Complete Genome Sequencing and Functional Prediction of Bacillus velezensis ANY11

Complete Genome Sequencing and Functional Prediction of Bacillus velezensis ANY11 | 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 Complete Genome Sequencing and Functional Prediction of Bacillus velezensis ANY11 Yulei Chen, Jiaye Tang, Wenli Xin, Ximeng Xiao, Borui Mou, Jialian Li, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4254829/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Bacillus velezensis , a member of phylum firmicutes, is a gram-positive rod-shaped and endospore-forming bacterium inhabiting diverse environments. The preliminary analysis of the whole genome of Bacillus velezensis ANY11 , isolated from bamboo fiber humus in the intestines of Cyrtotrachelus buqueti , revealed that the genome is approximately 3,949,880 bp in length and contains 4265 coding genes. Among these, 12815, 2473, 3193, and 171 genes were annotated in the GO, KEGG, COG, and CAZy databases, respectively. Additionally, the virulence, pathogenicity, and antibiotic resistance of Bacillus velezensis ANY11 were analyzed using PHI, VFDB, and CARD databases. Based on the genomic sequencing and gene function analysis, Bacillus velezensis is believed to possesses certain disease resistance and the capability to hydrolyze lignocellulose, predicting its potential role in plant disease prevention and control as well as in the hydrolysis and reuse of lignocellulose lays The bioinformatics from this study may lay a foundation for the production of biofertilizers and biopesticides, as well as for the utilization of biomass in the production of clean energy ethanol. Bacillus velezensis Gene annotation Gene function prediction Whole genome Whole genome sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Bacillus velezensis was first isolated from the mouth of the river Vélez in Málaga (Southern Spain) in 2005 [ 1 ]. Widely distributed in various environments such as plant rhizosphere, soil, rivers, human food, animal intestines, and seawater, these microorganisms are easy to isolate and cultivate [ 2 ]. Bacillus velezensis belongs to the genus Bacillus and is a type of Gram-positive rod-shaped multifunctional bacterium. Under unfavorable conditions, it can produce spores, which can be converted into powder without causing bacterial death. Such feature gives Bacillus velezensis a significant advantage compared to other biocontrol bacteria [ 3 ]. Due to its harmlessness to humans and animals and its environmental friendliness, Bacillus velezensis has been commercially utilized as a biofertilizer and biopesticide. Extensive research has demonstrated that Bacillus velezensis produce a broad-spectrum antibacterial activity effectively against a variety of plant pathogenic fungi. Consequently, it can be utilized in the prevention and control of plant diseases [ 4 ]. Currently, there has been extensive research on the antibacterial activity of Bacillus velezensis . A genomic sequencing was conducted to predict the gene clusters responsible for the synthesis of secondary metabolites and explore the antibacterial active substances and their mechanisms. By delving into the antibacterial genes of these strains, our study provides a bioinformatics foundation for the efficient development and application of Bacillus velezensis in agricultural production. Lignocellulose, a widely distributed, renewable, and abundantly available biomass resource, is an essential raw material for the production of bioethanol. However, the hydrolysis of lignocellulose, particularly the degradation of cellulose, remains a significant challenge in the production of lignocellulosic bioethanol [ 5 ]. In nature, there are many examples of lignocellulose degradation, out of which herbivorous insects are considered the most dominant. Among these insects, gut symbiotic microorganisms play a crucial role in degrading lignocellulose [ 6 ]. Therefore, the intestines of scavenger insects represent ideal sites for isolating lignocellulose-degrading microorganisms. Studies have shown that Bacillus velezensis can produce highly active neutral enzymes -proteases and cellulases, which break down cellulose into oligosaccharides or monosaccharides [ 7 ]. Furthermore, Bacillus velezensis possesses genes encoding enzymes related to the degradation of cellulose, xylan, lignin, starch, mannan, galactosides, and arabinose [ 8 ]. Previous studies have isolated Bacillus velezensis LC1 from bamboo fiber humus and whole-genome sequencing as well as cellulase activity measurement was conducted. This symbiotic bacterium possesses the ability to degrade lignocellulose and exhibits cellulase activity, indicating its potential to further convert bamboo lignocellulosic components into ethanol [ 9 ]. The Bacillus velezensis ANY11 used in this experiment was isolated from bamboo fiber humus in the intestines of Cyrtotrachelus buqueti . Whole-genome sequencing, genomic analysis, and functional annotation conducted in this study lay the foundation for future research on its potential applications in biofertilizers, plant disease and pest control, as well as in the biocatalytic production of renewable ethanol. 2. Experimental materials and procedures Bacillus velezensis ANY11 was isolated from bamboo fiber humus in the intestines of Cyrtotrachelus buqueti . LB Medium: 0.5% yeast extract, 1% peptone, 1% sodium chloride, pH adjusted to 7.0. The Bacillus velezensis strain was inoculated into LB liquid medium and cultured with constant shaking at 220 r/min at 30°C for 12–24 hours to activate the bacteria. After activation, the bacterial cells were collected by centrifugation. Genomic DNA from the sample was extracted using the STE method. The purity and integrity of the DNA were subsequently assessed by agarose gel electrophoresis, and quantitation was performed using Qubit. Large fragments were then recovered using the BluePippin automated nucleic acid fragment recovery system, followed by end repair and A-tailing. The samples were then mixed in equimolar amounts, and adapter ligation was performed using the SQK-LSK109 ligation kit (Oxford Nanopore Technologies) to construct a 1D library. Finally, sequencing was carried out using the Nanopore platform. The DNA samples that passed the quality check of electrophoresis were randomly fragmented into approximately 350 bp-long segments using an ultrasonic disruptor. The processed DNA fragments were then used for library preparation. After passing library quality control, the different libraries were sequenced on both the Nanopore PromethION and Illumina NovaSeq PE150 platforms based on their effective concentrations and targeted sequencing outputs. 3. Result and analysis 3.1 Sequencing and assembly of Bacillus velezensis ANY11 With the data of each sample passing the quality control, a second-generation and third-generation sequencing was performed using Unicycler software [ 10 ]. Chromosome and plasmid sequences were screened and the chromosome sequences were assembled into a circular genome, followed by a coding gene prediction for the newly sequenced genome. Finally, the full genome sequence of Bacillus velezensis ANY11 was assembled into a circular chromosome measuring 3,949,880 bp in length with a 45.85% GC content (Fig. 1 ). Based on gene prediction, we identified 4,265 coding genes in Bacillus velezensis ANY11 . The total length of all coding genes was 3,530,166 bp, accounting for 89.37% of the entire genome. The distribution of gene lengths is presented in Fig. 2 . Repetitive sequences (DNA repeats) are identical or complementary fragments that are present in multiple copies in the genome and serve as components of gene regulatory networks. Based on their distribution in the linear genome, these repeated sequences are classified as interspersed or tandem repeats. Interspersed repeats include Short Interspersed Nuclear Elements (SINEs) and Long Interspersed Nuclear Elements (LINEs) notably with LINEs are often transpositionally active. Tandem repeats, on the other hand, can be further categorized into Minisatellite DNA and Microsatellite DNA. Repetitive sequences evolve at a faster pace, with certain sequences being species-specific. These species-specific repetitive elements serve as genetic markers, facilitating the study of evolutionary relationships among different species. Through the prediction of repeats, we identified 13 SINEs measuring 1,084 bp in in length, 34 LINEs 2,196 bp in length, 148 Minisatellite DNAs 9,512 bp in length, and one 39 bp-long Microsatellite DNA in the genome of Bacillus