Whole genome-sequence analysis of Bacillus subtilis strain KC14-1 with broad-spectrum antibacterial activity

Whole genome-sequence analysis of Bacillus subtilis strain KC14-1 with broad-spectrum antibacterial activity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Whole genome-sequence analysis of Bacillus subtilis strain KC14-1 with broad-spectrum antibacterial activity Xiaowei Li, Yanhan Chen, Shunyi Yang, Yi Zhou, Chengde Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5319559/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Mar, 2025 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background Bacillus is utilized as a biological control agent in agricultural production. The main mechanisms accountable for the biocontrol activity encompass the generation of various antifungal active substances during life activities, competition, antagonism with pathogens, promotion of growth and induction of plant resistance, thereby enhancing the inhibition of pathogenic fungi. It is regarded as having high biological control potential and has turned into a research hotspot. Results We found that strain KC14-1 had significant inhibitory effects on Fusarium Fujikuroi , Rhizoclonia Solani , Alternaria Solani , Fusarium oxysporum and Valsa mali . Based on morphological observations, physiological and biochemical determinations, and 16S rRNA, gyrA, and gyrB gene sequencing, strain KC14-1 was identified as Bacillus subtilis . Whole gene sequencing results showed that the genome of strain KC14-1 was composed of a ring chromosome 3908079 bp in size, with a GC content of 43.82%, and 3895 coding genes. Anti-SMASH predicted that the genome of strain KC14-1 contained nine gene clusters that synthesised antibacterial substances. The homology between fengycin, bacillibactin, pulcherriminic acid, subtilosin A, and bacilysin was 100%. Conclusion The biocontrol potential of Bacillus subtilis KC14-1 was determined through whole-genome analysis. Our study provides a solid foundation for the development and utilisation of this strain. whole genome sequence Bacillus subtilis secondary metabolites KC14-1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Background Plant disease incidence significantly limits agricultural production. The occurrence of plant diseases leads to an annual loss of approximately 10%-15% of the global crop output, which translates into an economic loss of hundreds of billions of dollars [ 1 ] Chemical fungicides remain the main tool used to prevent and control plant diseases. [ 2 ] However, owing to their long-term use, many diseases not only have developed resistance [ 3 ] but, additionally, they have severely affected the environment, threatening food safety, and causing numerous other problems. Therefore, many chemical fungicides have been gradually banned, which in turn has resulted in the inability to effectively control plant diseases. In particular, consumer requirements regarding the quality and safety of agricultural products have changed significantly over the past few decades, and people now attach more importance to whether agricultural products are green and healthy, [ 4 , 5 ] which has also led to the use of traditional pesticides to combat diseases. Therefore, the control of plant diseases does not rely so heavily on chemical pesticides; instead, biological pest control, rather than chemical pesticide use, is considered an effective measure for combating plant diseases. [ 2 , 6 , 7 ] Biological control refers to the use of microorganisms and their metabolites to inhibit the spread of pathogens. [ 8 – 12 ] The main bacteria used to control plant diseases are Bacillus and Pseudomonas . Owing to their broad-spectrum antibacterial activity and biosafety, members of genus Bacillus are used as biological control agents in agricultural production. [ 13 , 14 ] The main mechanisms responsible for the biocontrol activity include the production of a variety of antibacterial active substances during life activities, such as lipopeptide antibiotics (e.g. iturin, [ 15 ] surfactin, [ 16 ] and fengycin [ 17 ] ) and antibacterial proteins (e.g. cellulase and chitinase). [ 18 ] Competition and antagonism with pathogens can promote growth and induce resistance in plants, [ 19 , 20 ] thereby enhancing pathogen inhibition. Hence, competition and antagonism are considered to have high potential for biocontrol and have become as a research hotspot. Bacillus produces a variety of secondary metabolites, including polypeptides, polyketones, enzymes, iron carriers, and other active substances. [ 21 – 24 ] However, traditional techniques cannot efficiently and readily determine whether antagonistic strains can produce bacteriostatic substances. In addition, some potentially active antibacterial substances that have not yet been discovered are difficult to identify using traditional methods. However, with the development of biological information, whole-genome sequencing of bacteria has become the method of choice for its greater convenience and speed. Thus, through whole-genome sequencing analysis, bacteriostatic synthetic gene clusters [ 25 ] can be mined, significantly changing the situation. Indeed, to date, many researchers have analysed active secondary metabolites produced by Bacillus through genome sequencing. [ 26 – 28 ] In particular, studying functional antibacterial genes and secondary metabolite gene clusters at the molecular level is important for mining microbial resources with potential for biocontrol. Although many strains of secondary metabolite genes have been predicted to be resolved because of the large number of microorganisms, DNA content may significantly differ even among strains of the same species. Genomic analysis of strains with antagonistic activity is of great significance to supplement the capacity for the production of secondary metabolites. [ 29 , 30 ] In this study, Bacillus strain KC14-1 showing broad-spectrum antimicrobial activity was obtained by screening. The classification status of this bacterium was determined based on morphological observations, physiological and biochemical analyses, and molecular biology techniques. Whole-gene component analysis, functional annotation, and analysis were performed to provide a genetic basis for further development of this bacterial strain. Materials and methods Antagonistic screening of biocontrol strains Early-stage biocontrol strains, KC14-1 and KC14-2 were isolated from a soil sample in the laboratory. To evaluate the antagonistic effect of these biocontrol strains, F. fujikuroi, R. solani, A. solani, F. oxysporum and V. mali were used as target fungi. Face-off culture was performed on potato agar medium, and the edges of the activated pathogenic fungi were formed into a 5-mm thick fungal cake and inserted into the centre of the PDA medium. Biocontrol strains were inoculated on both sides of the pathogen at equal distances, and non inoculate biocontrol strains were used as controls. Each treatment was triplicated and colony diameter was measured at 25°C for 5 d, and the antifungal rate was calculated. High-activity biocontrol strains were screened, and broad-spectrum activity was determined using the method described above. Biological control strains and pathogenic fungi were stored at -20°C in the College of Plant Protection, Gansu Agricultural University. Biocontrol bacteria were activated with LB medium and pathogenic fungi were activated with PDA medium. Classification and status of the antagonistic strains GEN-III microtitre plates were used to determine the phenotypes of the biocontrol bacterial strains. This included 71 carbon-source utilisation tests and 23 chemical sensitivity tests. The strains were inoculated into LB medium and cultured at 37°C for 12 h. The morphology of the strains was observed using transmission electron microscopy. A bacterial genome extraction kit was used to extract bacterial genomic DNA using bacterial universal primers, 27F (5‘-AGTTTGATCMTGGCTCAG-3’) and R1492(5‘-GGTTACCTTGTTACGACTT-3’). Primer sequences p-gyrA-f (5‘-CAGTCAGGA AATGCGTACGTCCTT-3’) and p-gyrA-r (5‘-CAAGGTAATGCTCCAGGCATTGCT-3’) [ 31 ] were used for gyrA gene amplification via PCR, Similarly, PCR amplification of gyrB gene was performed using primers up-1s(5‘-GAAGTCATCATGACCGTTCTGCA-3’) and up-2 sr(5‘-AGCAGGGTACGGATGTGCGAGCC-3’). [ 32 ] The PCR reaction mixture included 9.5 µL ddH 2 O, upstream and downstream primers (10 µmoL/L) 1 µL, DNA template 1 µL, 2 x Rapid Taq Master Mix 12.5 µL. The PCR reaction procedure was as follows: 95°C for 3 min; 95°C 15s, 55°C 15s, and 72°C 30s, 30 cycles. The PCR products were sent to Xi 'an Qingke Biological Company for sequencing, and the sequencing results were BLAST-compared using NCBI to filter out the sequences of highly similar strains, and a phylogenetic tree was constructed using MEGA 5.0 software. Strain whole-genome sequencing The biocontrol bacterial strains were inoculated into LB liquid medium at 28°C, shaken at 180 rpm, and incubated for 24 h. The fermentation broth was centrifuged at 4°C, at 10,000 rpm for 5 min to collect the bacterial pellet, and DNA was extracted and commissioned to perform whole-genome sequencing by Baseo, using PacBio and Illumina. The quality of the extracted DNA was examined using Qubit (Thermo Fisher Scientific, Waltham, MA) and Nanodrop (Thermo Fisher Scientific, Waltham, MA). Genome assembly and correction The sequencing results were assembled using Falcon software (version 0.3.0) [ 33 ] and filtered using the Illumina FASTP platform (version 0.20.0). [ 34 ] Filtering conditions: (1) removal of reads with ≥ 10% unrecognised nucleotides (N); 2) removal of ≥ 50% of reads with bases with Phred quality score ≤ 20; 3 removal of reads targeting the barcode adapters. After filtering, the genome sequence was corrected, and the final genome sequence was determined using Pilon (version 1.23) software. [ 35 ] Prediction of genome components Prediction of sequenced ORF genomes was performed using the NCBI database; non-coding RNA prediction was performed using rRNAmmer (version 1.2); gene island prediction was performed using IslandPath-DIMOB (version 1.0.0) in the online tool IslandViewer4; genomic CRISPR prediction was performed using the CRISPRfinder software (version 4.2.17) to predict genomic CRISPR; transposon prediction was performed using TransposonPSI (version: 20100822). RepeatMasker software (version 4.0.5 and TRF software (version 4.09) were used to predict genomic repeats and tandem repeats, respectively. Finally, software Phage_Finder was used to predict prophages (version 2.0). [ 36 ] Feature notes A genosphere map of strain KC14-1 was created using CGView v2.0. Genes were annotated at the National Centre for Biotechnology Information (NCBI) by comparing non-redundant protein databases (Nr), high-quality protein annotation information databases such as SwissProt, Kyoto Encyclopaedia of Genes and Genomes (KEGG), and the Gene Function Classification Database (GO). Additionally, the Homologous Protein Cluster Database (COG) and Carbohydrate enzymes (CAZy) were used to complement the note database. Lastly, anti-SMASH (version 4.1.0) was used to predict the gene clusters of secondary metabolites. [ 26 , 37 , 38 ] Results Screening of antagonistic bacterial strains Five pathogenic fungi, namely, F. fujikuroi, R. solani, A. solani, F. oxysporum and V. mali , were selected in the laboratory to test the antibacterial activity of the biological control Bacillus strains KC14-1 and KC14-2, and the growth diameter of the pathogens on the third and seventh days, respectively. The results showed that the two bacterial strains had antifungal activity against the five fungal pathogens above; furthermore, the antifungal effect of strain KC14-1 was greater than that of strain KC14-2 on the third and seventh days. On the third day, strain KC14-1 showed high antagonistic activity against Valsa mali , with an inhibition rate of 65.48%. Later, on the seventh day, the inhibition rate of KC14-1 against Valsa mali reached 70% and it had an antagonistic effect against the other four pathogens.