figure 8B).

3.2. Antagonistic and Hydrolytic Activities

The antagonistic activity of B. velezensis KS04AU against phytopathogenic fungi are presented in Figure 9. The results after incubation showed inhibition effects of KS04AU on the growth of all phytopathogenic fungi tested in this study, since the zones of inhibition were observed against A. alternata, F. graminarium, F. oxysporum, and P. syringae (Figure 9), compared with the positive and negative control strains, B. mojavensis PS17 and P. putida PCL1760. The ability of B. velezensis KS04AU to produce hydrolytic enzymes is represented in Figure 9b. The results obtained show the lipase, chitinase, protease, cellulase, amylase, and phytase activity of KS04AU (Figure 10).

3.3. Biocontrol Ability of B. velezensis KS04AU to Suppress Tomato Foot and Root Rot

The ability of B. velezensis KS04AU to inhibit the growth of root disease cause by Forl is shown in Figure 11. After 21 days of incubation, the disease index in the group of plants treated with B. velezensis KS04AU was statistically lower compared with the control: B. velezensis KS04AU (disease index of 0.61 ± 0.12188) in comparison with control without treatment (disease index of 1.13 ± 0.0839) and P. putida PCL1760 with (disease index of 0.50 ± 0.13541), respectively. More importantly, compared to the well-known biocontrol P. putida PCL1760, no statistical difference (p < 0.05) was observed in terms of its biocontrol ability in tomato plants against Forl ZUM2407.

4. Discussion

Bacillus velezensis strains received much attention in the past two decades for their enzymatic properties and their wide spectrum range of antagonistic activity against phytopathogens, including F. oxysporum, F. graminearum, Botrytis cinerea, A. alternata, Fulvia fulva, and Ustilaginoidea virens [35,36]. Since microbial strain activities are normally regulated by the substances produced by other microbes in their community (biotic) and the environmental conditions (abiotic), there is a constant mutation in their genomes. These mutations include deletions, insertions, and translocations by mobile elements contributing to the unique features of a strain [37]. Although the phylogenetic tree based on the 16S rRNA genes showed that KS04AU is 98.90% identical to B. subtilis, a similar report showed that B. methylotrophicus KACC 13105 is closely related to B. subtilis [38].
A work published by Borris et al. [39] explains that neither the minimal description of new taxa based on phenotypic characteristics, nor the 16S rRNA nucleotide sequence is enough for strain discrimination of close-related bacteria. The authors used phylogenetic analysis of gyrase subunit A (gyrA) and histidine kinase (cheA) as a complementary approach to discriminate close-related Bacillus strains. Taking this into account, the best method for the discrimination of close-related Bacillus species by full genome analysis was adopted in this work. Full genome analysis of ANI genes did prove that the identity of our strain is closely related to B. velezensis ONU-553, but the genome comparison based on functional group of genes performing a particular biological function showed differences in potassium metabolism, phages, prophages, transposable elements, plasmids, and protein metabolism (Table S1). Likewise, PHASTER analysis showed KS04AU to have a high number of identified phages (four) followed by species, but B. amyloliqueficiens LL3, and ONU-553 but with two identical phages, showed the possibility of higher immunity of our strain to such phages in comparison with strains of the same species.
Recently, the rate of duplication of cells was calculated with the number of phages constituent in a bacterium [40]. The authors confirmed that fast-growing bacteria contain more prophages in their genome, which might be one characteristic of KS04AU. Out of the four phage regions found in the KS04AU genome, the two intact phages were identical to the thermophyllic bacteriophage Aeribacillus bacteriophage AP45 [41], first isolated from the Kamchatka region, Russia, and Paenibacillus larvae bacteriophage Tripp from North Carolina, USA [42]. The two phage regions contain no phage lytic enzyme (lysin) gene to lyse the host strain; we, therefore, suggest KS04AU to be immune to these phages, making it a stable strain in relation to subsequent infections. The key adaptive resistant mechanism of bacteria and archea as a form of systematic immune manipulations depends on clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) genes when the phage absorption or superinfection exclusion (Sie) system is inevitable [43,44]. CRISPR–Cas component system of KS04AU was identical in all parameters, with the exception of B. velezensis JS25R and B. amyloliquefaciens IT-45. The strain KS04AU can comparably be considered as a robust strain in relation to JS25R and IT-45, since the main element responsible for immunity is as targets against phages is the spacer genes.
Secondary metabolites that are responsible for antagonism against phytopathogens (fungal, bacterial, and viral), induction of ISR, and iron-chelating (siderophore) genes are primarily associated with Bacillus of this related strain [45,46,47]. Compared with its closely related strains, the lantibiotic mersacidin gene cluster is only present in the KS04AU strain. The unique property of this secondary metabolite is its antibiotic activity against methicillin-resistant Staphylococcus aureus (MRSA) bacteria [48]. Although mersacidin was reported not to be synthesized in FZB42, a fragment of the gene was found in its genome [49], but in our case the antiSMASH program showed no identity of the gene cluster. The expression of mersacidin in FZB42 was achieved only after the transfer of the biosynthetic part to its gene cluster [50]. In KS04AU, the similarity percentage is 100%, showing the presence of a full gene cluster of this secondary metabolite in this strain.
Most transpositions of IS elements are thought to induce mutations which are capable of altering the fitness of the cell host [51,52], which make them the main factor involved in the evolution and diversification of the bacterial genome. In this study, the comparative analysis revealed 47 IS-Elements in KS04AU compared with its closest-related strain, ONU-553, which has 53.
The ability for B. velezensis to protect plants as an inoculant in the soil depends on its viability in relation to other antibiotic-producing microbes that can inhibit its growth by the different classes of antibiotics they produce. For this purpose, the presence of an antimicrobial resistant gene family was analyzed, and the results confirmed the resistance of KS04AU to different drug classes of antibiotics targeting the alteration gene family Cfr 23S ribosomal RNA methyltransferase (clbA) and the major facilitator superfamily (MFS) antibiotic efflux pump tet (45). These genes were reported for other strains of B. velezensis showing a high resistance to most antibiotics and used as a biocontrol agent against Erwinia amylovora [53].
Finally, the phenotypic parameters to attest to the biocontrol and the plant growth-promoting ability of B. velezensis KS04AU can be seen by its antagonistic activity against the selected phytopathogens (Forl ZUM2407, F. graminearum, A. alternata, P. syringae) and the solubilization of phosphate. Although P. putida PCL1760 was used as a negative control in our antagonistic and enzymatic activity experiments, it was able to inhibit the bacterial pathogen P. syringae in comparison with B. mojavensis PS17 (positive control). Ye et al. [54] reported on the P. putida strain W15Oct28 that was able to inhibit the growth of Staphylococcus aureus, Pseudomonas aeruginosa and the plant pathogen P. syringae, stating this characteristic as unusual. There is no report on P. putida PCL1760 producing active metabolic compounds able to inhibit the plant pathogen P. syringae, but there are several reports of it as a good root-colonizing bacteria able to control tomato foot and root rot [55]. As a biocontrol agent against Forl ZUM2407, B. velezensis KS04AU was able to control the disease in tomato and did not differ statistically from the positive control PCL1760.