velezensis ANY11 (Table 1 ). Table 1 Statistics of the results of repetitive sequences of Bacillus velezensis ANY11 Type Number Total Length(bp) In genome(%) LTR 110 9155 0.2318 DNA 31 1759 0.0445 LINE 34 2196 0.0556 SINE 13 1084 0.0274 RC 2 88 0.0022 Minisatellite DNA 148 9512 0.2408 Microsatellite DNA 1 39 0.001 Note : Type: Type of interspersed repeat sequence; Number: Number of repeat sequences; Total Length (bp): Total length of repeat sequences; In genome (%): Percentage of repeat sequences in the genome; LTR: Long terminal repeat; DNA: DNA transposon; LINE: Long interspersed nuclear element; SINE: Short interspersed nuclear element; RC: Rolling circle; Minisatellite DNA: Minisatellite DNA; Microsatellite DNA: Microsatellite DNA. Genomic Islands (GIs) are genomic segments that are integrated into the genomes of bacteria, phages, or plasmids through horizontal gene transfer. GIs play an important role in the bacteria’s evolutionary adaptation and pathogenicity [ 11 ]. Based on sequence composition, the IslandPath-DIOMB software is used to predict gene island [ 12 ]. According to the presence of mobile genes and dinucleotide bias, this software identifies gene islands and potential horizontal gene transfer events. Through detection, seven genomic islands (GIs) are predicted in Bacillus velezensis ANY11 with a total length of 285,922 bp. The distribution of genes within these GIs is shown in Fig. 3 . An analysis of the secondary metabolite gene clusters in Bacillus velezensis ANY11 was conducted and the prediction revealed a total of 10 gene clusters, with the number of genes contained in each cluster shown in Fig. 4 . 3.2 Functional annotation of the Bacillus velezensis ANY11 genome We compared the predicted proteins of Bacillus velezensis ANY11 genes with functional databases such as NR, GO, KEGG, COG, and CAZy. After filtering, the results of each sequence alignment were used for gene function annotation. The Non-Redundant (NR) Database is a comprehensive and non-redundant protein database. The annotation results often include species information and can be used for species classification [ 12 ]. Figure 5 shows the species annotation of Bacillus velezensis ANY11 in the NR database. It can be observed that the protein sequences of the predicted genes are enriched in Bacillus amyloliquefaciens , Bacillus subtilis , and Bacillus velezensis . Gene Ontology(GO) provides a framework and set of concepts for describing the functions of gene products from all organisms. It considers three distinct aspects of how gene functions can be described: cellular component, molecular function, and biological process [ 13 ]. Cellular component describes describe subcellular structures, locations, and macromolecular complexes. Molecular function is used to describe the functions of individual genes and gene products, while biological process describes the biological processes involved in gene-encoded products. Figure 6 shows the statistical structure of the three major categories in the GO database for Bacillus velezensis ANY11 genes. As shown in the figure, 6570, 2622, and 3623 functional genes of Bacillus velezensis ANY11 are annotated to biological process, cellular component, and molecular function, respectively. Among them, the predicted gene-encoded products are mainly involved in two major biological processes: catalytic activity (1559 genes, 12.17%) and binding (1316 genes, 10.27%). KEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive database resource that that integrates genomic, chemical and systemic functional information. It systematically analyse the metabolic pathways of each gene product and compounds in the cell, so as to more comprehensively understand the functions of these gene products [ 14 ]. As shown in Fig. 7 , a total of 2473 genes annotated in the database were analyzed and found enriched in six major functional categories in the KEGG Pathway: Cellular Processes, Environmental Information Processing, Genetic Information Processing, Human Diseases, Metabolism, and Organismal Systems. Among them, the Metabolism function had the most annotations, with a total of 1699 genes. Within Metabolism, the Global and overview maps pathway (635 genes) was the most frequently annotated subcategory followed by the Carbohydrate metabolism pathway (230 genes). The database of COG (Clusters of Orthologous Groups of proteins) is an attempt on a phylogenetic classification of the proteins encoded in 21 complete genomes of bacteria, archaea and eukaryotes. By comparison, a certain protein sequence can be annotated to a specific COG, and each COG cluster consists of orthologous sequences, so that the function of the sequence can be inferred [ 15 ]. According to the COG functional annotation classification diagram for Bacillus velezensis ANY11 (Fig. 8 ), it’s been observe that there are 24 categories of annotations. Among them, genes related to amino acid transport and metabolism (303 genes, 9.00%) are the most common, followed genes related to transcription (290 genes, 8.62%). Additionally, genes related to carbohydrate transport and metabolism (245, 7.28%) rank the third, closely followed by general function prediction only. The Carbohydrate-Active Enzyme (CAZy) database was employed to annotate the enzyme families related to the catalysis of carbohydrate degradation, modification, and biosynthesis in the complete genome of Bacillus velezensis ANY11 (Fig. 9 ). Among the five major categories these families mainly comprise-Glycoside Hydrolases (GHs), GlycosylTransferases (GTs), Polysaccharide Lyases (PLs), Carbohydrate Esterases (CEs), and Auxiliary Activities (AAs), the largest number of genes encoded in the genome of Bacillus velezensis ANY11 are related to Glycoside Hydrolases, totaling 73 genes and accounting for 42.69%. Genes encoding Carbohydrate Esterases (44, 25.73%) and genes related to GlycosylTransferases (33, 21.05%) come second and third, respectively. 3.3 Analysis of the virulence or pathogenicity of Bacillus velezensis ANY11 The PHI database, which specializes in pathogen-host interactions, plays a crucial role in identifying target genes for drug intervention studies. It also encompasses antifungal compounds and their corresponding target genes. Each gene entry in the database includes nucleic acid and amino acid sequences, along with detailed descriptions of the predicted protein functions during host infection [ 16 ]. Utilizing the PHI database as a reference, we searched for potential pathogenicity-related genes in Bacillus velezensis ANY11 . As shown in Fig. 10 , out of the 349 genes annotated in the PHI database, 212 genes were annotated as reduced pathogenicity; 63 genes were annotated as having unaffected pathogenicity; 33 genes were annotated as virulence enchanced; 13 genes were annotated as lethal factors; 9 genes were annotated as pathogenic loss; 2 genes were annotated as effectors related to plant avirulence determinant; 1 gene was annotated as a chemically sensitive target; and 13 genes were annotated as unknown. The VFDB database is dedicated to the study of virulence factors in pathogenic bacteria, chlamydiae, and mycoplasmas by providing species information and basic characteristics of virulence genes and detailed descriptions of their functions and pathogenic mechanisms [ 17 ]. Comparing the genomic data of Bacillus velezensis ANY11 with the VFDB database, four virulence genes with known functions were identified (Identity threshold of ≥ 70%) (Table 2 ). Among these, the virulence genes ClpC [ 18 ] and BslA [ 19 ] are associated with bacterial adhesion, ClpP is related to bacterial growth and metabolism [ 20 ], and Capsule is involved in bacterial protection [ 21 ]. Table 2 The VFDB annotation results for Bacillus velezensis ANY11 reveal four virulence genes with known functions Gene-id VF-name Related-genes Identity(%) Functions GM003742 ClpC clpC endopeptidase Clp ATP-binding chain C 78.6 An ATPase promoting early escape form the phagosome of macrophages; ClpC is also required for adhesion and invasion, possibly by modulating the expression of InlA,InlB and ActA GM003613 ClpP clpP ATP-dependent Clp protease proteolytic subunit 77.9 Serine protease involved in proteolysis and is required for growth under stress conditions GM003119 BslA bslA/yuaB hydrophobin BslA 73.9 Encodes a major S-layer protein that is located within the pXO1 pathogenicity island that also codes for toxin genes. BslA mediates adherence and entry to epithelial cells by binding integrin 2 1 and complement component C1q;forms a highly hydrophobic coat