(Fig. 1 , Table 1 ) Therefore, we believe that strain KC14-1 has broad-spectrum antifungal activity. Table 1 Broad-spectrum activity determination of the biocontrol Bacillus strains KC14-1 and KC14-2 Pathogenic fungus 3d 7d CK (cm) KC14-1 (cm) KC14-1 bacteriostatic rate (%) KC14-2 (cm) KC14-2 bacteriostatic rate (%) CK (cm) KC14-1 (cm) KC14-1 bacteriostatic rate (%) KC14-2 (cm) KC14-2 bacteriostatic rate (%) V. mali 4.43 ± 0.18a 1.83 ± 0.24c 65.48 ± 7.81a 2.87 ± 0.15b 39.84 ± 2.45a 9.00 ± 0.00a 1.90 ± 0.12c 83.53 ± 1.36a 3.05 ± 0.24b 70.00 ± 2.78a F. fujikuroi 3.45 ± 0.13a 2.90 ± 0.10b 18.16 ± 6.24b 2.80 ± 0.15b 21.63 ± 6.83b 6.82 ± 0.17a 3.03 ± 0.07b 59.79 ± 2.04c 3.27 ± 0.09b 56.21 ± 0.23cd R. solani 6.57 ± 0.26a 3.40 ± 0.06b 52.01 ± 2.36a 3.87 ± 0.09b 44.28 ± 3.04a 9.00 ± 0.00a 3.60 ± 0.12c 63.53 ± 1.36bc 4.03 ± 0.03b 58.43 ± 0.39c F. oxysporum 4.02 ± 0.02a 3.05 ± 0.03c 27.48 ± 1.13b 3.60 ± 0.08b 11.87 ± 1.76b 9.00 ± 0.00a 3.38 ± 0.02c 66.08 ± 0.20b 4.53 ± 0.09b 52.55 ± 1.04d A. solani 3.53 ± 0.08a 2.77 ± 0.17b 25.02 ± 6.77b 2.97 ± 0.08b 18.42 ± 4.86b 7.25 ± 0.13a 2.75 ± 0.10b 66.61 ± 1.97b 2.95 ± 0.05b 63.67 ± 1.17b Data are means ± SD. Lowercase letters in the same column indicate significant differences( p < 0.05) Identification of strain KC14-1 Strain KC14-1 was cultured in darkness, at 28°C for 24 h. The colony edges were milky white, rough, opaque, irregular wavy, and light orange in the centre, with obvious bumps and folds, and gram-negative staining. Scanning electron microscopy revealed that the bacteria were blunt, short, rod-like, and isolated at both ends (Fig. 2 ). The phenotypic fingerprint of the strain was identified through physiological and biochemical tests using GEN-III microplates of a biological, microbial automatic-identification system. The colour changes during the REDOX reaction of tetrazolium dye indicated the utilization of carbon sources and sensitivity to chemical substances. The results showed that strain KC14-1 can use D-trehalose, sucrose, D-fructose, gentiobiose, D-cellobiose and other carbon sources. Chemical susceptibility tests showed that strain KC14-1 grew normally in 8% NaCl (Table 2 ). Based on the Identification Manual of Common Bacteria, the strain was tentatively named Bacillus sp . Table 2 Physiological and biochemical determination of the biocontrol strain KC14-1 Carbon source utilization testing Test result Carbon source utilization testing Test result Carbon source utilization testing Test result Chemical sensitivity test Test result Negative Control - L-Fucose \ D-Gluconic Acid + Positive Control + Dextrin + L-Rhamnose \ D-GlucuronicAcid - pH 6 + D-Maltose - Inosine - Glucuronamid e \ pH 5 - D-Trehalose + D-Sorbitol - Mucic Acid - 1% NaCl + D-Cellobiose + D-Mannitol + Quinic Acid \ 4% NaCl + Gentiobiose + D-Arabitol - D-Saccharic Acid + 8% NaCl + Sucrose + myo-Inositol \ p-Hydroxy- Phenylacetic Acid - 1% Sodium Lactate + D-Turanose - Glycerol + Methyl Pyruvate + Fusidic Acid \ Stachyose - D-Glucose-6-PO4 \ D-Lactic Acid Methyl Ester - D-Serine \ D-Raffinose + D-Fructose-6-PO4 + L-Lactic Acid + Troleandomycin \ α-D-Lactose - D-Aspartic Acid + Citric Acid + Rifamycin SV - D-Melibiose - D-Serine - α-Keto-Glutaric Acid - Minocycline \ β-Methyl-D-Glucoside + Gelatin + D-Malic Acid - Lincomycin \ D-Salicin - Glycyl-L-Proline - L-Malic Acid + Guanidine HCl - N-Acetyl-D-Glucosamine + L-Alanine + Bromo-Succinic Acid + Niaproof 4 \ N-Acetyl-β-D-Mannosamine + L-Arginine + Tween 40 - Vancomycin \ N-Acetyl-D-Galactosamine \ L-Aspartic Acid + γ-Amino-Butryric Acid - Tetrazolium Violet \ N-Acetyl Neuraminic Acid - L-Glutamic Acid + α-Hydroxy-Butyric Acid \ Tetrazolium Blue \ α-D-Glucose + L-Histidine + β-Hydroxy-D,LButyric Acid \ Nalidixic Acid - D-Mannose + L-Pyroglutamic Acid - α-Keto-Butyric Acid \ Lithium Chloride + D-Fructose + L-Serine - Acetoacetic Acid + Potassium Tellurite + D-Galactose - Pectin + Propionic Acid + Aztreonam - 3-Methyl Glucose \ D-Galacturonic Acid + Acetic Acid + Sodium Butyrate + D-Fucose \ L-Galactonic Acid Lactone \ Formic Acid + Sodium Bromate \ Note: “+” means positive; “-” means negative. “\” means that it cannot be judged accurately and is judged as a limit value.The 16S rRNA, gyrA, and gyrB of strain KC14-1 were sequenced. The effective sequence lengths according to PCR amplification were 1493, 939, and 1200 bp, respectively. The electrophoretic results for the amplified products are shown in Fig. 3 . Homologous BLAST sequences were compared with those in the NCBI database. MEGA5.0 software was used to construct the phylogenetic tree of strain KC14-1 using the neighbour-joining tree method. The results showed that the 16S rRNA sequence of KC14-1 correlated with Bacillus subtilis NFAA (MT192659.1) and Bacillus subtilis LSRBMoFPIKRGCFTRI33 (MT133340.1), clustered in the same branch. In turn, the gyrA gene sequence from KC14-1 and Bacillus subtilis SRCM100761 (CP021889.1), and the gyrB gene sequence from Bacillus subtilis BEST3145 (AP024628.1) clustered in the same branch. The phylogenetic tree constructed from the amplified gene sequences was identified as Bacillus subtilis ( Fig. 4 ). Based on morphological observations, and physiological and biochemical characteristics, 16S rRNA, gyrA, and gyrB were identified as genes of Bacillus subtilis. Whole genome-sequence analysis of Bacillus strain KC14-1 Second-generation Illumina sequencing technology, combined with third-generation PacBio sequencing technology, third-generation sequencing data for genome assembly, and second-generation data were used to correct assembly results for the Bacillus KC14-1 strain used in the experiments reported described herein. Using the NCBI database, and after splice assembly and correction of the three-generation sequencing reads with Falcon, the genome of strain KC14-1 was found to consist of a ring chromosome with a genome size of 3908079 bp, GC content of 43.82%, and 3895 coding genes. Total gene length was 33544750 bp, the longest gene was 10764 bp, and the shortest was 78 bp, with a GC content of 44.56% ( Fig. 5 ) . The number of tRNA genes predicted by non-coding genes was 86, with an average length of 77 bp and a total length of 6646 bp. The number of rRNA genes was 30, including the number of 5S_rRNA, 23S_rRNA, and 16S_rRNA genes, which was 10, with lengths of 1160, 29277 and 15500, respectively. There were 23 sRNA genes with a total length of 3050. Using the CRISPR finder software CRISPR projections for the genome predicted the number of genes to be 3. The CRISPR_ Lengths were 105, 107, and 112, and the predicted Repeat_ Lengths were 25, 24, and 32. respectively. The RepeatMasker software was used to predict the scattered repeat sequences in the bacterial strain genome. Prediction results showed that the total number of short interspersed repeat sequences (SINEs) was 12, with a total length of 719 bp. Meanwhile, the total number of long interspersed repeat sequences (LINEs) was 25, with a total length of 1650 bp. In turn, the total number of long terminal repeat (LTR) sequences was 1 with a length was 66 bp. Additionally, the total number of DNA transposons (DNA elements) was three, with a length of 168 bp. A total of 42 scattered repeats were predicted with a total length of 2812 bp, accounting for 0.07% of the entire genome, and one unclassified type: tandem repeat sequence distribution of clusters on the chromosomes, including microsatellite sequences, small satellites, and satellite DNA sequences. The TRF software was used to predict 67 tandem repeats in the bacterial genome, with a total length of 6050 bp, accounting for 0.15% of the total length of the genome. Strain KC14-1 was predicted to have five genes on the genome island with lengths of 17396, 8056, 8067, 58116, and 54076 bp, respectively. The total length of the GIs on the genome island was 145711 bp, with an average length of 29142.20 bp. Lastly, a total of two prophages were predicted, with genome sizes of 34777 and 23834 bp, respectively. The predicted total prophage length was 58611 whose average length was 29305.50. Note The outermost circle represents the position coordinates of the genome sequence. The figure shows the positive chain genes from the outer to the inner circle, followed by negative chain genes, ncRNA (black for tRNA, red for rRNA), GC content (red for greater than the mean, blue for less than the mean), GC SKEW (GC SKEW), which is used to measure the relative content of G and C, and to mark the starting and end points in circular chromosomes; GC skew = (G-C)/(G + C); purple means greater than 0, orange means less than 0). Basic functional notes The Nr, Swiss-Prot, GO, KEGG, and COG databases were used for gene annotation, and BLAST was used to predict the stem gene sequences. Functional databases were used to predict the amino acid sequences of the encoded proteins. The total number of coding genes was 3895. The numbers of functionally annotated genes as per NR, Swiss-Prot, COG, and KEGG were 3873, 3733, 2926, and 3878, respectively, and the number of unannotated genes was 17 (Fig. 6 ). The gene sequences were translated into their corresponding amino acid sequences and compared with the NR database. A total of 3873 genes were successfully annotated using the NR database. B. subtilis , Bacillus sp. Bacillus sp. CMAA 1185, Bacillus sp. LM 4 − 2, Streptococcus pneumoniae, Bacillus sp. JS, Paenibacillus polymyxa, Bacillus sp. YP1, Bacillus sp. SN32, Bacillus sp. MBGLi79, Bacillus azotoformans, Bacillus sp. Rc4, Bacillus cereus and Bacillus sp. FJAT-14266, Bacillus halotolerans, Bacillus sp. Ru63, Terrabacteria, Bacillus amyloliquefaciens, Bacillus sp. SJZ110 and Bacillus sp. 79 − 23 had 3583, 89, 72, 50, 12, 8, 7, 6, 6, 5, 3, 3, 3, 3, 2, 2, 2, 2, 2 and 1, respectively(Fig. 7 ). KEGG is a database that systematically analyses the metabolic pathways of gene products in cells and their functions as gene products. KEGG can be used to further investigate the complex biological behaviours of genes. Gene pathway annotation can be obtained according to the KEGG annotation information, which makes it easier to understand microbial function from the biological process of the system. DIAMOND was compared with the KEGG database to obtain annotation results corresponding to the genes. According to KEGG pathways, a total of 3878 genes were found to be enriched in 133 metabolic pathways, including mainly metabolism, genetic information processing, environmental information processing, cellular processes, and organic systems. Amino acid metabolism, 206 genes; carbohydrate metabolism, 267 genes; energy metabolism, 119 genes; metabolism of cofactors and vitamins, 157 genes; lipid metabolism, 70 genes; xenobiotic biodegradation and metabolism, 37 genes; biosynthesis of other secondary metabolites, 49 genes; nucleotide metabolism, 79 genes; metabolism of terpenoids and polyketones, 36 genes; and other ammonia genes. There were 55 genes involved in basal acid metabolism and 30 more in polysaccharide biosynthesis and metabolism (Fig. 8 ) . Many genes are involved in the regulation of secondary metabolism in strain KC14-1. Therefore, the types of secondary metabolites in this strain may be abundant. Gene ontology, GO, annotation for strain KC14-1 included cytological components, molecular functions, and biological pathways. The annotation results revealed 25 functional branches of biological pathways with 14,113 annotated genes, 15 branches of molecular functions with 5,739 annotated genes, and 19 functional branches of cytological components with 8,706 annotated genes. The numbers of genes related to cellular and metabolic processes were 2845 and 2612, respectively. In terms of molecular function, catalytic activity and binding-related genes were the highest, at 2262 and 1890, respectively. Meanwhile, the number of cell-related genes in the cytology component was the highest (2266) ( Fig. 9 ) . The cellular environment, possible biological processes, and molecular functions of stem gene products are described to understand their biological significance. A total of 5572 protein-coding genes were annotated in the COG database, and functional annotations were divided into the following 25 categories: RNA processing and modification (A), chromatin structure and kinetics (B), energy production and conversion (C), cell cycle division regulation (D), amino acid transport and metabolism (E), nucleotides transport and metabolism (F), carbohydrate transport and metabolism (G), coenzyme transport and metabolism (H), lipid transport and metabolism (I), ribosome structure translation (J ), transcription (K), replication (L), cell wall or membrane or extracellular envelope biosynthesis (M), cell mitosis (N), post-translational modification (O), inorganic ion transport and metabolism (P), secondary metabolite biosynthesis (Q), general function prediction of genes (R), Function unknown (S), information transduction mechanisms (T), secretion and vesicle transport (U), and defence mechanism (V). The number of successfully annotated genes for these 22 categories were 0, 2, 192, 34, 363, 83, 285, 132, 112, 167, 307, 119, 196, 66, 103, 219, 91, 493, 319, 170, 51, 61, respectively. Additionally, there was no gene enrichment in in the following three functional pathways: extracellular structure (W), nuclear structure (Y), or cytoskeleton (Z) ( Fig. 10 ) . Further studies are needed to annotate genes with unknown functions. Our