5. Conclusions

To summarize, characterization of Bacillus species by phenotypic analysis and 16S rRNA is inadequate without multi-loci or genomic sequencing analysis. The genomic characteristics of B. velezensis KS04AU, in comparison with its strains of the same species and related species, provides an overview of the unique characteristics of the strain. The enzymatic activity of strain KS04AU attests the absence of down-regulation in relation to the genes responsible for the tested exoenzymes and secondary metabolites. The planta experiment of its biocontrol ability also shows that B. velezensis KS04AU is a good candidate for biopreparation against plant pathogens. Reportedly, most B. velezensis strains have these abilities, and genomic analysis of KS04AU provides comprehensive information on the unique characteristics of this strain.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/ijpb13030018/s1, Figure S1: Intact Prophage founded in B. velezensis KS04AU. PHAGE_Aeriba_AP45_NC_048651 (region 2) and PHAGE_Paenib_Tripp_NC_02893 (region 4), Table S1: Comparative analysis of functional subsystem category in genomes of B. velezensis KS04AU, SCRM102752, FZB42, ONU553, and B. amyloliquefaciens LL3 and IT-45 based on SEED servers, Table S2: Analysis of mobile genetic elements (IS-Elements) of genome Bacillus velezensis KS04AU, JS25R, FZB42, ONU-553, and SRCM102752. Table S3: Mobile genetic elements (IS-Elements) shared between genomes used in this study.

Author Contributions

Conceptualization, D.M.A. and R.G.C.D.; methodology, D.M.A., R.G.C.D. and S.Z.V.; data acquisition and analysis, D.M.A., R.G.C.D. and E.U.S.; writing—original draft preparation, D.M.A. and R.G.C.D.; writing—review and editing, R.G.C.D., D.M.A. and S.Z.V.; supervision, D.M.A. and S.Z.V. All authors have read and agreed to the published version of the manuscript.

Funding

The study was conducted with financial support provided by the Ministry of Education and Science of the Russian Federation, Grant # RF-1930.61321X0001/15.IP.21.0020.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Not applicable.

Conflicts of Interest

The authors have no conflict of interest to declare.