around B. subtilis biofilms GM002521 Capsule gnd 6-phosphogluconate dehydrogenase 71.1 Assisting in evading the host immune system by protecting bacteria from opsonophagocytosis and serum killing The annotation of resistance genes can be performed using the CARD (Comprehensive Antibiotic Resistance Database) database, which is centered around the ARO (Antibiotic Resistance Ontology) and integrates information such as sequences, antibiotic resistance profiles, mechanisms of action, and associations among AROs. According to annotation of the database, the names of resistance-related genes and the types of antibiotics they confer resistance to are made clear. By aligning the amino acid sequences of Bacillus velezensis ANY11 with the CARD database and combining the target species' genes with their corresponding resistance function annotations, we obtained the annotation results as summarized in Table 3 . Table 3 The CARD annotation results for Bacillus velezensis ANY11 Gene-id ARO-name Drug-Class Resistance-Mechanism GM000467 vanT gene in vanG cluster glycopeptide antibiotic antibiotic target alteration GM000514 clbA lincosamide antibiotic; streptogramin antibiotic; streptogramin A antibiotic; oxazolidinone antibiotic; antibiotic target alteration GM000547 Nocardia farcinica rox rifamycin antibiotic antibiotic inactivation GM001271 BcI cephalosporin; penem antibiotic inactivation GM001819 qacJ disinfecting agents and antiseptics antibiotic efflux GM002063 vanY gene in vanB cluster glycopeptide antibiotic antibiotic target alteration GM002563 vanT gene in vanG cluster glycopeptide antibiotic antibiotic target alteration GM002728 tet(45) tetracycline antibiotic antibiotic efflux Based on Table 3 , it can be observed that the genome of Bacillus velezensis ANY11 contains eight antibiotic resistance genes. Specifically, the clbA, BcI, and qacJ genes exhibit multi-drug resistance, leading to our speculation that Bacillus velezensis ANY11 possesses a certain degree of antibiotic resistance. 4. Discussion As an efficient detection technique, whole-genome sequencing has been widely used to predict and explore microbial function. Therefore in order to obtain the genomic sequence information of B. velezensis ANY11 , isolated from bamboo fiber humus, whole-genome sequencing was conducted. After initial contruction, correction, and optimization, the genome was assembled into a circular chromosome with a length of 3,949,880 bp with the predicted coding genes measuring 3,530,166 bp in length, accounting for 89.37% of the entire genome. Additionally, 190 scattered repeats and 176 tandem repeats came into sight when repetitive sequences in the genome were detected. The non-coding RNAs include 86 tRNAs, 9 16sRNAs, 9 23sRNAs, 9 5sRNAs, and 9 sRNAs. As genomic islands can harbor genes for pathogenicity, metabolism, antibiotic resistance and symbiosis, prediction of the genomic islands in B. velezensis ANY11 was carried out. Furthermore, we predicted the prophages that might contribute to bacteria's acquisition of antibiotic resistance, improved environmental adaptability, enhanced adhesiveness, or pathogenicity. The results suggested that there were seven GIs, eleven prophages and ten gene clusters predicted in the whole genome of Bacillus velezensis ANY11 . Annotation results of the PHI and VFDB databases, elucidated strain B1 contained a total of 349 virulence factor genes. Based on these annotations, it is speculated that B. velezensis ANY11 may release virulence factors to inhibit the growth of pathogenic bacteria. Previous studies on the antibacterial properties of Bacillus velezensis have illustrated that Bacillus velezensis ZF2 demonstrates significant antagonistic activity against 14 plant pathogenic bacteria. Furthermore, it was predicted through genomic sequencing that the bacterium contains 14 gene clusters related to the synthesis of secondary metabolites. These gene clusters are capable of encoding various known antimicrobial compounds [ 22 ]. Previous studies have also delved into the genome of B. velezensis Bvel1 , which secretes metabolites that inhibit Botrytis cinerea and indentified 13 antibacterial biosynthetic gene clusters. Further analysis confirmed that these gene clusters encode various known antibacterial compounds such as iturin A, fengycin, surfactin, bacilysin, difficidin, bacillaene, and bacillibactin [ 23 ]. Analysis of the genome of Bacillus velezensis HNA3 strain revealed that it contains 77 genes encoding various antibacterial enzymes, including chitinase, endoglucanase, lysozyme, and peptidoglycan [ 24 ]. Bacillus velezensis is a potential biocontrol agent owing to its excellent inhibitory effects against various pathogenic fungi. The B. velezensis ANY11 strain, isolated from the intestine of Cyrtotrachelus buqueti , has been found to possess considerable antibacterial capability based on genomic analysis. However, further gene mining is required to identify specific genes that encode antibacterial enzymes and gene clusters related to disease resistance. A comprehensive exploration of the antibacterial genes of B. velezensis ANY11 will provide crucial insights into its antibacterial mechanisms and potential applications and serves as a molecular basis for the development and utilization of B. velezensis in agricultural production and biopesticide development. Significant genetic performance of B. velezensis ANY11 in carbohydrate degradation was observed by annotating its genes using functional databases such as NR, GO, KEGG, COG, and CAZy. The NR database annotations indicate a high correlation between the genes on the genome of strain B. velezensis ANY11 and those of Bacillus amyloliquefaciens , Bacillus subtilis , and Bacillus velezensis . Previous study has found that both Bacillus amyloliquefaciens [ 25 ] and Bacillus subtilis are capable of decomposing lignocellulose. There has been extensive research on various cellulases produced by Bacillus subtilis , investigating their impact on the digestibility and structural modification of lignocellulosic biomass [ 26 ]. The Bacillus velezensis SSF6 strain, isolated from humus soil, has been found to possess the ability to decompose lignocellulose. The Bacillus velezensis SSF6 strain underwent physiological and biochemical analysis using the Biolog Gen III MicroStation automatic microbial identification system and the carbon source utilization test revealed 24 positive reactions including the ability to utilize cellobiose, sucrose, and fructose as substrates [ 27 ]. Furthermore, Bacillus velezensis LC1 , which was also isolated from bamboo fiber humus in the intestine of Cyrtotrachelus buqueti , has the ability to decompose lignocellulose. When cultured on media and stained with Congo red, it produces clear zones around the colonies [ 9 ]. Through analysis and annotation using the KEGG database, 230 genes were identified related to carbohydrate metabolism pathways. Additionally, the five main types of carbohydrate enzymes were obtained present in the genome of B. velezensis ANY11 with the help of the CAZy database. These include genes from different glycoside hydrolase (GH) families that are essential for the degradation of cellulose and hemicellulose [ 27 ]. Table 4 compares the numbers of genes encoding glycoside hydrolases(GH), glycosyltransferases(GT), polysaccharide lyases(PL), carbohydrate esterases(CE), and auxiliary activities(AA) in several Bacillus velezensis strains with lignocellulose-degrading capabilities to those of B. velezensis ANY11 . Table 4 Comparison of CAZy database classification annotation results for other Bacillus velezensis Strains CBM CE GH GT PL AA B. velezensis B1 44 13 73 36 3 2 B. velezensis SSF6 (Zhang et al. 2023) 39 14 67 34 3 1 B. velezensis LC1 (Li et al. 2020) 15 30 43 38 3 6 B. velezensis 157 (Chen et al. 2018) 23 18 43 33 3 5 B. velezensis SQR9 (Zhang et al. 2015) 18 20 42 33 3 5 B. velezensis UCMB5113 (Niazi et al. 2014) 22 18 41 32 3 5 B. velezensis SYBC_H47 (Li et al. 2016) 18 21 37 32 3 5 B. velezensis FZB42 (Li et al. 2020) 21 10 37 36 3 1 Based on the results presented above, it was found that B. velezensis ANY11 possesses a large number of genes necessary for the metabolism of carbohydrates and other nutrients, indicating that the strain has a remarkable ability to degrade carbohydrate polysaccharides. Upon comparison with other strains that have lignocellulose degradation ability and cellulase activity, it is speculated that B. velezensis ANY11 also has the ability to degrade lignocellulose. Furthermore, it was observed that this strain has