results showed that six functions were identified: glycoside hydrolase (GH), glycosyltransferase (GT), polysaccharide lyase (PLs), carbohydrate esterase (CEs), auxiliary REDOX enzyme (AAs), and carbohydrate binding modules (CBMs). The numbers of genes involved in annotation were 216, 243, 8, 47, 2, and 99, respectively. Glycoside hydrolase (GH) and glycosyltransferase (GT) had the highest proportions among gene families. Analysis of these genes showed that the KC-14 genome contained genes encoding glucanases GH16 and CBM3, xylan-degrading enzymes GH30_8 and GH11, and peptidoglycan-degrading enzymes CBM50, GT28, CE4, and GT2, among others ( Fig. 11 ) . The gene encoding the lysozyme protein, GH23, showed that the strain could degrade dextran, xylan, and other substances. Natural metabolite gene clusters are predicted on the anti-SMASH website. In this case, we found nine gene clusters in the genome of strain KC14-1 ( Table 3 ) . Secondary metabolites are mainly produced via two metabolic pathways: non-ribosomal peptide synthase (NRPS) and polyketide synthase (PKS). In turn, the gene cluster encoding the secondary metabolism of polyketide synthases is divided into three types: type I polyketides synthase (T1pks), type II polyketides synthase (T2pks), and type III polyketides synthase (T3pks). The KC14-1 genome contains four encoded PKS and NRPS gene clusters: one PKS synthase gene cluster has two gene clusters involved in terpene synthesis, a gene cluster associated with iron vector synthesis, and a gene cluster involved in active peptide synthesis. There are five gene clusters with a similarity > 90%, which can be considered to produce this secondary metabolic gene cluster, although there may be some deviations in the predicted results on the anti-SMASH website; however, the above data still show that strain KC14-1 has a huge potential to synthesise and produce a variety of secondary metabolites. Table 3 Gene clusters encoding secondary metabolites in strain KC14-1 Region Type From TO Most similar known cluster Similarity Region 1 NRPS,NRPS-like 354098 419490 surfactin NRP: Lipopeptide Region 2 terpene 1124811 1145608 Region 3 NRPS, betalactone 1845799 1897348 fengycin NRP Region 4 terpene 1978609 2000507 Region 5 T3PKS 2048239 2089336 1-carbapen-2-em-3-carboxylic acid Other Region 6 NRP-metallophore, NRPS 2966640 3018417 bacillibactin NRP Region 7 CDPS 3295582 3316328 pulcherriminic acid Other Region 8 sactipeptide 3533103 3554714 subtilosin A RiPP:Thiopeptide Region 9 other 3558022 3599440 bacilysin Discussion Bacillus is widely present in soils, aquatic environments, and plant bodies, with a wide variety and large number of closely related species, [ 39 , 40 ] making it difficult to determine their taxonomic status by any one single method. Therefore, in this study, we jointly identified strain KC14-1 as Bacillus subtilis by morphological, physiological and biochemical characteristics, and by molecular biology techniques. According to previous studies, Bacillus has the ability to promote plant growth, [ 41 ] induce plant disease resistance and secrete active substances against pathogens, [ 37 ] whereby it is widely used in agriculture. Thus, for example, Bacillus subtilis F62 has inhibitory effects on all pathogens and can reduce the rate of mycelial growth and decrease Botrytis sp. Incidence. [ 42 ] In particular, Bacillus amyloliquefaciens strains Trb7 and Trb1 were identified as effective bactericidal agents effectively inhibiting Ralstonia pseudosolanacearum in tomato; [ 43 ] in another case, antagonistic bacteria, JF-4 and JF-5, were effective against banana wilt by 48.3% and 40.3%, respectively. [ 44 ] Consistently, B. subtilis strain KC14-1 showed bacteriostatic activity against a variety of pathogenic fungi, and the bacterial inhibition rate was more than 50% at day 5 compared to the control. We preliminarily believe that strain KC14-1 has the potential for biocontrol and can be further explored as a biocontrol strain. Analysing species information at the genomic level has become an effective means of efficiently developing and using antagonistic bacterial strains, which not only provides an in-depth understanding of the genetic and physiological characteristics of the strains but, additionally, it has great significance in unravelling the underlying mechanisms of defence and their potential for the production of secondary metabolites. [ 41 , 45 – 47 ] Via whole genome-sequencing of strain KC14-1, we assembled and corrected a gene sequence consisting of a circular chromosome, with a genome size of 3908079 bp, a GC content of 43.82%, and a coding gene number of 3895. The genome of strain KC14-1 was found to contain a variety of gene clusters involved in the synthesis of antimicrobial substances, including surfactin, 1-carbapen-2-em-3-carboxylic acid, fengycin, bacillibactin, pulcherriminic acid, subtilosin A, and bacilysin. The anti-SMASH website predictions showed high homology (100%) of the gene clusters for the synthesis of fengycin, bacillibactin, pulcherriminic acid, subtilosin A, and bacilysin, followed by 78% homology of the gene cluster for the synthesis of surfactin, and only 16% homology of the gene cluster for the synthesis of 1-carbapen-2-em-3-carboxylic acid, which does not exclude the possibility that strain KC14-1 can produce, as yet, unidentified secondary metabolites. Fengycin is produced by a variety of Bacillus species and inhibits pathogenic bacteria by altering the structure and permeability of pathogenic bacterial biofilms, destroying the stability and integrity of lipid membranes; it is a ferric ion chelator that chelates iron in the environment and affects the growth of pathogenic bacteria. [ 48 – 50 ] In turn, bacillibactin is formed by cyclization of glycine, threonine, and DHB, and was first isolated from B. subtilis . [ 51 ] It is synthesized through the NRPS pathway, not only as a high-affinity line of organisms to run iron carriers, but also competition, antibiosis, toxicity, and environmental remediation. It is currently believed that bacteria are able to inhibit pathogens owing to the ability of the ferritin to chelate iron ions in the environment, causing iron deficiency in pathogenic bacteria and nutrient deficiency leading to growth inhibition. [ 52 ] As for bacilysin, this is a dipeptide antibiotic that is active against a wide range of pathogens. Its structure is simple and has an effective mechanism of action as a pleiotropic signalling molecule, affecting cellular activity; however, not all bacilli can produce bacilysin. [ 53 ] In turn, subtilosin A is a cyclic wool sulphur-antibiotic protein; [ 54 ] a genetically encoded and ribosomally synthesised polypeptide antibiotic [ 55 ] that prevents the polymerisation of monomers in the bacterial cell wall to form functional cell wall plasmids. In addition, the KC14-1 genome contained two secondary metabolite-related gene synthesis clusters with unknown functions. The inhibitory effect of this bacterium on several pathogenic fungi demonstrated by the preliminary test may be related to known bacteriostatic active substances; however, the possibility that unknown metabolites may be involved in the inhibitory process cannot be excluded. The genome of strain KC14-1 also revealed 615 genes encoding CAZy family members involved in the production of glucanases, xylanases, peptidoglycanases, and lysozymes, suggesting that strain KC14-1 can cause the hydrolysis of the cell wall of the pathogenic fungus, thus affecting the whole life activity of the fungus, and, consequently, preventing disease damage. [ 56 – 59 ] Through whole genome analysis of strain KC14-1, the potential for biological control of this strain was comprehensively analysed, and secondary metabolite prediction revealed that this strain can produce a variety of antifungal active substances. We believe that strain KC14-1 cannot only be used for disease control by developing new fungicides but by isolating its secondary active substances as well. Conclusions Bacillus subtilis strain KC14-1 showed broad-spectrum antifungal activity against various pathogenic fungi. The strain was identified as B. subtilis using morphological, physiological, biochemical, and molecular analyses. The whole genome of the strain was sequenced, assembled, and calibrated. The data showed that the genome of strain KC14-1 is composed of a ring chromosome with a genome size of 3908079bp and a GC content of 43.82%. Analysis and functional annotation of the genomic components showed that the genome of strain KC14-1 contains various gene clusters encoding carbohydrate enzymes and secondary metabolites. The study of this bacterial genome is of great significance for the further development and utilisation of the strain, and for the study of the mechanisms responsible for the biological control it is capable of exerting for the benefit of agriculture. Abbreviations NCBI National Center for Biotechnology Information Search database ncRNA non-coding RNA KEGG Kyoto Encyclopedia of Genes and Genomes GO Gene ontology COG Cluster of Orthologous Groups of proteins GIs Genomic Islands LTR Long terminal repeat sequence SINEs short interspersed repeated sequences LINEs long interspered repeated sequences CRISPR Clustered Regularly Interspaced Short Palindromic Repeats Nr Non-redundant protein sequence CAZy Carbohydrate-Active enZYmes T1pks type I polyketides synthase T2pks type II polyketides synthase T3pks type III polyketides synthase NRPS non-ribosomal peptides synthase Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Funding This study was supported by Higher Education Innovation Fund Project of Gansu Province (No. 2021B-117), Natural Science Foundation of Gansu Province (No. 21JR7RA820) and the National Natural Science Foundation of China (No. 32160628). Author Contribution Y.C and X.L designed this study and completed the test operation content, S. Y, Y.Z and C. Y analysed the bioinformatics of strain KC14-1,Y.C and X.L wrote the manuscript. All the authors have read and agreed to the published version of the manuscript. Acknowledgement The cDNA / DNA / Small RNA libraries were sequenced on the Illumina/PacBio sequencing platform by Genedenovo Biotechnology Co., Ltd (Guangzhou, China). We are grateful to/thank Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in sequencing and/or bioinformatics analysis. Data Availability The datasets presented in this study can be found in the NCBI Sequence Database (https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_030863625.1/) under accession no. 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Cite Share Download PDF Status: Published Journal Publication published 31 Mar, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 26 Dec, 2024 Reviews received at journal 20 Dec, 2024 Reviews received at journal 16 Dec, 2024 Reviewers agreed at journal 13 Dec, 2024 Reviewers agreed at journal 11 Dec, 2024 Reviewers agreed at journal 11 Dec, 2024 Reviewers invited by journal 29 Nov, 2024 Editor invited by journal 27 Nov, 2024 Editor assigned by journal 27 Oct, 2024 Submission checks completed at journal 24 Oct, 2024 First submitted to journal 23 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5319559","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":373560836,"identity":"ca2d0010-42b5-47c4-b0ff-30e5e36c025d","order_by":0,"name":"Xiaowei Li","email":"","orcid":"","institution":"College of Plant Protection, Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiaowei","middleName":"","lastName":"Li","suffix":""},{"id":373560837,"identity":"a1536e26-a1e8-45ee-b7c0-f4e83d9f1267","order_by":1,"name":"Yanhan Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAs0lEQVRIiWNgGAWjYFACHhBxQI6Nvf0AaVqM+XjOJJCmJXGehIMBcRoMjp89+Lmg5k56mwRDAsOPim1EaDmTlyw949iz3DbpxgOMPWduE6HlQI6BNG/D4dw2mQMJzIxtxGg5/8b4N1BLOptEggGRWm7kmIFsSSBei+SNN2bWPMcOG7YBA/kgUX7hO59jfJun5rC8fHv7wQc/KojQonAAiXMAhyJUIN9AlLJRMApGwSgY0QAAldE/Jsl4Em8AAAAASUVORK5CYII=","orcid":"","institution":"College of Plant Protection, Gansu Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Yanhan","middleName":"","lastName":"Chen","suffix":""},{"id":373560838,"identity":"d23149f4-b348-4eb6-a888-17213e80c396","order_by":2,"name":"Shunyi Yang","email":"","orcid":"","institution":"College of Plant Protection, Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Shunyi","middleName":"","lastName":"Yang","suffix":""},{"id":373560839,"identity":"0648e3da-bc64-4916-a3cf-7ab03fd96377","order_by":3,"name":"Yi Zhou","email":"","orcid":"","institution":"College of Plant Protection, Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Zhou","suffix":""},{"id":373560840,"identity":"9bcbcc38-ffbf-43b6-b327-30f3298dc349","order_by":4,"name":"Chengde Yang","email":"","orcid":"","institution":"College of Plant Protection, Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chengde","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2024-10-23 14:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5319559/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5319559/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-11227-3","type":"published","date":"2025-03-31T15:57:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68247973,"identity":"1c2d4b36-2048-4c74-84ed-f064437c204a","added_by":"auto","created_at":"2024-11-05 09:32:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1547004,"visible":true,"origin":"","legend":"\u003cp\u003eBroad-spectrum activity determination of the biocontrol \u003cem\u003eBacillus\u003c/em\u003e strains KC14-1 and KC14-2\u003c/p\u003e\n\u003cp\u003eNotes:\u003cem\u003e V. mali\u003c/em\u003e, A;\u003cem\u003e F. oxysporum, \u003c/em\u003eB;\u003cem\u003e R. solani,\u003c/em\u003eC;\u003cem\u003e F. fujikuroi\u003c/em\u003e, D;\u003cem\u003e A. solani, \u003c/em\u003eE.