References

  1. Fira, D.; Dimkić, I.; Berić, T.; Lozo, J.; Stanković, S. Biological control of plant pathogens by Bacillus species. J. Biotechnol. 2018, 285, 44–55. [Google Scholar] [CrossRef]
  2. Ongena, M.; Jacques, P. Bacillus lipopeptides: Versatile weapons for plant disease biocontrol. Trends Microbiol. 2008, 16, 115–125. [Google Scholar] [CrossRef]
  3. Ruiz-Garcia, C.; Bejar, V.; Martinez-Checa, F.; Llamas, I.; Quesada, E. Bacillus velezensis sp. nov., a surfactant-producing bacterium isolated from the river Velez in Malaga, southern Spain. Int. J. Syst. Evol. Microbiol. 2005, 55, 191–195. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Cao, Y.; Pi, H.; Chandrangsu, P.; Li, Y.; Wang, Y.; Zhou, H.; Xiong, H.; Helmann, J.D.; Cai, Y. Antagonism of two plant-growth promoting Bacillus velezensis isolates against Ralstonia solanacearum and Fusarium oxysporum. Sci. Rep. 2018, 8, 4360. [Google Scholar] [CrossRef] [PubMed]
  5. Chen, L.; Wang, X.; Ma, Q.; Bian, L.; Liu, X.; Xu, Y.; Zhang, H.; Shao, J.; Liu, Y. Bacillus velezensis CLA178-induced systemic resistance of Rosa multiflora against crown gall disease. Front. Microbiol. 2020, 11, 11:587667. [Google Scholar] [CrossRef] [PubMed]
  6. Yi, Y.; Zhang, Z.; Zhao, F.; Liu, H.; Yu, L.; Zha, J.; Wang, G. Probiotic potential of Bacillus velezensis JW: Antimicrobial activity against fish pathogenic bacteria and immune enhancement effects on Carassius auratus. Fish Shellfish Immunol. 2018, 78, 322–330. [Google Scholar] [CrossRef]
  7. 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, e0198560. [Google Scholar] [CrossRef] [Green Version]
  8. Dunlap, C.A.; Kim, S.J.; Kwon, S.W.; Rooney, A.P. Phylogenomic analysis shows that Bacillus amyloliquefaciens subsp. plantarum is a later heterotypic synonym of Bacillus methylotrophicus. Int. J. Syst. Evol. 2015, 65 Pt 7, 2104–2109. [Google Scholar] [CrossRef]
  9. Dunlap, C.; Kim, S.J.; Kwon, S.W.; Rooney, A. Bacillus velezensis is not a later heterotypic synonym of Bacillus amyloliquefaciens, Bacillus methylotrophicus, Bacillus amyloliquefaciens subsp. plantarum and ‘Bacillus oryzicola’ are later heterotypic synonyms of Bacillus velezensis based on phylogenomics. Int. J. Syst. Evol. Microbiol. 2016, 66, 1212–1217. [Google Scholar] [CrossRef]
  10. Kaltz, O.; Escobar-Páramo, P.; Hochberg, M.E.; Cohen, J.E. Bacterial microcosms obey Taylor’s law: Effects of abiotic and biotic stress and genetics on mean and variance of population density. Ecol. Process. 2012, 1, 5. [Google Scholar] [CrossRef] [Green Version]
  11. Adeniji, A.A.; Loots, D.T.; Babalola, O.O. Bacillus velezensis: Phylogeny, useful applications, and avenues for exploitation. Appl. Microbiol. Biotechnol. 2019, 103, 3669–3682. [Google Scholar] [CrossRef] [PubMed]
  12. Brown, J.; Pirrung, M.; McCue, L.A. FQC Dashboard: Integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool. Bioinformatics 2017, 33, 3137–3139. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [Green Version]
  14. Wick, R.R.; Judd, L.M.; Gorrie, C.L.; Holt, K.E. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput. Biol. 2017, 13, e100559. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Gurevich, A.; Saveliev, V.; Vyahhi, N.; Tesler, G. QUAST: Quality assessment tool for genome assemblies. Bioinformatics 2013, 29, 1072–1075. [Google Scholar] [CrossRef] [PubMed]
  16. Richter, M.; Rosselló-Móra, R. Shifting the genomic gold standard for the prokaryotic species definition. Proc. Natl. Acad. Sci. USA 2009, 106, 19126–19131. [Google Scholar] [CrossRef] [Green Version]
  17. Darling, A.C.; Mau, B.; Blattner, F.R.; Perna, N.T. Mauve: Multiple alignment of conserved genomic sequence with rearrangements. Genome Res. 2004, 14, 1394–1403. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Chu, C.; Li, X.; Wu, Y. GAPPadder: A sensitive approach for closing gaps on draft genomes with short sequence reads. BMC Genom. 2019, 20, 426. [Google Scholar] [CrossRef] [Green Version]
  19. Seemann, T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics 2014, 30, 2068–2069. [Google Scholar] [CrossRef]
  20. Tatusova, T.; DiCuccio, M.; Badretdin, A.; Chetvernin, V.; Nawrocki, E.P.; Zaslavsky, L.; Lomsadze, A.; Pruitt, K.D.; Borodovsky, M.; Ostell, J. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res. 2016, 44, 6614–6624. [Google Scholar] [CrossRef]
  21. Besemer, J.; Lomsadze, A.; Borodovsky, M. GeneMarkS: A self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res. 2001, 29, 2607–2618. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. McArthur, A.G.; Waglechner, N.; Nizam, F.; Yan, A.; Azad, M.A.; Baylay, A.J.; Wright, G.D. The comprehensive antibiotic resistance database. Antimicrob. Agents Chemother. 2013, 57, 3348–3357. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Zhou, Y.; Liang, Y.; Lynch, K.H.; Dennis, J.J.; Wishart, D.S. PHAST: A fast phage search tool. Nucleic Acids Res. 2011, 39 (Suppl. S2), W347–W352. [Google Scholar] [CrossRef]