more GH family genes related to the degradation of cellulose and hemicellulose compared to most Bacillus velezensis strains, suggesting that it possesses a higher lignocellulose degradation capacity. Therefore, B. velezensis ANY11 , which was isolated from the bamboo fiber humus in intestines of Cyrtotrachelus buqueti , is able to decompose lignocellulose and assist in its conversion to ethanol, this makes it a potential functional strain for the production of new energy ethanol through biomass decomposition. However, further exploration is required to identify the specific cellulase genes within the genome of the strain which will eventually help improve the lignocellulose degradation rate and ethanol production efficiency. In this experiment, we analyzed the genome of B. velezensis ANY11 , isolated from bamboo fiber humus in the intestines of Cyrtotrachelus buqueti and obtained the complete genome sequence of the strain. The genome was annotated using functional databases to infer the functions of the strain. Initial tests were also conducted on the virulence and pathogenicity of this strain, with virulence factors annotated using the Pathogen-Host Interactions (PHI) database and VFDB database. In addition, drug resistance genes were annotated using the databases. The analysis of these data reveals that B. velezensis ANY11 contains genes associated with antibacterial activity. This indicates that it may have a certain inhibitory effect on pathogenic fungi, making it a potential biocontrol agent for improving agricultural production. In addition, it was discovered that the strain has the potential to degrade lignocellulose. This was determined through a comparative analysis of annotations from the CAZy database. Further research on the specific genes responsible for degrading enzyme in this strain can provide important bioinformatics evidence for revealing the genetic basis of lignocellulose degradation and the production of clean fuel ethanol from lignocellulose. Genomic sequencing and analysis in this study adds new microbial resources for lignocellulose degradation, promising to open up broad prospects for industrial production application. Declarations Author Contributions HW, YC, and JT conceived and designed the project. YC, JT, WX, XX, BM, JL, and FL performed the experiments. YC, WX, HW, CF, WL, HL, XH, and LY performed the data analysis. YC, JT, WX, and WX wrote the manuscript. HW, YY, and MM revised the manuscript. All authors read and approved the final manuscript. Funding This work was financially supported by the Scientific Research and Cultivation Plan of Leshan Normal University (No. 2022SSDJS009, KYPY2024-0005, KYCXTD2023-10, and KYPY2024-0012). Conflict of interest The authors declared that they have no conflict of interests related to this work. Data Availability Statement The datasets presented in this study can be found in NCBI publicdatabase. The accession number for genome sequence of Bacillus velezensis strain ANY11 is PRJNA1089309 Ethical Approval This is not applicable because this study does not involve human participants. Consent to Participate This is not applicable because this study does not involve human participants. Consent for Publication This is not applicable because this study does not involve human participants. Competing Interests The authors declare no competing interests. References Wang J, Xing J, Lu J, Sun Y, Zhao J, Miao S, Xiong Q, Zhang Y, Zhang G: Complete Genome Sequencing of Bacillus velezensis WRN014, and Comparison with Genome Sequences of other Bacillus velezensis Strains . J Microbiol Biotechnol 2019, 29 (5):794-808. Ye M, Tang X, Yang R, Zhang H, Li F, Tao F, Li F, Wang Z: Characteristics and Application of a Novel Species of Bacillus: Bacillus velezensis . ACS Chem Biol 2018, 13 (3):500-505. Lalloo R, Maharajh D, Görgens J, Gardiner N: A downstream process for production of a viable and stable Bacillus cereus aquaculture biological agent . Appl Microbiol Biotechnol 2010, 86 (2):499-508. Park G, Nam J, Kim J, Song J, Kim PI, Min HJ, Lee CWJBotKCS: Structure and mechanism of surfactin peptide from Bacillus velezensis antagonistic to fungi plant pathogens . B Korean Chem Soc 2019, 40 (7):704-709. Mansour AA, Da Costa A, Arnaud T, Lu-Chau TA, Fdz-Polanco M, Moreira MT, Cacho Rivero JA: Review of lignocellulolytic enzyme activity analyses and scale-down to microplate-based assays . Talanta 2016, 150 :629-637. Zhang H, Jackson TA: Autochthonous bacterial flora indicated by PCR-DGGE of 16S rRNA gene fragments from the alimentary tract of Costelytra zealandica (Coleoptera: Scarabaeidae) . J Appl Microbiol 2008, 105 (5):1277-1285. Peixoto SB, Cladera‐Olivera F, Daroit DJ, Brandelli AJAR: Cellulase‐producing Bacillus strains isolated from the intestine of Amazon basin fish . Aquac Res 2011, 42 (6):887-891. Chen L, Gu W, Xu H-y, Yang G-L, Shan X-F, Chen G, Kang Y-h, Wang C-F, Qian A-DJB: Comparative genome analysis of Bacillus velezensis reveals a potential for degrading lignocellulosic biomass . 3 Biotech 2018, 8 :1-5. Li Y, Lei L, Zheng L, Xiao X, Tang H, Luo C: Genome sequencing of gut symbiotic Bacillus velezensis LC1 for bioethanol production from bamboo shoots . Biotechnol Biofuels 2020, 13 :34. Wick RR, Judd LM, Gorrie CL, Holt KE: Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads . PLoS Comput Biol 2017, 13 (6):e1005595. Liu G, Kong Y, Fan Y, Geng C, Peng D, Sun M: Data on genome analysis of Bacillus velezensis LS69 . Data Brief 2017, 13 :1-5. Hsiao W, Wan I, Jones SJ, Brinkman FSL: IslandPath: aiding detection of genomic islands in prokaryotes . Bioinformatics 2003, 19 (3):418-420. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JTJNg: Gene ontology: tool for the unification of biology . Nat Genet 2000, 25 (1):25-29. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M: From genomics to chemical genomics: new developments in KEGG . Nucleic Acids Res 2006, 34 (Database issue):D354-D357. Galperin MY, Makarova KS, Wolf YI, Koonin EV: Expanded microbial genome coverage and improved protein family annotation in the COG database . Nucleic Acids Res 2015, 43 (Database issue):D261-D269. Urban M, Pant R, Raghunath A, Irvine AG, Pedro H, Hammond-Kosack KE: The Pathogen-Host Interactions database (PHI-base): additions and future developments . Nucleic Acids Res 2015, 43 (Database issue):D645-D655. Chen L, Xiong Z, Sun L, Yang J, Jin Q: VFDB 2012 update: toward the genetic diversity and molecular evolution of bacterial virulence factors . Nucleic Acids Res 2012, 40 (Database issue):D641-D645. Xu X, Huang L, Su Y, Yan Q: The complete genome sequence of Vibrio aestuarianus W-40 reveals virulence factor genes . Microbiologyopen 2018, 7 (3):e00568. Kern J, Schneewind OJMm: BslA, the S‐layer adhesin of B. anthracis, is a virulence factor for anthrax pathogenesis . Mol Microbiol 2010, 75 (2):324-332. Roy S, Zhu Y, Ma J, Roy AC, Zhang Y, Zhong X, Pan Z, Yao H: Role of ClpX and ClpP in Streptococcus suis serotype 2 stress tolerance and virulence . Microbiol Res 2019, 223-225 . Taylor CM, Roberts ISJCibv: Capsular polysaccharides and their role in virulence . Nephron 2005, 12 :55-66. Xu S, Xie X, Zhao Y, Shi Y, Chai A, Li L, Li B: Whole-genome analysis of bacillus velezensis ZF2, a biocontrol agent that protects cucumis sativus against corynespora leaf spot diseases . 3 Biotech 2020, 10 (4):186. Nifakos K, Tsalgatidou PC, Thomloudi E-E, Skagia A, Kotopoulis D, Baira E, Delis C, Papadimitriou K, Markellou E, Venieraki A et al : Genomic Analysis and Secondary Metabolites Production of the Endophytic Bacillus velezensis Bvel1: A Biocontrol Agent against Botrytis cinerea Causing Bunch Rot in Post-Harvest Table Grapes . Plants (Basel) 2021, 10 (8). Zaid DS, Cai S, Hu C, Li Z, Li Y: Comparative Genome Analysis Reveals Phylogenetic Identity of Bacillus velezensis HNA3 and Genomic Insights into Its Plant Growth Promotion and Biocontrol Effects . Microbiol Spectr 2022, 10 (1):e0216921. Mei J, Shen X, Gang L, Xu H, Wu F, Sheng L: A novel lignin degradation bacteria-Bacillus amyloliquefaciens SL-7 used to degrade straw lignin efficiently . Bioresour Technol 2020, 310 :123445. Malik WA, Javed S: Biochemical Characterization of Cellulase From Bacillus subtilis Strain and its Effect on Digestibility and Structural Modifications of Lignocellulose Rich Biomass . Front Bioeng Biotechnol 2021, 9 :800265. Zhang T, Wei S, Liu Y, Cheng C, Ma J, Yue L, Gao Y, Cheng Y, Ren Y, Su S et al : Screening and genome-wide analysis of lignocellulose-degrading bacteria from humic soil . Front Microbiol 2023, 14 :1167293. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4254829","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304918579,"identity":"2a75adb0-e00b-46dd-8d1a-c22035227398","order_by":0,"name":"Yulei Chen","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yulei","middleName":"","lastName":"Chen","suffix":""},{"id":304918580,"identity":"5ad6a5a0-4f02-4425-a1c2-8c96838ad8f3","order_by":1,"name":"Jiaye Tang","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jiaye","middleName":"","lastName":"Tang","suffix":""},{"id":304918581,"identity":"7bc24f43-0caf-47c3-a626-efce832eca42","order_by":2,"name":"Wenli Xin","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wenli","middleName":"","lastName":"Xin","suffix":""},{"id":304918582,"identity":"ca582e46-d0f8-4813-b4f7-d6a99349ff0e","order_by":3,"name":"Ximeng Xiao","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Ximeng","middleName":"","lastName":"Xiao","suffix":""},{"id":304918583,"identity":"5a60ff9e-4dcf-4268-a607-b4c666bd7280","order_by":4,"name":"Borui Mou","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Borui","middleName":"","lastName":"Mou","suffix":""},{"id":304918584,"identity":"50fc9b16-6e52-4688-a025-6f72ae58539c","order_by":5,"name":"Jialian Li","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jialian","middleName":"","lastName":"Li","suffix":""},{"id":304918585,"identity":"b486681f-4291-422d-9d41-9b24782a34e7","order_by":6,"name":"Fujia Lu","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Fujia","middleName":"","lastName":"Lu","suffix":""},{"id":304918586,"identity":"8a1afe63-d620-44f0-b8db-971c7105832e","order_by":7,"name":"Chun Fu","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Fu","suffix":""},{"id":304918587,"identity":"60fb4472-8379-4fdd-9fec-5df6c0913c09","order_by":8,"name":"Wencong Long","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wencong","middleName":"","lastName":"Long","suffix":""},{"id":304918588,"identity":"5808fcb7-fe7e-4584-8a40-a607f253091d","order_by":9,"name":"Hong Liao","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Liao","suffix":""},{"id":304918589,"identity":"a9fe1b92-cee1-4462-8fbc-1a2670aa6833","order_by":10,"name":"Xuebing Han","email":"","orcid":"","institution":"Hunan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xuebing","middleName":"","lastName":"Han","suffix":""},{"id":304918590,"identity":"52521ff3-2dda-4bd2-a683-1a47a865d557","order_by":11,"name":"Liuyun Yang","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Liuyun","middleName":"","lastName":"Yang","suffix":""},{"id":304918591,"identity":"42af8e65-d289-4440-a476-922ab31a8b1c","order_by":12,"name":"Menggen Ma","email":"","orcid":"","institution":"Sichuan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Menggen","middleName":"","lastName":"Ma","suffix":""},{"id":304918592,"identity":"aed66a4c-fffb-4e2f-a207-7ded16d45c34","order_by":13,"name":"Yaojun Yang","email":"","orcid":"","institution":"Leshan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yaojun","middleName":"","lastName":"Yang","suffix":""},{"id":304918593,"identity":"849bf536-6360-4e25-8eae-686ca0c0ef56","order_by":14,"name":"Hanyu Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIie2PMUvDQBTHL1RuOswmVwLN4Be4EFAL1X6VhEKm4tzRUuiUDxDRj+Bwq9srB+cSe+tBBvsBImTsIOililDolYyC91v+b/j/eO8h5HD8QRj8jj0Auh21wx1CYOnvKziFYZ6Z9Dor5BxmWHRQXl5lQJAIL/0nBJqoAXubzzdNiUL/7LA3Lm+zVomei3dYFVdVzKS3iAqNovuHxHLY9MIolcf1OhGUVCmX3jIgDUpYZVFUvVPGXJdMfOB1B0V/b0m5yhlQDD+KPqbU8fCRfU64xgn080ncl6n5paT2X9Q00vUsu+ZKiIZubwanQqw2jRyFfnBYMZxQxEzQ/QK11Vt6zS58OFZyOByO/8wX0EduOzhwrL4AAAAASUVORK5CYII=","orcid":"","institution":"Leshan Normal University","correspondingAuthor":true,"prefix":"","firstName":"Hanyu","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-04-12 01:59:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4254829/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4254829/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57104922,"identity":"62a46e52-b9a7-426e-aafa-a95df3325dd2","added_by":"auto","created_at":"2024-05-24 17:03:29","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":197067,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWhole genome mapping.\u003c/strong\u003e The outermost circle represents the position coordinates of the genome sequence. Moving from the outside to the inside, the following elements are included: gene function annotation results (including COG/KOG annotation information based on the actual project), ncRNA, and GC content of the genome. The GC content is calculated using a window size of (chromosome length / 1000) bp and a step size of (chromosome length / 1000) bp. The inward blue sections indicate regions where the GC content is lower than the average GC content of the entire genome, while the outward red sections indicate the opposite. The higher the peak, the greater the deviation from the average GC content. Additionally, the GC skew value is calculated using the same window and step sizes, with the specific algorithm being (G-C) / (G+C). The inward green sections represent regions where the content of G is lower than that of C, while the outward orange sections indicate the opposite.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/cb1468d317ccea6f1f0c51c7.jpg"},{"id":57104604,"identity":"69bb7d86-cffc-4032-a8a1-d40ae3cd2264","added_by":"auto","created_at":"2024-05-24 16:55:29","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":144584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene length distribution.\u003c/strong\u003e The horizontal axis represents the gene length, and the vertical axis represents the number of corresponding genes.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/2d3b33873d4b301fc4f701f4.jpg"},{"id":57104612,"identity":"d070e19e-49c8-4678-98f8-6efa42bd2912","added_by":"auto","created_at":"2024-05-24 16:55:29","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":67979,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStatistical chart of gene distribution in the genomic island.\u003c/strong\u003e The horizontal axis represents the length scale (only genomic islands with lengths less than 15kb are displayed in the figure).\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/52fa850f83529fd91cd07d83.jpg"},{"id":57104923,"identity":"e980de53-cdb4-4f47-ba63-2bc89e52e2ae","added_by":"auto","created_at":"2024-05-24 17:03:29","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":120754,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStatistical chart of gene clusters and their corresponding gene counts.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/1d9ccca660005a770632cf56.jpg"},{"id":57104603,"identity":"b33933e8-ef2d-4faa-a937-a37003621edf","added_by":"auto","created_at":"2024-05-24 16:55:28","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":162863,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStatistical chart of species annotations from the NR database.\u003c/strong\u003e The horizontal axis represents species ID, and the vertical axis represents the number of genes annotated.\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/e7dab4c299e6fe9cdb4d8878.jpg"},{"id":57104611,"identity":"cc2b8ec3-d10b-45c5-a46e-3840d6c9eb2d","added_by":"auto","created_at":"2024-05-24 16:55:29","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":110604,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene function annotation GO functional classification chart.\u003c/strong\u003e The horizontal axis represents the GO terms of the next level under the three major categories of GO, while the vertical axis represents the number of genes annotated to that term (including its sub-terms). The three different classifications represent the three basic categories of GO terms: biological process, cellular component, and molecular function (from left to right).\u003c/p\u003e","description":"","filename":"Fig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/dade936c2406eb6454a14573.jpg"},{"id":57104607,"identity":"fb75aeae-0dad-4b45-86da-49d7f031d351","added_by":"auto","created_at":"2024-05-24 16:55:29","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":290704,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene function annotation KEGG metabolic pathway classification chart.\u003c/strong\u003e The numbers on the bar chart represent the number of genes annotated. The other axis represents the level 1 functional category codes from the database, with the explanations for the codes provided in the corresponding legend.