\u003c/p\u003e","description":"","filename":"Fig.1BroadspectrumactivitydeterminationofthebiocontrolBacillusstrainsKC141andKC142.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/395ff4bed0a228dccb6e6d22.png"},{"id":68247548,"identity":"e22d6b47-2085-4577-ad54-7ecce0ce8fc9","added_by":"auto","created_at":"2024-11-05 09:24:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":304527,"visible":true,"origin":"","legend":"\u003cp\u003eColony morphology and electron microscope morphology of Bacillus strain KC14-1\u003c/p\u003e\n\u003cp\u003eNote：A: Colony morphology on LB medium; B: C: Morphology of bacteria under electron microscope\u003c/p\u003e","description":"","filename":"Fig.2ColonymorphologyandelectronmicroscopemorphologyofBacillusstrainKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/33d497fd9d92a6b1e0ce1ca7.png"},{"id":68247550,"identity":"04a2cf71-40b0-4c8e-a0e8-846a9782d52d","added_by":"auto","created_at":"2024-11-05 09:24:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":81688,"visible":true,"origin":"","legend":"\u003cp\u003ePCR amplification of gyrA, 16S rRNA, and gyrB of \u003cem\u003eB. subtilis\u003c/em\u003e strain KC14-1\u003c/p\u003e","description":"","filename":"Fig.3PCRamplificationofgyrA16SrRNAandgyrBofB.subtilisstrainKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/8869e23d164d282fdbbeb723.png"},{"id":68246647,"identity":"8095dd71-800e-44b4-acb6-3ac30b3b4c8c","added_by":"auto","created_at":"2024-11-05 09:16:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":214169,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic evolutionary tree based on (A) 16S rRNA gene, (B) gyrA gene, and (C) gyrB gene\u003c/p\u003e","description":"","filename":"Fig.4PhylogeneticevolutionarytreebasedonA16SrRNAgene.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/2281e87fa453e8654b31e1e0.png"},{"id":68247972,"identity":"2166b6ac-8b4e-4140-97dd-1b50fffd36c9","added_by":"auto","created_at":"2024-11-05 09:32:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1737112,"visible":true,"origin":"","legend":"\u003cp\u003eWhole genome circle map of \u003cem\u003eBacillus subtilis \u003c/em\u003eKC14-1\u003c/p\u003e\n\u003cp\u003eNote: The outermost circle represents the position coordinates of the genome sequence. The figure shows the positive chain genes from the outer to the inner circle, followed by negative chain genes, ncRNA (black for tRNA, red for rRNA), GC content (red for greater than the mean, blue for less than the mean), GC SKEW (GC SKEW), which is used to measure the relative content of G and C, and to mark the starting and end points in circular chromosomes; GC skew = (G-C)/(G+C); purple means greater than 0, orange means less than 0).\u003c/p\u003e","description":"","filename":"Fig.5WholegenomecirclemapofBacillussubtilisKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/861fd197a91b42196e350a1f.png"},{"id":68247971,"identity":"bfad6f05-0dc3-4e52-90cc-2e19dcd73653","added_by":"auto","created_at":"2024-11-05 09:32:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":352316,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram for Nr-, Swiss-Prot-, KEGG- and COG-annotated genes\u003c/p\u003e","description":"","filename":"Fig.6VenndiagramforNrSwissProtKEGGandCOGannotatedgenes.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/a359dd60ac5070df69a6d832.png"},{"id":68246656,"identity":"85c6fcb7-8baa-4f05-a75a-7ad30c925686","added_by":"auto","created_at":"2024-11-05 09:16:30","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":7699976,"visible":true,"origin":"","legend":"\u003cp\u003eNr-annotated genes in species of \u003cem\u003eBacillus subtilis \u003c/em\u003eKC14-1 strain\u003c/p\u003e","description":"","filename":"Fig.7NrannotatedgenesinspeciesofBacillussubtilisKC141strain.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/f2b449f8bd76f4689b9e2600.png"},{"id":68246651,"identity":"f99c94c8-84bb-4e00-ae9d-404f99498fe7","added_by":"auto","created_at":"2024-11-05 09:16:29","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":848120,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG-annotated genes of \u003cem\u003eBacillus subtilis \u003c/em\u003estrain KC14-1\u003c/p\u003e","description":"","filename":"Fig.8KEGGannotatedgenesofBacillussubtilisstrainKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/374a8441890c9e1f685b6dde.png"},{"id":68246657,"identity":"b0b06005-d194-47ef-ae83-994455e3426b","added_by":"auto","created_at":"2024-11-05 09:16:30","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1472351,"visible":true,"origin":"","legend":"\u003cp\u003eGene ontology (GO) annotation and functional classification of \u003cem\u003eBacillus subtilis \u003c/em\u003eKC14-1\u003c/p\u003e","description":"","filename":"Fig.9GeneontologyGOannotationandfunctionalclassificationofBacillussubtilisKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/7bfbd20f3a3c2e1114e676f5.png"},{"id":68247568,"identity":"415e5c2d-8a70-42a4-adb9-71a24b5f2006","added_by":"auto","created_at":"2024-11-05 09:24:30","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":984375,"visible":true,"origin":"","legend":"\u003cp\u003eCOG functional classification diagram for \u003cem\u003eBacillus subtilis \u003c/em\u003eKC14-1\u003c/p\u003e","description":"","filename":"Fig.10COGfunctionalclassificationdiagramforBacillussubtilisKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/a7190379dc0fd808179347e8.png"},{"id":68246653,"identity":"71ac8e27-f357-4d9a-a342-5784b92b00ae","added_by":"auto","created_at":"2024-11-05 09:16:30","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":304213,"visible":true,"origin":"","legend":"\u003cp\u003eCAZy classification diagram for \u003cem\u003eBacillus subtilis \u003c/em\u003eKC14-1\u003c/p\u003e","description":"","filename":"Fig.11CAZyclassificationdiagramforBacillussubtilisKC141.png","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/758e1d548fe851cbdd8adf31.png"},{"id":80082123,"identity":"b16878f3-aa4a-465d-baeb-cb51e674b2bf","added_by":"auto","created_at":"2025-04-07 16:07:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":16728360,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5319559/v1/c7bd4b83-a8b9-42eb-b32b-fa8c0d053035.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Whole genome-sequence analysis of Bacillus subtilis strain KC14-1 with broad-spectrum antibacterial activity","fulltext":[{"header":"Background","content":"\u003cp\u003ePlant disease incidence significantly limits agricultural production. The occurrence of plant diseases leads to an annual loss of approximately 10%-15% of the global crop output, which translates into an economic loss of hundreds of billions of dollars\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e Chemical fungicides remain the main tool used to prevent and control plant diseases.\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e However, owing to their long-term use, many diseases not only have developed resistance\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e but, additionally, they have severely affected the environment, threatening food safety, and causing numerous other problems. Therefore, many chemical fungicides have been gradually banned, which in turn has resulted in the inability to effectively control plant diseases. In particular, consumer requirements regarding the quality and safety of agricultural products have changed significantly over the past few decades, and people now attach more importance to whether agricultural products are green and healthy,\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e which has also led to the use of traditional pesticides to combat diseases. Therefore, the control of plant diseases does not rely so heavily on chemical pesticides; instead, biological pest control, rather than chemical pesticide use, is considered an effective measure for combating plant diseases.\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eBiological control refers to the use of microorganisms and their metabolites to inhibit the spread of pathogens.\u003csup\u003e[\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e The main bacteria used to control plant diseases are \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e. Owing to their broad-spectrum antibacterial activity and biosafety, members of genus \u003cem\u003eBacillus\u003c/em\u003e are used as biological control agents in agricultural production.\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e The main mechanisms responsible for the biocontrol activity include the production of a variety of antibacterial active substances during life activities, such as lipopeptide antibiotics (e.g. iturin,\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e surfactin,\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e and fengycin\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e) and antibacterial proteins (e.g. cellulase and chitinase).\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e Competition and antagonism with pathogens can promote growth and induce resistance in plants,\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e thereby enhancing pathogen inhibition. Hence, competition and antagonism are considered to have high potential for biocontrol and have become as a research hotspot.\u003c/p\u003e \u003cp\u003e \u003cem\u003eBacillus\u003c/em\u003e produces a variety of secondary metabolites, including polypeptides, polyketones, enzymes, iron carriers, and other active substances.\u003csup\u003e[\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e However, traditional techniques cannot efficiently and readily determine whether antagonistic strains can produce bacteriostatic substances. In addition, some potentially active antibacterial substances that have not yet been discovered are difficult to identify using traditional methods. However, with the development of biological information, whole-genome sequencing of bacteria has become the method of choice for its greater convenience and speed. Thus, through whole-genome sequencing analysis, bacteriostatic synthetic gene clusters\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e can be mined, significantly changing the situation. Indeed, to date, many researchers have analysed active secondary metabolites produced by \u003cem\u003eBacillus\u003c/em\u003e through genome sequencing.\u003csup\u003e[\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e In particular, studying functional antibacterial genes and secondary metabolite gene clusters at the molecular level is important for mining microbial resources with potential for biocontrol. Although many strains of secondary metabolite genes have been predicted to be resolved because of the large number of microorganisms, DNA content may significantly differ even among strains of the same species. Genomic analysis of strains with antagonistic activity is of great significance to supplement the capacity for the production of secondary metabolites.\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn this study, \u003cem\u003eBacillus\u003c/em\u003e strain KC14-1 showing broad-spectrum antimicrobial activity was obtained by screening. The classification status of this bacterium was determined based on morphological observations, physiological and biochemical analyses, and molecular biology techniques. Whole-gene component analysis, functional annotation, and analysis were performed to provide a genetic basis for further development of this bacterial strain.