  24. Blin, K.; Shaw, S.; Steinke, K.; Villebro, R.; Ziemert, N.; Lee, S.Y.; Weber, T. antiSMASH 5.0: Updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res. 2019, 47, W81–W87. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Carver, T.; Thomson, N.; Bleasby, A.; Berriman, M.; Parkhill, J. DNAPlotter: Circular and linear interactive genome visualization. Bioinformatics 2009, 25, 119–120. [Google Scholar] [CrossRef]
  26. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 2021, 38, 3022–3027. [Google Scholar] [CrossRef] [PubMed]
  27. Jones, D.T.; Taylor, W.R.; Thornton, J.M. The rapid generation of mutation data matrices from protein sequences. Bioinformatics 1992, 8, 275–282. [Google Scholar] [CrossRef]
  28. Xu, L.; Dong, Z.; Fang, L.; Luo, Y.; Wei, Z.; Guo, H.; Wang, Y. OrthoVenn2: A web server for whole-genome comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res. 2019, 47, W52–W58. [Google Scholar] [CrossRef] [Green Version]
  29. Grissa, I.; Vergnaud, G.; Pourcel, C. CRISPRFinder: A web tool to identify clustered regularly interspaced short palindromic repeats. Nucleic Acids Res. 2007, 35, W52–W57. [Google Scholar] [CrossRef] [Green Version]
  30. Couvin, D.; Bernheim, A.; Toffano-Nioche, C.; Touchon, M.; Michalik, J.; Néron, B.; Pourcel, C. CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins. Nucleic Acids Res. 2018, 46, W246–W251. [Google Scholar] [CrossRef] [Green Version]
  31. Tarailo-Graovac, M.; Chen, N.S. Using repeat masker to identify repetitive elements in genomic sequences. Curr. Protoc. Bioinform. 2009, 5, 4.10.1–4.10.14. [Google Scholar] [CrossRef]
  32. Aziz, R.K.; Bartels, D.; Best, A.A.; DeJongh, M.; Disz, T.; Edwards, R.A.; Zagnitko, O. The RAST Server: Rapid annotations using subsystems technology. BMC Genom. 2008, 9, 75. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Teather, R.M.; Wood, P.J. Use of Congo red-polysaccharide interactions in enumeration and characterization of cellulolytic bacteria from the bovine rumen. Appl. Environ. Microbiol. 1982, 43, 777–780. [Google Scholar] [CrossRef] [Green Version]
  34. Howson, S.J.; Davis, R.P. Production of phytate-hydrolysing enzyme by some fungi. Enzym. Microb. Technol. 1983, 5, 377–382. [Google Scholar] [CrossRef]
  35. Huang, L.; Li, Q.C.; Hou, Y.; Li, G.Q.; Yang, J.Y.; Li, D.W.; Ye, J.R. Bacillus velezensis strain HYEB5-6 as a potential biocontrol agent against anthracnose on Euonymus japonicus. Biocontrol. Sci. Technol. 2017, 27, 636–653. [Google Scholar] [CrossRef]
  36. Myo, E.M.; Liu, B.; Ma, J.; Shi, L.; Jiang, M.; Zhang, K.; Ge, B. Evaluation of Bacillus velezensis NKG-2 for bio-control activities against fungal diseases and potential plant growth promotion. Biol. Control 2019, 134, 23–31. [Google Scholar] [CrossRef]
  37. Oda, Y.; Larimer, F.W.; Chain, P.S.; Malfatti, S.; Shin, M.V.; Vergez, L.M.; Hauser, L.; Land, M.L.; Braatsch, S.; Beatty, J.T.; et al. Multiple genome sequences reveal adaptations of a phototrophic bacterium to sediment microenvironments. Proc. Natl. Acad. Sci. USA 2008, 105, 18543–18548. [Google Scholar] [CrossRef] [Green Version]
  38. Rooney, A.P.; Price, N.P.; Ehrhardt, C.; Swezey, J.L.; Bannan, J.D. Phylogeny and molecular taxonomy of the Bacillus subtilis species complex and description of Bacillus subtilis subsp. inaquosorum subsp. nov. Int. J. Syst. Evol. Microbiol. 2009, 59, 2429–2436. [Google Scholar] [CrossRef]
  39. Borriss, R.; Chen, X.H.; Rueckert, C.; Blom, J.; Becker, A.; Baumgarth, B.; Fan, B.; Pukall, R.; Schumann, P.; Spröer, C.; et al. Relationship of Bacillus amyloliquefaciens clades associated with strains DSM 7T and FZB42T: A proposal for Bacillus amyloliquefaciens subsp. amyloliquefaciens subsp. nov. and Bacillus amyloliquefaciens subsp. plantarum subsp. nov. based on complete genome sequence comparisons. Int. J. Syst. Evol. Microbiol. 2011, 61, 786–1801. [Google Scholar] [CrossRef]
  40. Pattenden, T.; Eagles, C.; Wahl, L.M. Host life-history traits influence the distribution of prophages and the genes they carry. Philos. Trans. R. Soc. B 2022, 377, 20200465. [Google Scholar] [CrossRef]
  41. Morozova, V.; Bokovaya, O.; Kozlova, Y.; Kurilshikov, A.; Babkin, I.; Tupikin, A.; Bondar, A.; Ryabchikova, E.; Brayanskaya, A.; Peltek, S.; et al. A novel thermophilic Aeribacillus bacteriophage AP45 isolated from the Valley of Geysers, Kamchatka: Genome analysis suggests the existence of a new genus within the Siphoviridae family. Extremophiles 2019, 23, 599–612. [Google Scholar] [CrossRef] [PubMed]
  42. Abraham, J.; Bousquet, A.C.; Bruff, E.; Carson, N.; Clark, A.; Connell, A.; Davis, Z.; Dums, J.; Everington, C.; Groth, A.; et al. Paenibacillus larvae phage Tripp genome has 378-base-pair terminal repeats. Genome Announc. 2016, 4, e01498-15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Labrie, S.J.; Samson, J.E.; Moineau, S. Bacteriophage resistance mechanisms. Nat. Rev. Microbiol. 2010, 8, 317–327. [Google Scholar] [CrossRef] [PubMed]