\u003c/p\u003e","description":"","filename":"Fig.7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/3841a29951f321844e3d0ffa.jpg"},{"id":57104616,"identity":"9d00d181-8500-438e-a7e7-640cf81862d5","added_by":"auto","created_at":"2024-05-24 16:55:30","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":167954,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene function annotation COG functional classification chart.\u003c/strong\u003e The horizontal axis represents the COG functional categories, and the vertical axis represents the number of genes annotated.\u003c/p\u003e","description":"","filename":"Fig.8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/0623c4c2f8827a0f893a1956.jpg"},{"id":57104615,"identity":"ca165c0e-1092-4e98-a2a0-316702302bee","added_by":"auto","created_at":"2024-05-24 16:55:30","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":75421,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStatistical chart of CAZy functional classification and corresponding gene counts.\u003c/strong\u003e The horizontal axis represents the classification types from the CAZy database, while the vertical axis represents the number of genes annotated.\u003c/p\u003e","description":"","filename":"Fig.9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/e933d2b0b425c55a2d78771c.jpg"},{"id":57104609,"identity":"e300cd19-ca9f-497a-b5f3-08caa1cf3106","added_by":"auto","created_at":"2024-05-24 16:55:29","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":80425,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution chart of phenotypic mutation types of pathogen PHI.\u003c/strong\u003e The horizontal axis represents the phenotypic mutation types, while the vertical axis represents the number of genes annotated.\u003c/p\u003e","description":"","filename":"Fig.10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/35481a6ab4e51dbb4cead87b.jpg"},{"id":59485681,"identity":"52830208-e6cc-4e47-b13a-227d542925dd","added_by":"auto","created_at":"2024-07-02 11:00:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2888014,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4254829/v1/6aea4475-9498-4757-89cc-0a7bbe5e0f10.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Complete Genome Sequencing and Functional Prediction of Bacillus velezensis ANY11","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cem\u003eBacillus velezensis\u003c/em\u003e was first isolated from the mouth of the river V\u0026eacute;lez in M\u0026aacute;laga (Southern Spain) in 2005 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Widely distributed in various environments such as plant rhizosphere, soil, rivers, human food, animal intestines, and seawater, these microorganisms are easy to isolate and cultivate [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. \u003cem\u003eBacillus velezensis\u003c/em\u003e belongs to the \u003cem\u003egenus Bacillus\u003c/em\u003e and is a type of Gram-positive rod-shaped multifunctional bacterium. Under unfavorable conditions, it can produce spores, which can be converted into powder without causing bacterial death. Such feature gives \u003cem\u003eBacillus velezensis\u003c/em\u003e a significant advantage compared to other biocontrol bacteria [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDue to its harmlessness to humans and animals and its environmental friendliness, \u003cem\u003eBacillus velezensis\u003c/em\u003e has been commercially utilized as a biofertilizer and biopesticide. Extensive research has demonstrated that \u003cem\u003eBacillus velezensis\u003c/em\u003e produce a broad-spectrum antibacterial activity effectively against a variety of plant pathogenic fungi. Consequently, it can be utilized in the prevention and control of plant diseases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Currently, there has been extensive research on the antibacterial activity of \u003cem\u003eBacillus velezensis\u003c/em\u003e. A genomic sequencing was conducted to predict the gene clusters responsible for the synthesis of secondary metabolites and explore the antibacterial active substances and their mechanisms. By delving into the antibacterial genes of these strains, our study provides a bioinformatics foundation for the efficient development and application of \u003cem\u003eBacillus velezensis\u003c/em\u003e in agricultural production.\u003c/p\u003e \u003cp\u003eLignocellulose, a widely distributed, renewable, and abundantly available biomass resource, is an essential raw material for the production of bioethanol. However, the hydrolysis of lignocellulose, particularly the degradation of cellulose, remains a significant challenge in the production of lignocellulosic bioethanol [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In nature, there are many examples of lignocellulose degradation, out of which herbivorous insects are considered the most dominant. Among these insects, gut symbiotic microorganisms play a crucial role in degrading lignocellulose [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, the intestines of scavenger insects represent ideal sites for isolating lignocellulose-degrading microorganisms.\u003c/p\u003e \u003cp\u003eStudies have shown that \u003cem\u003eBacillus velezensis\u003c/em\u003e can produce highly active neutral enzymes -proteases and cellulases, which break down cellulose into oligosaccharides or monosaccharides [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, \u003cem\u003eBacillus velezensis\u003c/em\u003e possesses genes encoding enzymes related to the degradation of cellulose, xylan, lignin, starch, mannan, galactosides, and arabinose [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Previous studies have isolated \u003cem\u003eBacillus velezensis LC1\u003c/em\u003e from bamboo fiber humus and whole-genome sequencing as well as cellulase activity measurement was conducted. This symbiotic bacterium possesses the ability to degrade lignocellulose and exhibits cellulase activity, indicating its potential to further convert bamboo lignocellulosic components into ethanol [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e used in this experiment was isolated from bamboo fiber humus in the intestines of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e. Whole-genome sequencing, genomic analysis, and functional annotation conducted in this study lay the foundation for future research on its potential applications in biofertilizers, plant disease and pest control, as well as in the biocatalytic production of renewable ethanol.\u003c/p\u003e"},{"header":"2. Experimental materials and procedures","content":"\u003cp\u003e \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e was isolated from bamboo fiber humus in the intestines of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eLB Medium: 0.5% yeast extract, 1% peptone, 1% sodium chloride, pH adjusted to 7.0.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eBacillus velezensis\u003c/em\u003e strain was inoculated into LB liquid medium and cultured with constant shaking at 220 r/min at 30\u0026deg;C for 12\u0026ndash;24 hours to activate the bacteria. After activation, the bacterial cells were collected by centrifugation.\u003c/p\u003e \u003cp\u003eGenomic DNA from the sample was extracted using the STE method. The purity and integrity of the DNA were subsequently assessed by agarose gel electrophoresis, and quantitation was performed using Qubit. Large fragments were then recovered using the BluePippin automated nucleic acid fragment recovery system, followed by end repair and A-tailing. The samples were then mixed in equimolar amounts, and adapter ligation was performed using the SQK-LSK109 ligation kit (Oxford Nanopore Technologies) to construct a 1D library. Finally, sequencing was carried out using the Nanopore platform. The DNA samples that passed the quality check of electrophoresis were randomly fragmented into approximately 350 bp-long segments using an ultrasonic disruptor. The processed DNA fragments were then used for library preparation. After passing library quality control, the different libraries were sequenced on both the Nanopore PromethION and Illumina NovaSeq PE150 platforms based on their effective concentrations and targeted sequencing outputs.