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAntagonistic screening of biocontrol strains\u003c/h2\u003e \u003cp\u003eEarly-stage biocontrol strains, KC14-1 and KC14-2 were isolated from a soil sample in the laboratory. To evaluate the antagonistic effect of these biocontrol strains, \u003cem\u003eF. fujikuroi, R. solani, A. solani, F. oxysporum\u003c/em\u003e and \u003cem\u003eV. mali\u003c/em\u003e were used as target fungi. Face-off culture was performed on potato agar medium, and the edges of the activated pathogenic fungi were formed into a 5-mm thick fungal cake and inserted into the centre of the PDA medium. Biocontrol strains were inoculated on both sides of the pathogen at equal distances, and non inoculate biocontrol strains were used as controls. Each treatment was triplicated and colony diameter was measured at 25\u0026deg;C for 5 d, and the antifungal rate was calculated. High-activity biocontrol strains were screened, and broad-spectrum activity was determined using the method described above. Biological control strains and pathogenic fungi were stored at -20\u0026deg;C in the College of Plant Protection, Gansu Agricultural University. Biocontrol bacteria were activated with LB medium and pathogenic fungi were activated with PDA medium.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClassification and status of the antagonistic strains\u003c/h3\u003e\n\u003cp\u003eGEN-III microtitre plates were used to determine the phenotypes of the biocontrol bacterial strains. This included 71 carbon-source utilisation tests and 23 chemical sensitivity tests. The strains were inoculated into LB medium and cultured at 37\u0026deg;C for 12 h. The morphology of the strains was observed using transmission electron microscopy.\u003c/p\u003e \u003cp\u003eA bacterial genome extraction kit was used to extract bacterial genomic DNA using bacterial universal primers, 27F (5\u0026lsquo;-AGTTTGATCMTGGCTCAG-3\u0026rsquo;) and R1492(5\u0026lsquo;-GGTTACCTTGTTACGACTT-3\u0026rsquo;). Primer sequences p-gyrA-f (5\u0026lsquo;-CAGTCAGGA AATGCGTACGTCCTT-3\u0026rsquo;) and p-gyrA-r (5\u0026lsquo;-CAAGGTAATGCTCCAGGCATTGCT-3\u0026rsquo;)\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e were used for gyrA gene amplification via PCR, Similarly, PCR amplification of gyrB gene was performed using primers up-1s(5\u0026lsquo;-GAAGTCATCATGACCGTTCTGCA-3\u0026rsquo;) and up-2 sr(5\u0026lsquo;-AGCAGGGTACGGATGTGCGAGCC-3\u0026rsquo;).\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe PCR reaction mixture included 9.5 \u0026micro;L ddH\u003csub\u003e2\u003c/sub\u003eO, upstream and downstream primers (10 \u0026micro;moL/L) 1 \u0026micro;L, DNA template 1 \u0026micro;L, 2 x Rapid Taq Master Mix 12.5 \u0026micro;L. The PCR reaction procedure was as follows: 95\u0026deg;C for 3 min; 95\u0026deg;C 15s, 55\u0026deg;C 15s, and 72\u0026deg;C 30s, 30 cycles.\u003c/p\u003e \u003cp\u003eThe PCR products were sent to Xi 'an Qingke Biological Company for sequencing, and the sequencing results were BLAST-compared using NCBI to filter out the sequences of highly similar strains, and a phylogenetic tree was constructed using MEGA 5.0 software.\u003c/p\u003e\n\u003ch3\u003eStrain whole-genome sequencing\u003c/h3\u003e\n\u003cp\u003eThe biocontrol bacterial strains were inoculated into LB liquid medium at 28\u0026deg;C, shaken at 180 rpm, and incubated for 24 h. The fermentation broth was centrifuged at 4\u0026deg;C, at 10,000 rpm for 5 min to collect the bacterial pellet, and DNA was extracted and commissioned to perform whole-genome sequencing by Baseo, using PacBio and Illumina. The quality of the extracted DNA was examined using Qubit (Thermo Fisher Scientific, Waltham, MA) and Nanodrop (Thermo Fisher Scientific, Waltham, MA).\u003c/p\u003e\n\u003ch3\u003eGenome assembly and correction\u003c/h3\u003e\n\u003cp\u003eThe sequencing results were assembled using Falcon software (version 0.3.0)\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e and filtered using the Illumina FASTP platform (version 0.20.0).\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e Filtering conditions: (1) removal of reads with \u0026ge;\u0026thinsp;10% unrecognised nucleotides (N); 2) removal of \u0026ge;\u0026thinsp;50% of reads with bases with Phred quality score\u0026thinsp;\u0026le;\u0026thinsp;20; 3 removal of reads targeting the barcode adapters. After filtering, the genome sequence was corrected, and the final genome sequence was determined using Pilon (version 1.23) software.\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003ePrediction of genome components\u003c/h3\u003e\n\u003cp\u003ePrediction of sequenced ORF genomes was performed using the NCBI database; non-coding RNA prediction was performed using rRNAmmer (version 1.2); gene island prediction was performed using IslandPath-DIMOB (version 1.0.0) in the online tool IslandViewer4; genomic CRISPR prediction was performed using the CRISPRfinder software (version 4.2.17) to predict genomic CRISPR; transposon prediction was performed using TransposonPSI (version: 20100822). RepeatMasker software (version 4.0.5 and TRF software (version 4.09) were used to predict genomic repeats and tandem repeats, respectively. Finally, software Phage_Finder was used to predict prophages (version 2.0).\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFeature notes\u003c/h2\u003e \u003cp\u003eA genosphere map of strain KC14-1 was created using CGView v2.0. Genes were annotated at the National Centre for Biotechnology Information (NCBI) by comparing non-redundant protein databases (Nr), high-quality protein annotation information databases such as SwissProt, Kyoto Encyclopaedia of Genes and Genomes (KEGG), and the Gene Function Classification Database (GO). Additionally, the Homologous Protein Cluster Database (COG) and Carbohydrate enzymes (CAZy) were used to complement the note database. Lastly, anti-SMASH (version 4.1.0) was used to predict the gene clusters of secondary metabolites.\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eScreening of antagonistic bacterial strains\u003c/h2\u003e \u003cp\u003eFive pathogenic fungi, namely, \u003cem\u003eF. fujikuroi, R. solani, A. solani, F. oxysporum\u003c/em\u003e and \u003cem\u003eV. mali\u003c/em\u003e, were selected in the laboratory to test the antibacterial activity of the biological control \u003cem\u003eBacillus\u003c/em\u003e strains KC14-1 and KC14-2, and the growth diameter of the pathogens on the third and seventh days, respectively. The results showed that the two bacterial strains had antifungal activity against the five fungal pathogens above; furthermore, the antifungal effect of strain KC14-1 was greater than that of strain KC14-2 on the third and seventh days. On the third day, strain KC14-1 showed high antagonistic activity against \u003cem\u003eValsa mali\u003c/em\u003e, with an inhibition rate of 65.48%. Later, on the seventh day, the inhibition rate of KC14-1 against \u003cem\u003eValsa mali\u003c/em\u003e reached 70% and it had an antagonistic effect against the other four pathogens.(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Therefore, we believe that strain KC14-1 has broad-spectrum antifungal activity.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBroad-spectrum activity determination of the biocontrol \u003cem\u003eBacillus\u003c/em\u003e strains KC14-1 and KC14-2\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePathogenic fungus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e3d\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c12\" namest=\"c7\"\u003e \u003cp\u003e7d\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKC14-1 (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKC14-1 bacteriostatic rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKC14-2 (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eKC14-2 bacteriostatic rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCK (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eKC14-1 (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eKC14-1 bacteriostatic rate (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eKC14-2 (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eKC14-2 bacteriostatic rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eV. mali\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.48\u0026thinsp;\u0026plusmn;\u0026thinsp;7.81a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e39.84\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e83.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e70.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF. fujikuroi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.16\u0026thinsp;\u0026plusmn;\u0026thinsp;6.24b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e21.63\u0026thinsp;\u0026plusmn;\u0026thinsp;6.83b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e59.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e56.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23cd\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR. solani\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.01\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e44.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e63.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36bc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e58.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39c\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eF. oxysporum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e11.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e66.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e52.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA. solani\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.02\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e18.42\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e66.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e63.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Lowercase letters in the same column indicate significant differences(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003cp\u003e \u003cb\u003eIdentification of strain\u003c/b\u003e KC14-1\u003c/p\u003e \u003cp\u003eStrain KC14-1 was cultured in darkness, at 28\u0026deg;C for 24 h. The colony edges were milky white, rough, opaque, irregular wavy, and light orange in the centre, with obvious bumps and folds, and gram-negative staining. Scanning electron microscopy revealed that the bacteria were blunt, short, rod-like, and isolated at both ends (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe phenotypic fingerprint of the strain was identified through physiological and biochemical tests using GEN-III microplates of a biological, microbial automatic-identification system. The colour changes during the REDOX reaction of tetrazolium dye indicated the utilization of carbon sources and sensitivity to chemical substances. The results showed that strain KC14-1 can use D-trehalose, sucrose, D-fructose, gentiobiose, D-cellobiose and other carbon sources. Chemical susceptibility tests showed that strain KC14-1 grew normally in 8% NaCl (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Based on the Identification Manual of Common Bacteria, the strain was tentatively named \u003cem\u003eBacillus sp\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysiological and biochemical determination of the biocontrol strain KC14-1\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbon source utilization testing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTest result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarbon source utilization testing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCarbon source utilization testing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTest result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChemical sensitivity test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTest result\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Fucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD-Gluconic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDextrin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Rhamnose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD-GlucuronicAcid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003epH 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Maltose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInosine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGlucuronamid e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003epH 