  44. Marraffini, L.A. CRISPR-Cas immunity against phages: Its effects on the evolution and survival of bacterial pathogens. PLoS Pathog. 2013, 9, e1003765. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Wu, G.; Liu, Y.; Xu, Y.; Zhang, G.; Shen, Q.; Zhang, R. Exploring elicitors of the beneficial rhizobacterium Bacillus amyloliquefaciens SQR9 to induce plant systemic resistance and their interactions with plant signaling pathways. Mol. Plant-Microbe Interact. 2018, 31, 560–567. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  46. Camele, I.; Elshafie, H.S.; Caputo, L.; Sakr, S.H.; De Feo, V. Bacillus mojavensis: Biofilm formation and biochemical investigation of its bioactive metabolites. J. Biol. Res. 2019, 92, 39–45. [Google Scholar] [CrossRef]
  47. Elshafie, H.S.; Sakr, S.; Bufo, S.A.; Camele, I. An attempt of biocontrol the tomato-wilt disease caused by Verticillium dahliae using Burkholderia gladioli pv. agaricicola and its bioactive secondary metabolites. Int. J. Plant Biol. 2017, 8, 57–60. [Google Scholar] [CrossRef] [Green Version]
  48. Kruszewska, D.; Sahl, H.G.; Bierbaum, G.; Pag, U.; Hynes, S.O.; Ljungh, A. Mersacidin eradicates methicillin-resistant Staphylococcus aureus (MRSA) in a mouse rhinitis model. J. Antimicrob. Chemother. 2004, 54, 648–653. [Google Scholar] [CrossRef]
  49. Borriss, R.; Wu, H.; Gao, X. Secondary Metabolites of the Plant Growth Promoting Model Rhizobacterium Bacillus velezensis FZB42 Are Involved in Direct Suppression of Plant Pathogens and in Stimulation of Plant-Induced Systemic Resistance; Springer: Singapore, 2019; pp. 147–168. [Google Scholar] [CrossRef]
  50. Herzner, A.M.; Dischinger, J.; Szekat, C.; Josten, M.; Schmitz, S.; Yakeleba, A.; Reinartz, R.; Jansen, A.; Sahl, H.G.; Piel, J.; et al. Expression of the lantibiotic mersacidin in Bacillus amyloliquefaciens FZB42. PLoS ONE 2011, 6, e22389. [Google Scholar] [CrossRef] [Green Version]
  51. Touchon, M.; Rocha, E.P.C. Causes of insertion sequences abundance in prokaryotic genomes. Mol. Biol. Evol. 2007, 24, 969–981. [Google Scholar] [CrossRef] [Green Version]
  52. Siguier, P.; Gourbeyre, E.; Chandler, M. Bacterial insertion sequences: Their genomic impact and diversity. FEMS Microbiol. Rev. 2014, 38, 865–891. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Medhioub, I.; Cheffi, M.; Tounsi, S.; Triki, M.A. Study of Bacillus velezensis OEE1 potentialities in the biocontrol against Erwinia amylovora, causal agent of fire blight disease of rosaceous plants. Biol. Control 2022, 167, 104842. [Google Scholar] [CrossRef]
  54. Ye, L.; Hildebrand, F.; Dingemans, J.; Ballet, S.; Laus, G.; Matthijs, S.; Berendsen, R.; Cornelis, P. Draft genome sequence analysis of a Pseudomonas putida W15Oct28 strain with antagonistic activity to Gram-positive and Pseudomonas sp. pathogens. PLoS ONE 2014, 9, e110038. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Validov, S.Z.; Kamilova, F.; Lugtenberg, B.J. Pseudomonas putida strain PCL1760 controls tomato foot and root rot in stonewool under industrial conditions in a certified greenhouse. Biol. Control 2009, 48, 6–11. [Google Scholar] [CrossRef]
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Figure 1. Draft genome of B. velezensis KS04AU. Blue circle—CDS on the plus strand, red circle—CDS on the minus strand, black circle is GC-skew plot (dark blue portion—GC-skew positive, olive-purple portion—GC-skew negative).
Figure 1. Draft genome of B. velezensis KS04AU. Blue circle—CDS on the plus strand, red circle—CDS on the minus strand, black circle is GC-skew plot (dark blue portion—GC-skew positive, olive-purple portion—GC-skew negative).
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Figure 2. The phylogenetic analysis based on the 16S rRNA genes of strain KS04AU based on NCBI blast System. The tree was generated by MEGA 11 using the neighbor-joining method.
Figure 2. The phylogenetic analysis based on the 16S rRNA genes of strain KS04AU based on NCBI blast System. The tree was generated by MEGA 11 using the neighbor-joining method.
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Figure 3. Blast Ring Image Generator (BRIG) plot showing a whole genome comparison. The figure shows BLAST comparisons of B. velezensis strains KS04AU, ONU-553, FZB42, JS25R, SRCM102752 and B. amyloliquefaciens strains LL3 and IT-45.
Figure 3. Blast Ring Image Generator (BRIG) plot showing a whole genome comparison. The figure shows BLAST comparisons of B. velezensis strains KS04AU, ONU-553, FZB42, JS25R, SRCM102752 and B. amyloliquefaciens strains LL3 and IT-45.
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Figure 4. Neighbor-joining phylogenetic tree constructed from 16S rRNA extracted from genomes using the ContEst16S tool. The tree was generated by MEGA 11 using the neighbor-joining method.