\u003c/p\u003e"},{"header":"3. Result and analysis","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Sequencing and assembly of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eWith the data of each sample passing the quality control, a second-generation and third-generation sequencing was performed using Unicycler software [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Chromosome and plasmid sequences were screened and the chromosome sequences were assembled into a circular genome, followed by a coding gene prediction for the newly sequenced genome. Finally, the full genome sequence of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e was assembled into a circular chromosome measuring 3,949,880 bp in length with a 45.85% GC content (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Based on gene prediction, we identified 4,265 coding genes in \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e. The total length of all coding genes was 3,530,166 bp, accounting for 89.37% of the entire genome. The distribution of gene lengths is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRepetitive sequences (DNA repeats) are identical or complementary fragments that are present in multiple copies in the genome and serve as components of gene regulatory networks. Based on their distribution in the linear genome, these repeated sequences are classified as interspersed or tandem repeats. Interspersed repeats include Short Interspersed Nuclear Elements (SINEs) and Long Interspersed Nuclear Elements (LINEs) notably with LINEs are often transpositionally active. Tandem repeats, on the other hand, can be further categorized into Minisatellite DNA and Microsatellite DNA. Repetitive sequences evolve at a faster pace, with certain sequences being species-specific. These species-specific repetitive elements serve as genetic markers, facilitating the study of evolutionary relationships among different species.\u003c/p\u003e \u003cp\u003eThrough the prediction of repeats, we identified 13 SINEs measuring 1,084 bp in in length, 34 LINEs 2,196 bp in length, 148 Minisatellite DNAs 9,512 bp in length, and one 39 bp-long Microsatellite DNA in the genome of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eStatistics of the results of repetitive sequences of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal Length(bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIn genome(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLINE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSINE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinisatellite DNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrosatellite DNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNote\u003c/b\u003e: Type: Type of interspersed repeat sequence; Number: Number of repeat sequences; Total Length (bp): Total length of repeat sequences; In genome (%): Percentage of repeat sequences in the genome; LTR: Long terminal repeat; DNA: DNA transposon; LINE: Long interspersed nuclear element; SINE: Short interspersed nuclear element; RC: Rolling circle; Minisatellite DNA: Minisatellite DNA; Microsatellite DNA: Microsatellite DNA.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGenomic Islands (GIs) are genomic segments that are integrated into the genomes of bacteria, phages, or plasmids through horizontal gene transfer. GIs play an important role in the bacteria\u0026rsquo;s evolutionary adaptation and pathogenicity [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Based on sequence composition, the IslandPath-DIOMB software is used to predict gene island [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. According to the presence of mobile genes and dinucleotide bias, this software identifies gene islands and potential horizontal gene transfer events. Through detection, seven genomic islands (GIs) are predicted in \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e with a total length of 285,922 bp. The distribution of genes within these GIs is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAn analysis of the secondary metabolite gene clusters in \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e was conducted and the prediction revealed a total of 10 gene clusters, with the number of genes contained in each cluster shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Functional annotation of the \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e genome\u003c/h2\u003e \u003cp\u003eWe compared the predicted proteins of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e genes with functional databases such as NR, GO, KEGG, COG, and CAZy. After filtering, the results of each sequence alignment were used for gene function annotation.\u003c/p\u003e \u003cp\u003eThe Non-Redundant (NR) Database is a comprehensive and non-redundant protein database. The annotation results often include species information and can be used for species classification [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the species annotation of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e in the NR database. It can be observed that the protein sequences of the predicted genes are enriched in \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e, \u003cem\u003eBacillus subtilis\u003c/em\u003e, and \u003cem\u003eBacillus velezensis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGene Ontology(GO) provides a framework and set of concepts for describing the functions of gene products from all organisms. It considers three distinct aspects of how gene functions can be described: cellular component, molecular function, and biological process [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Cellular component describes describe subcellular structures, locations, and macromolecular complexes. Molecular function is used to describe the functions of individual genes and gene products, while biological process describes the biological processes involved in gene-encoded products. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the statistical structure of the three major categories in the GO database for \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e genes. As shown in the figure, 6570, 2622, and 3623 functional genes of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e are annotated to biological process, cellular component, and molecular function, respectively. Among them, the predicted gene-encoded products are mainly involved in two major biological processes: catalytic activity (1559 genes, 12.17%) and binding (1316 genes, 10.27%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive database resource that that integrates genomic, chemical and systemic functional information. It systematically analyse the metabolic pathways of each gene product and compounds in the cell, so as to more comprehensively understand the functions of these gene products [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, a total of 2473 genes annotated in the database were analyzed and found enriched in six major functional categories in the KEGG Pathway: Cellular Processes, Environmental Information Processing, Genetic Information Processing, Human Diseases, Metabolism, and Organismal Systems. Among them, the Metabolism function had the most annotations, with a total of 1699 genes. Within Metabolism, the Global and overview maps pathway (635 genes) was the most frequently annotated subcategory followed by the Carbohydrate metabolism pathway (230 genes).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe database of COG (Clusters of Orthologous Groups of proteins) is an attempt on a phylogenetic classification of the proteins encoded in 21 complete genomes of bacteria, archaea and eukaryotes. By comparison, a certain protein sequence can be annotated to a specific COG, and each COG cluster consists of orthologous sequences, so that the function of the sequence can be inferred [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to the COG functional annotation classification diagram for \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), it\u0026rsquo;s been observe that there are 24 categories of annotations. Among them, genes related to amino acid transport and metabolism (303 genes, 9.00%) are the most common, followed genes related to transcription (290 genes, 8.62%). Additionally, genes related to carbohydrate transport and metabolism (245, 7.28%) rank the third, closely followed by general function prediction only.