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Trehalose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Sorbitol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMucic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1% NaCl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Cellobiose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Mannitol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuinic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4% NaCl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGentiobiose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Arabitol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD-Saccharic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8% NaCl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emyo-Inositol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-Hydroxy- Phenylacetic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1% Sodium Lactate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Turanose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlycerol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMethyl Pyruvate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFusidic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStachyose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Glucose-6-PO4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD-Lactic Acid Methyl Ester\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eD-Serine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Raffinose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Fructose-6-PO4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL-Lactic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTroleandomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα-D-Lactose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Aspartic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCitric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRifamycin SV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Melibiose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Serine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eα-Keto-Glutaric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMinocycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-Methyl-D-Glucoside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGelatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eD-Malic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLincomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Salicin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlycyl-L-Proline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eL-Malic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGuanidine HCl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN-Acetyl-D-Glucosamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Alanine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBromo-Succinic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNiaproof 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN-Acetyl-β-D-Mannosamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Arginine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTween 40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVancomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN-Acetyl-D-Galactosamine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Aspartic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eγ-Amino-Butryric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTetrazolium Violet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN-Acetyl Neuraminic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Glutamic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eα-Hydroxy-Butyric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTetrazolium Blue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα-D-Glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Histidine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eβ-Hydroxy-D,LButyric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNalidixic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Mannose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Pyroglutamic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eα-Keto-Butyric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLithium Chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Fructose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Serine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetoacetic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePotassium Tellurite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Galactose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePectin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePropionic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAztreonam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3-Methyl Glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD-Galacturonic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSodium Butyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Fucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL-Galactonic Acid Lactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFormic Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSodium Bromate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\\\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: \u0026ldquo;+\u0026rdquo; means positive; \u0026ldquo;-\u0026rdquo; means negative. \u0026ldquo;\\\u0026rdquo; means that it cannot be judged accurately and is judged as a limit value.The 16S rRNA, gyrA, and gyrB of strain KC14-1 were sequenced. The effective sequence lengths according to PCR amplification were 1493, 939, and 1200 bp, respectively. The electrophoretic results for the amplified products are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Homologous BLAST sequences were compared with those in the NCBI database. MEGA5.0 software was used to construct the phylogenetic tree of strain KC14-1 using the neighbour-joining tree method. The results showed that the 16S rRNA sequence of KC14-1 correlated with \u003cem\u003eBacillus subtilis\u003c/em\u003e NFAA (MT192659.1) and \u003cem\u003eBacillus subtilis\u003c/em\u003e LSRBMoFPIKRGCFTRI33 (MT133340.1), clustered in the same branch. In turn, the gyrA gene sequence from KC14-1 and \u003cem\u003eBacillus subtilis\u003c/em\u003e SRCM100761 (CP021889.1), and the gyrB gene sequence from \u003cem\u003eBacillus subtilis\u003c/em\u003e BEST3145 (AP024628.1) clustered in the same branch. The phylogenetic tree constructed from the amplified gene sequences was identified as \u003cem\u003eBacillus subtilis\u003c/em\u003e\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003eBased on morphological observations, and physiological and biochemical characteristics, 16S rRNA, gyrA, and gyrB were identified as genes of \u003cem\u003eBacillus subtilis.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eWhole genome-sequence analysis of\u003c/b\u003e \u003cb\u003eBacillus\u003c/b\u003e \u003cb\u003estrain\u003c/b\u003e KC14-1\u003c/p\u003e \u003cp\u003eSecond-generation Illumina sequencing technology, combined with third-generation PacBio sequencing technology, third-generation sequencing data for genome assembly, and second-generation data were used to correct assembly results for the \u003cem\u003eBacillus\u003c/em\u003e KC14-1 strain used in the experiments reported described herein.\u003c/p\u003e \u003cp\u003eUsing the NCBI database, and after splice assembly and correction of the three-generation sequencing reads with Falcon, the genome of strain KC14-1 was found to consist of a ring chromosome with a genome size of 3908079 bp, GC content of 43.82%, and 3895 coding genes. Total gene length was 33544750 bp, the longest gene was 10764 bp, and the shortest was 78 bp, with a GC content of 44.56% \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The number of tRNA genes predicted by non-coding genes was 86, with an average length of 77 bp and a total length of 6646 bp. The number of rRNA genes was 30, including the number of 5S_rRNA, 23S_rRNA, and 16S_rRNA genes, which was 10, with lengths of 1160, 29277 and 15500, respectively. There were 23 sRNA genes with a total length of 3050. Using the CRISPR finder software CRISPR projections for the genome predicted the number of genes to be 3. The CRISPR_ Lengths were 105, 107, and 112, and the predicted Repeat_ Lengths were 25, 24, and 32. respectively.\u003c/p\u003e \u003cp\u003eThe RepeatMasker software was used to predict the scattered repeat sequences in the bacterial strain genome. Prediction results showed that the total number of short interspersed repeat sequences (SINEs) was 12, with a total length of 719 bp. Meanwhile, the total number of long interspersed repeat sequences (LINEs) was 25, with a total length of 1650 bp. In turn, the total number of long terminal repeat (LTR) sequences was 1 with a length was 66 bp. Additionally, the total number of DNA transposons (DNA elements) was three, with a length of 168 bp. A total of 42 scattered repeats were predicted with a total length of 2812 bp, accounting for 0.07% of the entire genome, and one unclassified type: tandem repeat sequence distribution of clusters on the chromosomes, including microsatellite sequences, small satellites, and satellite DNA sequences. The TRF software was used to predict 67 tandem repeats in the bacterial genome, with a total length of 6050 bp, accounting for 0.15% of the total length of the genome. Strain KC14-1 was predicted to have five genes on the genome island with lengths of 17396, 8056, 8067, 58116, and 54076 bp, respectively. The total length of the GIs on the genome island was 145711 bp, with an average length of 29142.20 bp. Lastly, a total of two prophages were predicted, with genome sizes of 34777 and 23834 bp, respectively. The predicted total prophage length was 58611 whose average length was 29305.50.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNote\u003c/strong\u003e \u003cp\u003eThe outermost circle represents the position coordinates of the genome sequence. The figure shows the positive chain genes from the outer to the inner circle, followed by negative chain genes, ncRNA (black for tRNA, red for rRNA), GC content (red for greater than the mean, blue for less than the mean), GC SKEW (GC SKEW), which is used to measure the relative content of G and C, and to mark the starting and end points in circular chromosomes; GC skew = (G-C)/(G\u0026thinsp;+\u0026thinsp;C); purple means greater than 0, orange means less than 0).\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBasic functional notes\u003c/h2\u003e \u003cp\u003eThe Nr, Swiss-Prot, GO, KEGG, and COG databases were used for gene annotation, and BLAST was used to predict the stem gene sequences. Functional databases were used to predict the amino acid sequences of the encoded proteins. The total number of coding genes was 3895. The numbers of functionally annotated genes as per NR, Swiss-Prot, COG, and KEGG were 3873, 3733, 2926, and 3878, respectively, and the number of unannotated genes was 17 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe gene sequences were translated into their corresponding amino acid sequences and compared with the NR database. A total of 3873 genes were successfully annotated using the NR database. \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eBacillus sp. Bacillus sp. CMAA 1185, Bacillus sp. LM 4\u0026thinsp;\u0026minus;\u0026thinsp;2, Streptococcus pneumoniae, Bacillus sp. JS, Paenibacillus polymyxa, Bacillus sp. YP1, Bacillus sp. SN32, Bacillus sp. MBGLi79, Bacillus azotoformans, Bacillus sp. Rc4, Bacillus cereus and Bacillus sp. FJAT-14266, Bacillus halotolerans, Bacillus sp. Ru63, Terrabacteria, Bacillus amyloliquefaciens, Bacillus sp. SJZ110 and Bacillus sp. 79\u0026thinsp;\u0026minus;\u0026thinsp;23\u003c/em\u003e had 3583, 89, 72, 50, 12, 8, 7, 6, 6, 5, 3, 3, 3, 3, 2, 2, 2, 2, 2 and 1, respectively(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKEGG is a database that systematically analyses the metabolic pathways of gene products in cells and their functions as gene products. KEGG can be used to further investigate the complex biological behaviours of genes. Gene pathway annotation can be obtained according to the KEGG annotation information, which makes it easier to understand microbial function from the biological process of the system. DIAMOND was compared with the KEGG database to obtain annotation results corresponding to the genes. According to KEGG pathways, a total of 3878 genes were found to be enriched in 133 metabolic pathways, including mainly metabolism, genetic information processing, environmental information processing, cellular processes, and organic systems. Amino acid metabolism, 206 genes; carbohydrate metabolism, 267 genes; energy metabolism, 119 genes; metabolism of cofactors and vitamins, 157 genes; lipid metabolism, 70 genes; xenobiotic biodegradation and metabolism, 37 genes; biosynthesis of other secondary metabolites, 49 genes; nucleotide metabolism, 79 genes; metabolism of terpenoids and polyketones, 36 genes; and other ammonia genes. There were 55 genes involved in basal acid metabolism and 30 more in polysaccharide biosynthesis and metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Many genes are involved in the regulation of secondary metabolism in strain KC14-1. Therefore, the types of secondary metabolites in this strain may be abundant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGene ontology, GO, annotation for strain KC14-1 included cytological components, molecular functions, and biological pathways. The annotation results revealed 25 functional branches of biological pathways with 14,113 annotated genes, 15 branches of molecular functions with 5,739 annotated genes, and 19 functional branches of cytological components with 8,706 annotated genes. The numbers of genes related to cellular and metabolic processes were 2845 and 2612, respectively. In terms of molecular function, catalytic activity and binding-related genes were the highest, at 2262 and 1890, respectively. Meanwhile, the number of cell-related genes in the cytology component was the highest (2266) ( Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The cellular environment, possible biological processes, and molecular functions of stem gene products are described to understand their biological significance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 5572 protein-coding genes were annotated in the COG database, and functional annotations were divided into the following 25 categories: RNA processing and modification (A), chromatin structure and kinetics (B), energy production and conversion (C), cell cycle division regulation (D), amino acid transport and metabolism (E), nucleotides transport and metabolism (F), carbohydrate transport and metabolism (G), coenzyme transport and metabolism (H), lipid transport and metabolism (I), ribosome structure translation (J ), transcription (K), replication (L), cell wall or membrane or extracellular envelope biosynthesis (M), cell mitosis (N), post-translational modification (O), inorganic ion transport and metabolism (P), secondary metabolite biosynthesis (Q), general function prediction of genes (R), Function unknown (S), information transduction mechanisms (T), secretion and vesicle transport (U), and defence mechanism (V). The number of successfully annotated genes for these 22 categories were 0, 2, 192, 34, 363, 83, 285, 132, 112, 167, 307, 119, 196, 66, 103, 219, 91, 493, 319, 170, 51, 61, respectively. Additionally, there was no gene enrichment in in the following three functional pathways: extracellular structure (W), nuclear structure (Y), or cytoskeleton (Z) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Further studies are needed to annotate genes with unknown functions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOur results showed that six functions were identified: glycoside hydrolase (GH), glycosyltransferase (GT), polysaccharide lyase (PLs), carbohydrate esterase (CEs), auxiliary REDOX enzyme (AAs), and carbohydrate binding modules (CBMs). The numbers of genes involved in annotation were 216, 243, 8, 47, 2, and 99, respectively. Glycoside hydrolase (GH) and glycosyltransferase (GT) had the highest proportions among gene families. Analysis of these genes showed that the KC-14 genome contained genes encoding glucanases GH16 and CBM3, xylan-degrading enzymes GH30_8 and GH11, and peptidoglycan-degrading enzymes CBM50, GT28, CE4, and GT2, among others \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The gene encoding the lysozyme protein, GH23, showed that the strain could degrade dextran, xylan, and other substances.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNatural metabolite gene clusters are predicted on the anti-SMASH website. In this case, we found nine gene clusters in the genome of strain KC14-1 \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Secondary metabolites are mainly produced via two metabolic pathways: non-ribosomal peptide synthase (NRPS) and polyketide synthase (PKS). In turn, the gene cluster encoding the secondary metabolism of polyketide synthases is divided into three types: type I polyketides synthase (T1pks), type II polyketides synthase (T2pks), and type III polyketides synthase (T3pks). The KC14-1 genome contains four encoded PKS and NRPS gene clusters: one PKS synthase gene cluster has two gene clusters involved in terpene synthesis, a gene cluster associated with iron vector synthesis, and a gene cluster involved in active peptide synthesis. There are five gene clusters with a similarity\u0026thinsp;\u0026gt;\u0026thinsp;90%, which can be considered to produce this secondary metabolic gene cluster, although there may be some deviations in the predicted results on the anti-SMASH website; however, the above data still show that strain KC14-1 has a huge potential to synthesise and produce a variety of secondary metabolites.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGene clusters encoding secondary metabolites in strain KC14-1\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrom\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMost similar known cluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSimilarity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNRPS,NRPS-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e419490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003esurfactin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNRP: Lipopeptide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eterpene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1124811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1145608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNRPS, betalactone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1845799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1897348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003efengycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNRP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eterpene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1978609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2000507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT3PKS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2048239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2089336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1-carbapen-2-em-3-carboxylic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNRP-metallophore, NRPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2966640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3018417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ebacillibactin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNRP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCDPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3295582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3316328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003epulcherriminic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esactipeptide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3533103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3554714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003esubtilosin A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRiPP:Thiopeptide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3558022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3599440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ebacilysin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e is widely present in soils, aquatic environments, and plant bodies, with a wide variety and large number of closely related species,\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e making it difficult to determine their taxonomic status by any one single method. Therefore, in this study, we jointly identified strain KC14-1 as \u003cem\u003eBacillus subtilis\u003c/em\u003e by morphological, physiological and biochemical characteristics, and by molecular biology techniques. According to previous studies, \u003cem\u003eBacillus\u003c/em\u003e has the ability to promote plant growth,\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e induce plant disease resistance and secrete active substances against pathogens,\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e whereby it is widely used in agriculture. Thus, for example, \u003cem\u003eBacillus subtilis\u003c/em\u003e F62 has inhibitory effects on all pathogens and can reduce the rate of mycelial growth and decrease \u003cem\u003eBotrytis sp.\u003c/em\u003e Incidence.\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e In particular, \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e strains Trb7 and Trb1 were identified as effective bactericidal agents effectively inhibiting \u003cem\u003eRalstonia pseudosolanacearum\u003c/em\u003e in tomato;\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e in another case, antagonistic bacteria, JF-4 and JF-5, were effective against banana wilt by 48.3% and 40.3%, respectively.\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e Consistently, \u003cem\u003eB. subtilis\u003c/em\u003e strain KC14-1 showed bacteriostatic activity against a variety of pathogenic fungi, and the bacterial inhibition rate was more than 50% at day 5 compared to the control. We preliminarily believe that strain KC14-1 has the potential for biocontrol and can be further explored as a biocontrol strain.\u003c/p\u003e \u003cp\u003eAnalysing species information at the genomic level has become an effective means of efficiently developing and using antagonistic bacterial strains, which not only provides an in-depth understanding of the genetic and physiological characteristics of the strains but, additionally, it has great significance in unravelling the underlying mechanisms of defence and their potential for the production of secondary metabolites.\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e Via whole genome-sequencing of strain KC14-1, we assembled and corrected a gene sequence consisting of a circular chromosome, with a genome size of 3908079 bp, a GC content of 43.82%, and a coding gene number of 3895. The genome of strain KC14-1 was found to contain a variety of gene clusters involved in the synthesis of antimicrobial substances, including surfactin, 1-carbapen-2-em-3-carboxylic acid, fengycin, bacillibactin, pulcherriminic acid, subtilosin A, and bacilysin. The anti-SMASH website predictions showed high homology (100%) of the gene clusters for the synthesis of fengycin, bacillibactin, pulcherriminic acid, subtilosin A, and bacilysin, followed by 78% homology of the gene cluster for the synthesis of surfactin, and only 16% homology of the gene cluster for the synthesis of 1-carbapen-2-em-3-carboxylic acid, which does not exclude the possibility that strain KC14-1 can produce, as yet, unidentified secondary metabolites. Fengycin is produced by a variety of \u003cem\u003eBacillus\u003c/em\u003e species and inhibits pathogenic bacteria by altering the structure and permeability of pathogenic bacterial biofilms, destroying the stability and integrity of lipid membranes; it is a ferric ion chelator that chelates iron in the environment and affects the growth of pathogenic bacteria.\u003csup\u003e[\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e In turn, bacillibactin is formed by cyclization of glycine, threonine, and DHB, and was first isolated from \u003cem\u003eB. subtilis\u003c/em\u003e.\u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e It is synthesized through the NRPS pathway, not only as a high-affinity line of organisms to run iron carriers, but also competition, antibiosis, toxicity, and environmental remediation. It is currently believed that bacteria are able to inhibit pathogens owing to the ability of the ferritin to chelate iron ions in the environment, causing iron deficiency in pathogenic bacteria and nutrient deficiency leading to growth inhibition.\u003csup\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e As for bacilysin, this is a dipeptide antibiotic that is active against a wide range of pathogens. Its structure is simple and has an effective mechanism of action as a pleiotropic signalling molecule, affecting cellular activity; however, not all bacilli can produce bacilysin. \u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e In turn, subtilosin A is a cyclic wool sulphur-antibiotic protein;\u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e a genetically encoded and ribosomally synthesised polypeptide antibiotic\u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e that prevents the polymerisation of monomers in the bacterial cell wall to form functional cell wall plasmids. In addition, the KC14-1 genome contained two secondary metabolite-related gene synthesis clusters with unknown functions. The inhibitory effect of this bacterium on several pathogenic fungi demonstrated by the preliminary test may be related to known bacteriostatic active substances; however, the possibility that unknown metabolites may be involved in the inhibitory process cannot be excluded.