Figure 4. Neighbor-joining phylogenetic tree constructed from 16S rRNA extracted from genomes using the ContEst16S tool. The tree was generated by MEGA 11 using the neighbor-joining method.
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Figure 5. Subsystem Information for B. velezensis KS04AU. In subsystem coverage, 29% is indicated in subsystem coverage with a total of 1180 genes (1125 non-hypotheticals and 55 hypotheticals) and 71% is not indicated in subsystem coverage with a total of 2961 genes (1508 non-hypotheticals and 1453 hypotheticals).
Figure 5. Subsystem Information for B. velezensis KS04AU. In subsystem coverage, 29% is indicated in subsystem coverage with a total of 1180 genes (1125 non-hypotheticals and 55 hypotheticals) and 71% is not indicated in subsystem coverage with a total of 2961 genes (1508 non-hypotheticals and 1453 hypotheticals).
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Figure 6. Comparison of the functional subsystem category in genomes of B. velezensis, SCRM102752 KS04AU, FZB42, ONU553, KS04AU, and B. amyloliquefaciens LL3 and IT-45 based on SEED servers. Functional classification is based on annotated and assigned roles of genes using RASTtk. Each color bar shows genes involved in a specific subsystem category.
Figure 6. Comparison of the functional subsystem category in genomes of B. velezensis, SCRM102752 KS04AU, FZB42, ONU553, KS04AU, and B. amyloliquefaciens LL3 and IT-45 based on SEED servers. Functional classification is based on annotated and assigned roles of genes using RASTtk. Each color bar shows genes involved in a specific subsystem category.
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Figure 7. Comparative analysis of mobile genetic elements (IS-Elements) of genome B. velezensis strains KS04AU, JS25R, FZB42, ONU-553, and SRCM102752. Data in italics represent the group number with IS-elements shared between genomes (Table S3).
Figure 7. Comparative analysis of mobile genetic elements (IS-Elements) of genome B. velezensis strains KS04AU, JS25R, FZB42, ONU-553, and SRCM102752. Data in italics represent the group number with IS-elements shared between genomes (Table S3).
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Figure 8. Genomic analysis using Orthovenn2. Venn diagram (A) displays the distribution of shared orthologous clusters among B. velezensis and amyloliquefaciens strains. (B) The occurrence table shows the occurrence pattern of shared orthologous groups among selected strains. (C) Pairwise heatmap of overlapping cluster numbers of compared genomes. Each cell shows the overlap cluster between species. The overlapping cluster numbers refer to the number of gene clusters shared among B. velezensis and amyloliquefaciens strains.
Figure 8. Genomic analysis using Orthovenn2. Venn diagram (A) displays the distribution of shared orthologous clusters among B. velezensis and amyloliquefaciens strains. (B) The occurrence table shows the occurrence pattern of shared orthologous groups among selected strains. (C) Pairwise heatmap of overlapping cluster numbers of compared genomes. Each cell shows the overlap cluster between species. The overlapping cluster numbers refer to the number of gene clusters shared among B. velezensis and amyloliquefaciens strains.
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Figure 9. The antagonistic activity of B. velezensis KS04AU against phytopathogenic fungi F. oxysporium (a,d), F. graminarium (b,e), A. alternata (c,f) after 5 days (I) and 14 days (II) of incubation. The antagonistic activity of B. velezensis KS04AU against phytopathogenic bacteria P. syringae (III) after 1 day (g) and 2 days (h) of incubation.
Figure 9. The antagonistic activity of B. velezensis KS04AU against phytopathogenic fungi F. oxysporium (a,d), F. graminarium (b,e), A. alternata (c,f) after 5 days (I) and 14 days (II) of incubation. The antagonistic activity of B. velezensis KS04AU against phytopathogenic bacteria P. syringae (III) after 1 day (g) and 2 days (h) of incubation.
Ijpb 13 00018 g009
Ijpb 13 00018 g010 550
Figure 10. Hydrolytic enzymatic activity of B. velezensis KS04AU with arrows indicating enzymatic zone of activity. Plates showing cellulase (a), chitinase (b), protease (c), amylase (d), lipase (e), and phytase (f).
Figure 10. Hydrolytic enzymatic activity of B. velezensis KS04AU with arrows indicating enzymatic zone of activity. Plates showing cellulase (a), chitinase (b), protease (c), amylase (d), lipase (e), and phytase (f).
Ijpb 13 00018 g010
Ijpb 13 00018 g011 550
Figure 11. Biocontrol ability of B. velezensis KS04AU in suppression of tomato root rot disease diseases caused by Forl ZUM2407. Different letters above the bars indicate a statistically significant difference between groups at p < 0.05.
Figure 11. Biocontrol ability of B. velezensis KS04AU in suppression of tomato root rot disease diseases caused by Forl ZUM2407. Different letters above the bars indicate a statistically significant difference between groups at p < 0.05.
Ijpb 13 00018 g011
Table
Table 1. Genomes used in this study.
Table 1. Genomes used in this study.
Microbial StrainNCBI Reference Sequence
B. velezensis SRCM102752NZ_CP028961.1
B. velezensis FZB42NC_009725.2
B. velezensis JS25RNZ_CP009679.1
B. velezensis KS04AUNZ_CP092750.1
B. velezensis ONU-553NZ_CP043416.1
B. amyloliquefaciens IT-45NC_020272.1
B. amyloliquefaciens LL3NC_017190.1
Table
Table 2. Comparative genomic features of B. velezensis KS04AU with closest-related strain.
Table 2. Comparative genomic features of B. velezensis KS04AU with closest-related strain.
FeaturesKS04AUSRCM102752ONU-553FZB42JS25RLL3IT-45
Genome (bp)4,063,5413,971,5093,934,5633,918,5964,006,0023,995,2273,928,857
G + C (%)46.546.4046.7046.5046.3945.6946.59
Genes (total)4028395038893870393341513927
Total CDS3941383237713749382640523797
CDS coding 3860376137063676376839433733
Genes (RNA)8711811812110799130
tRNA79868688817295
ncRNA5554555
Pseudo Genes 817165735810964
Table
Table 3. Genomic comparative analysis of B. velezensis KS04AU with 6 closest related Bacillus species based on ANI (average nucleotide identity).
Table 3. Genomic comparative analysis of B. velezensis KS04AU with 6 closest related Bacillus species based on ANI (average nucleotide identity).
B. velezensis KS04AUB. velezensis JS25RB. velezensis FZB42B. velezensis ONU-553B. velezensis SRCM102752B. amyloliquefaciens LL3B. amyloliquefaciens IT-45
B. velezensis KS04AU––98.19
(91.60)		98.66
(91.09)		99.53
(95.32)		98.31
(90.54)		93.29
(86.11)		97.38
(90.99)
B. velezensis JS25R98.20
(92.47)		––98.19
(92.03)		98.20
(92.58)		97.88
(91.14)		93.34
(86.41)		97.47
(92.00)
B. velezensis FZB4298.76
(93.84)		98.26
(94.17)		––98.77
(94.59)		98.62
(93.57)		93.30
(87.70)		97.51
(93.32)
B. velezensis ONU-55399.65
(97.83)		98.31
(94.21)		98.78
(94.25)		––98.44
(93.53)		93.40
(88.43)		97.53
(94.09)
B. velezensis SRCM10275298.34
(92.08)		97.80
(92.01)		98.56
(92.41)		98.39
(92.62)		––93.32
(87.67)		97.18
(91.83)
B. amyloliquefaciens LL393.78
(86.01)		93.77
(85.59)		93.74
(84.70)		93.82
(86.01)		93.80
(86.04)		––93.65
(85.92)
B. amyloliquefaciens IT-45.97.59
(93.22)		97.67
(93.34)		97.60
(92.86)		97.62
(93.94)		97.40
(92.58)		93.31
(88.40)		––
N.B. Data in bold—average nucleotide based on blast (ANib); data in italics—average aligned nucleotide.
Table
Table 4. Prophage regions found in Bacillus velezensis KS04AU genome.
Table 4. Prophage regions found in Bacillus velezensis KS04AU genome.
RegionRegion LengthCompletenessPhage Hit ProteinHypothetical
Protein		Specific
Keyword		Region PositionPossible PhageG + C
Percentage
118.1 KbIncomplete (10)135NA3336–21,513PHAGE_Bacill_SPP1_NC_00416644.55%
249.1 Kbintact (120)4131integrase, terminase, tail1,107,820–1,157,010PHAGE_Aeriba_AP45_NC_04865141.77%
331.3 Kbquestionable2916tail, plate, capsid1,203,112–1,234,419PHAGE_Brevib_Jimmer2_NC_04197646.98%
497.5 Kbintact6141integrase, tail, terminase, capsid3,892,492–3,990,010PHAGE_Paenib_Tripp_NC_02893047.43%
Table
Table 5. Comparison of prophages found in selected genomes.
Table 5. Comparison of prophages found in selected genomes.
PhagePresence (+) or Absence (−) in Related Strains
KS04AUSRCM102752ONU 553FZB42JS25RLL3IT-45
PHAGE_Aeriba_AP45_NC_048651+−−−−−−
PHAGE_Brevib_Jimmer2_NC_041976+++−−−−
PHAGE_Paenib_Tripp_NC_028930+−−−−−−
PHAGE_Bacill_SPP1_NC_004166+−+−−−−
PHAGE_Thermu_OH2_NC_021784−−−−−+−
PHAGE_Thermu_TMA_NC_015937−−−−+−−
PHAGE_Brevib_Osiris_NC_028969−−−−++−
PHAGE_Bacill_phi105_NC_004167−−−−−+−
Table
Table 6. Secondary metabolite biosynthetic gene clusters into genomic regions of B. velezensis KS04AU.
Table 6. Secondary metabolite biosynthetic gene clusters into genomic regions of B. velezensis KS04AU.
Genomic RegionTypeFromToMost Similar Known ClusterSimilarity
Region 1NRPS297,001359,149surfactinNRP: Lipopeptide95%
Region 2PKS-like881,875923,119butirosin A/butirosin BSaccharide7%
Region 3terpene1,009,2981,026,466
Region 4transAT-PKS1,379,8291,467,645macrolactin HPolyketide100%
Region 5transAT-PKS, T3PKS, NRPS1,689,8281,790,022bacillaenePolyketide + NRP100%
Region 6NRPS, transAT-PKS, betalactone1,856,6771,988,381fengycinNRP100%
Region 7terpene2,011,4062,033,289
Region 8T3PKS2,083,7242,124,824
Region 9transAT-PKS2,252,7982,344,192difficidinPolyketide + NRP100%
Region 10NRPS, RiPP-like2,955,2873,005,799bacillibactinNRP100%
Region 11NRPS3,284,1823,330,146
Region 12other3,550,7853,592,203bacilysinOther100%
Region 13lanthipeptide-class-ii3,740,3163,763,504mersacidinRiPP: Lanthipeptide100%
Table
Table 7. Comparative analysis of secondary metabolite clusters of B. velezensis KS04AU with closest-related strains.
Table 7. Comparative analysis of secondary metabolite clusters of B. velezensis KS04AU with closest-related strains.