\u003c/p\u003e \u003cp\u003eThe genome of strain KC14-1 also revealed 615 genes encoding CAZy family members involved in the production of glucanases, xylanases, peptidoglycanases, and lysozymes, suggesting that strain KC14-1 can cause the hydrolysis of the cell wall of the pathogenic fungus, thus affecting the whole life activity of the fungus, and, consequently, preventing disease damage.\u003csup\u003e[\u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThrough whole genome analysis of strain KC14-1, the potential for biological control of this strain was comprehensively analysed, and secondary metabolite prediction revealed that this strain can produce a variety of antifungal active substances. We believe that strain KC14-1 cannot only be used for disease control by developing new fungicides but by isolating its secondary active substances as well.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cem\u003eBacillus subtilis\u003c/em\u003e strain KC14-1 showed broad-spectrum antifungal activity against various pathogenic fungi. The strain was identified as \u003cem\u003eB. subtilis\u003c/em\u003e using morphological, physiological, biochemical, and molecular analyses. The whole genome of the strain was sequenced, assembled, and calibrated. The data showed that the genome of strain KC14-1 is composed of a ring chromosome with a genome size of 3908079bp and a GC content of 43.82%. Analysis and functional annotation of the genomic components showed that the genome of strain KC14-1 contains various gene clusters encoding carbohydrate enzymes and secondary metabolites. The study of this bacterial genome is of great significance for the further development and utilisation of the strain, and for the study of the mechanisms responsible for the biological control it is capable of exerting for the benefit of agriculture.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCBI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Center for Biotechnology Information Search database\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003encRNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-coding RNA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCluster of Orthologous Groups of proteins\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGenomic Islands\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLTR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLong terminal repeat sequence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSINEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eshort interspersed repeated sequences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLINEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elong interspered repeated sequences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRISPR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClustered Regularly Interspaced Short Palindromic Repeats\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNr\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-redundant protein sequence\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCAZy\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCarbohydrate-Active enZYmes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT1pks\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etype I polyketides synthase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2pks\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etype II polyketides synthase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT3pks\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etype III polyketides synthase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNRPS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-ribosomal peptides synthase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by Higher Education Innovation Fund Project of Gansu Province (No. 2021B-117), Natural Science Foundation of Gansu Province (No. 21JR7RA820) and the National Natural Science Foundation of China (No. 32160628).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.C and X.L designed this study and completed the test operation content, S. Y, Y.Z and C. Y analysed the bioinformatics of strain KC14-1,Y.C and X.L wrote the manuscript. All the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe cDNA / DNA / Small RNA libraries were sequenced on the Illumina/PacBio sequencing platform by Genedenovo Biotechnology Co., Ltd (Guangzhou, China). We are grateful to/thank Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in sequencing and/or bioinformatics analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets presented in this study can be found in the NCBI Sequence Database (https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_030863625.1/) under accession no. PRJNA872326.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePENG Y, LI S J YANJ et al. Research Progress on Phytopathogenic Fungi and Their Role as Biocontrol Agents [J]. 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Agronomy, 2023, 13(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLIU H, ZENG Q, YALIMAIMAITI N, et al. Comprehensive genomic analysis of \u003cem\u003eBacillus velezensis\u003c/em\u003e AL7 reveals its biocontrol potential against Verticillium wilt of cotton [J]. Mol Genet Genomics. 2021;296(6):1287\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLUO Y, CHEN L, LU Z et al. Genome sequencing of biocontrol strain \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e Bam1 and further analysis of its heavy metal resistance mechanism [J]. Bioresources Bioprocess, 2022, 9(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWANG D, ZHAN Y, CAI D, et al. Regulation of the Synthesis and Secretion of the Iron Chelator Cyclodipeptide Pulcherriminic Acid in \u003cem\u003eBacillus licheniformis\u003c/em\u003e [J]. Appl Environ Microbiol. 2018;84(13):e00262\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWANG S, WANG H, ZHANG D, et al. Multistep Metabolic Engineering of \u003cem\u003eBacillus licheniformis\u003c/em\u003e To Improve Pulcherriminic Acid Production [J]. Appl Environ Microbiol. 2020;86(9):e03041\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZHANG H, WANG S, DENG Q, et al. The effect of pulcherriminic acid produced by Metschnikowia citriensis in controlling postharvest diseases of citrus fruits [J]. Pestic Biochem Physiol. 2023;197:105657.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMAY JJ, WENDRICH T M, MARAHIEL MA. The dhb Operon of \u003cem\u003eBacillus subtilisEncodes\u003c/em\u003e the Biosynthetic Template for the Catecholic Siderophore 2,3-Dihydroxybenzoate-Glycine-Threonine Trimeric Ester Bacillibactin* [J]. J Biol Chem. 2001;276(10):7209\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYU X, AI C, XIN L, et al. The siderophore-producing bacterium, \u003cem\u003eBacillus subtilis\u003c/em\u003e CAS15, has a biocontrol effect on Fusarium wilt and promotes the growth of pepper [J]. Eur J Soil Biol. 2011;47(2):138\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eISLAM T, RABBEE M F, CHOI J et al. Biosynthesis, Molecular Regulation, and Application of Bacilysin Produced by \u003cem\u003eBacillus\u003c/em\u003e Species [J]. Metabolites, 2022, 12(5): 397.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eALGBURI A, ZEHM S. Subtilosin Prevents Biofilm Formation by Inhibiting Bacterial Quorum Sensing [J]. Probiotics Antimicrob Proteins. 2017;9(1):81\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTHENNARASU S, LEE D-K POONA, et al. Membrane permeabilization, orientation, and antimicrobial mechanism of subtilosin A [J]. Chem Phys Lipids. 2005;137(1):38\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXU T, ZHU T, LI S. β-1,3\u0026thinsp;\u0026ndash;\u0026thinsp;1,4-glucanase gene from \u003cem\u003eBacillus velezensis\u003c/em\u003e ZJ20 exerts antifungal effect on plant pathogenic fungi [J]. World J Microbiol Biotechnol. 2016;32(2):26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQIN Z, YU S, ZHANG K, et al. Characterization of a Glycoside Hydrolase Family 157 Endo-β-1,3-Glucanase That Displays Antifungal Activity against Phytopathogens [J]. J Agric Food Chem. 2023;71(27):10383\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBROWN AE. Activity of Glucanases of Zygorrhynchus moelleri in Relation to Antagonism Against some Soil-Borne Plant Pathogenic Fungi [J]. J Phytopathol. 1987;120(4):298\u0026ndash;309.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYU M, ZHANG G, JIANG J, et al. Lysobacter enzymogenes Employs Diverse Genes for Inhibiting Hypha Growth and Spore Germination of Soybean Fungal Pathogens [J]. Phytopathology\u0026reg;. 2020;110(3):593\u0026ndash;602.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"whole genome sequence, Bacillus subtilis, secondary metabolites, KC14-1","lastPublishedDoi":"10.21203/rs.3.rs-5319559/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5319559/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e \u003cem\u003eBacillus\u003c/em\u003e is utilized as a biological control agent in agricultural production. The main mechanisms accountable for the biocontrol activity encompass the generation of various antifungal active substances during life activities, competition, antagonism with pathogens, promotion of growth and induction of plant resistance, thereby enhancing the inhibition of pathogenic fungi. It is regarded as having high biological control potential and has turned into a research hotspot.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe found that strain KC14-1 had significant inhibitory effects on \u003cem\u003eFusarium Fujikuroi\u003c/em\u003e, \u003cem\u003eRhizoclonia Solani\u003c/em\u003e, \u003cem\u003eAlternaria Solani\u003c/em\u003e, \u003cem\u003eFusarium oxysporum\u003c/em\u003e and \u003cem\u003eValsa mali\u003c/em\u003e. Based on morphological observations, physiological and biochemical determinations, and 16S rRNA, gyrA, and gyrB gene sequencing, strain KC14-1 was identified as \u003cem\u003eBacillus subtilis\u003c/em\u003e. Whole gene sequencing results showed that the genome of strain KC14-1 was composed of a ring chromosome 3908079 bp in size, with a GC content of 43.82%, and 3895 coding genes. Anti-SMASH predicted that the genome of strain KC14-1 contained nine gene clusters that synthesised antibacterial substances. The homology between fengycin, bacillibactin, pulcherriminic acid, subtilosin A, and bacilysin was 100%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe biocontrol potential of \u003cem\u003eBacillus subtilis\u003c/em\u003e KC14-1 was determined through whole-genome analysis. Our study provides a solid foundation for the development and utilisation of this strain.\u003c/p\u003e","manuscriptTitle":"Whole genome-sequence analysis of Bacillus subtilis strain KC14-1 with broad-spectrum antibacterial activity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-05 09:16:24","doi":"10.21203/rs.3.rs-5319559/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-26T14:47:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-20T06:45:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-16T15:38:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"119454031200230275003385732105313343063","date":"2024-12-14T03:56:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73232550250554251183815095314367238822","date":"2024-12-11T16:59:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319633939468167741224686258103214530759","date":"2024-12-11T15:43:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-30T02:02:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-11-27T11:40:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-28T02:55:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-25T00:42:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2024-10-23T13:54:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"434d832c-b7d2-4a97-816b-eed1d834843d","owner":[],"postedDate":"November 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-07T16:03:02+00:00","versionOfRecord":{"articleIdentity":"rs-5319559","link":"https://doi.org/10.1186/s12864-025-11227-3","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-03-31 15:57:09","publishedOnDateReadable":"March 31st, 2025"},"versionCreatedAt":"2024-11-05 09:16:24","video":"","vorDoi":"10.1186/s12864-025-11227-3","vorDoiUrl":"https://doi.org/10.1186/s12864-025-11227-3","workflowStages":[]},"version":"v1","identity":"rs-5319559","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5319559","identity":"rs-5319559","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}