Presence (+) or Absence (−) of Secondary Metabolite Clusters in Related Strains
SynthetaseMetabolitesKS04AUSRCM102752ONU-553FZB42JS25RLL3IT-45
PKS-likesurfactin+++++++
terpene−+++++++
transAT-PKSbutirosin A/butirosin B+++++++
transAT-PKS, T3PKS, NRPSmacrolactin H+−+++−+
NRPS, transAT-PKS, betalactonebacillaene+++++++
terpene−+++++++
T3PKS−+++++
transAT-PKSfengycin+++++
NRPS, RiPP-like−+++++++
NRPSdifficidin+++++
NRPS, RiPP-likebacillibactin+++++++
NRPS +++++
otherbacilysin+++++++
lanthipeptide-class-iimersacidin+−−−−−−
cyclic-lactone-autoinducer, lanthipeptide-class-IIkijanimicin−+−−−−−
NRPS, transAT-PKSrhizocticin A−+−−−−−
RRE-containing, LAPplantazolicin−−−+−−−
Table
Table 8. Comparison of B. velezensis KS04AU ARM genes with closest-related strains.
Table 8. Comparison of B. velezensis KS04AU ARM genes with closest-related strains.
ARO Term ARMGene FamilyDrug ClassResistance MechanismPresence (+) or Absence (−)
KS04AUSRCM102752ONU 553FZB42JS25RLL3IT-45
clbACfr 23S ribosomal RNA methyltransferaseIncosamide antibiotic, streptogramin antibiotic, streptogramin A antibiotic, oxazolidinone antibiotic, phenicol antibiotic, pleuromutilin antibioticAntibiotic target alteration+++++++
tet (45)Major facilitator superfamily (MFS) antibiotic efflux pumpTetracycline antibioticAntibiotic efflux+++++++
qacJsmall multidrug resistance (SMR) antibiotic efflux pumpDisinfecting agents and antisepticsAntibiotic efflux+++++++
qacGsmall multidrug resistance (SMR) antibiotic efflux pumpDisinfecting agents and antisepticsAntibiotic efflux+++++++
qacJsmall multidrug resistance (SMR) antibiotic efflux pumpDisinfecting agents and antisepticsAntibiotic efflux+++++++
qacJsmall multidrug resistance (SMR) antibiotic efflux pumpDisinfecting agents and antisepticsAntibiotic efflux−−−−−−+
BcIclass A Bacillus cereus Bc beta-lactamasecephalosporin, penemantibiotic inactivation+++++++
Table
Table 9. Comparison of the CRISPR elements in Bacillus velezensis and amyloliquefaciens strains.
Table 9. Comparison of the CRISPR elements in Bacillus velezensis and amyloliquefaciens strains.
Strain Number of CRISPR/CAS ElementStartEndSpacer/GeneRepeat Consensus/Cas GenesDirection
KS04AU2Cas66,9953,697,96612Cas3_TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI(–)—8 Cas genes
(+)—4 Cas genes
CRISPR665,256665,3631CGGAGGATATCCGGGATACGGTTTND
CRISPR712,560712,6541TTCACCGGGGCAACGGGGCTGACND
SRCM1027521CAS61,0883,747,58712Cas3_TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI(–)—8 Cas genes
(+)—4 Cas genes
CRISPR780,220780,3141TTCACCGGGGCAACGGGGCTGACND
ONU 5531CAS61,0883,747,58712Cas3_TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI(–)—8 Cas genes
(+)—4 Cas genes
CRISPR TTCACCGGGGCAACGGGGCTGAC ND
FZB420
JS25R1CAS61,5003,812,92013Cas3_TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI(–)—7 Cas genes
(+)—6 Cas genes
CRISPR447,873447,9551AAGAAATCGGCCAAAAAGGCGGAND
CAS-TypeID2,171,8152,174,0611cas3_TypeID-
LL30
IT-452CAS 13Cas3_TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ TypeI, Cas3_ Type(–)—6 Cas genes
(+)—7 Cas genes
CRISPR2,680,2762,680,4021TGCTCGCAATCTCGTCCGCTTTTCCCATGAATGAGGTCGTGAACTTND
CRISPR3,044,1913,044,3201AACAGGCTTTCAGCGGGGAATCCGGCGGACAGCAGCAND
CAS-TypeID1,779,6831,781,9291cas3_TypeID
Table
Table 10. Comparative analysis of gene clusters using OrthoVenn2.
Table 10. Comparative analysis of gene clusters using OrthoVenn2.
SpeciesGene ClustersSingletons
KS04AU3727158
ONU-553368533
FZB42361482
JS25R3635137
SRCM1027523666126
IT-453662100
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Diabankana, R.G.C.; Shulga, E.U.; Validov, S.Z.; Afordoanyi, D.M. Genetic Characteristics and Enzymatic Activities of Bacillus velezensis KS04AU as a Stable Biocontrol Agent against Phytopathogens. Int. J. Plant Biol. 2022, 13, 201-222. https://doi.org/10.3390/ijpb13030018

AMA Style

Diabankana RGC, Shulga EU, Validov SZ, Afordoanyi DM. Genetic Characteristics and Enzymatic Activities of Bacillus velezensis KS04AU as a Stable Biocontrol Agent against Phytopathogens. International Journal of Plant Biology. 2022; 13(3):201-222. https://doi.org/10.3390/ijpb13030018

Chicago/Turabian Style

Diabankana, Roderic Gilles Claret, Elena Urievna Shulga, Shamil Zavdatovich Validov, and Daniel Mawuena Afordoanyi. 2022. "Genetic Characteristics and Enzymatic Activities of Bacillus velezensis KS04AU as a Stable Biocontrol Agent against Phytopathogens" International Journal of Plant Biology 13, no. 3: 201-222. https://doi.org/10.3390/ijpb13030018

APA Style

Diabankana, R. G. C., Shulga, E. U., Validov, S. Z., & Afordoanyi, D. M. (2022). Genetic Characteristics and Enzymatic Activities of Bacillus velezensis KS04AU as a Stable Biocontrol Agent against Phytopathogens. International Journal of Plant Biology, 13(3), 201-222. https://doi.org/10.3390/ijpb13030018

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