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Carbohydrate-Active Enzyme (CAZy) database was employed to annotate the enzyme families related to the catalysis of carbohydrate degradation, modification, and biosynthesis in the complete genome of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Among the five major categories these families mainly comprise-Glycoside Hydrolases (GHs), GlycosylTransferases (GTs), Polysaccharide Lyases (PLs), Carbohydrate Esterases (CEs), and Auxiliary Activities (AAs), the largest number of genes encoded in the genome of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e are related to Glycoside Hydrolases, totaling 73 genes and accounting for 42.69%. Genes encoding Carbohydrate Esterases (44, 25.73%) and genes related to GlycosylTransferases (33, 21.05%) come second and third, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Analysis of the virulence or pathogenicity of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe PHI database, which specializes in pathogen-host interactions, plays a crucial role in identifying target genes for drug intervention studies. It also encompasses antifungal compounds and their corresponding target genes. Each gene entry in the database includes nucleic acid and amino acid sequences, along with detailed descriptions of the predicted protein functions during host infection [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Utilizing the PHI database as a reference, we searched for potential pathogenicity-related genes in \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, out of the 349 genes annotated in the PHI database, 212 genes were annotated as reduced pathogenicity; 63 genes were annotated as having unaffected pathogenicity; 33 genes were annotated as virulence enchanced; 13 genes were annotated as lethal factors; 9 genes were annotated as pathogenic loss; 2 genes were annotated as effectors related to plant avirulence determinant; 1 gene was annotated as a chemically sensitive target; and 13 genes were annotated as unknown.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe VFDB database is dedicated to the study of virulence factors in pathogenic bacteria, chlamydiae, and mycoplasmas by providing species information and basic characteristics of virulence genes and detailed descriptions of their functions and pathogenic mechanisms [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Comparing the genomic data of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e with the VFDB database, four virulence genes with known functions were identified (Identity threshold of \u0026ge;\u0026thinsp;70%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among these, the virulence genes ClpC [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and BslA [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] are associated with bacterial adhesion, ClpP is related to bacterial growth and metabolism [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and Capsule is involved in bacterial protection [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\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\u003eThe VFDB annotation results for \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e reveal four virulence genes with known functions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene-id\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVF-name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRelated-genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentity(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFunctions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM003742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClpC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eclpC endopeptidase Clp ATP-binding chain C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAn ATPase promoting early escape form the phagosome of macrophages; ClpC is also required for adhesion and invasion, possibly by modulating the expression of InlA,InlB and ActA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM003613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClpP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eclpP ATP-dependent Clp protease proteolytic subunit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSerine protease involved in proteolysis and is required for growth under stress conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM003119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBslA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ebslA/yuaB hydrophobin BslA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEncodes a major S-layer protein that is located within the pXO1 pathogenicity island that also codes for toxin genes. BslA mediates adherence and entry to epithelial cells by binding integrin\u0026thinsp;\u0026lt;\u0026thinsp;alpha\u0026thinsp;\u0026gt;\u0026thinsp;2\u0026thinsp;\u0026lt;\u0026thinsp;beta\u0026thinsp;\u0026gt;\u0026thinsp;1 and complement component C1q;forms a highly hydrophobic coat around B. subtilis biofilms\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM002521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCapsule\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003egnd 6-phosphogluconate dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAssisting in evading the host immune system by protecting bacteria from opsonophagocytosis and serum killing\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\u003eThe annotation of resistance genes can be performed using the CARD (Comprehensive Antibiotic Resistance Database) database, which is centered around the ARO (Antibiotic Resistance Ontology) and integrates information such as sequences, antibiotic resistance profiles, mechanisms of action, and associations among AROs. According to annotation of the database, the names of resistance-related genes and the types of antibiotics they confer resistance to are made clear. By aligning the amino acid sequences of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e with the CARD database and combining the target species' genes with their corresponding resistance function annotations, we obtained the annotation results as summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\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\u003eThe CARD annotation results for \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene-id\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eARO-name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDrug-Class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResistance-Mechanism\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM000467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evanT gene in vanG cluster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eglycopeptide antibiotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic target alteration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM000514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eclbA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elincosamide antibiotic; streptogramin antibiotic; streptogramin A antibiotic; oxazolidinone antibiotic;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic target alteration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM000547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNocardia farcinica rox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erifamycin antibiotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic inactivation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM001271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBcI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecephalosporin; penem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic inactivation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM001819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eqacJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edisinfecting agents and antiseptics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic efflux\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM002063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evanY gene in vanB cluster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eglycopeptide antibiotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic target alteration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM002563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evanT gene in vanG cluster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eglycopeptide antibiotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic target alteration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGM002728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etet(45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etetracycline antibiotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eantibiotic efflux\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\u003eBased on Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, it can be observed that the genome of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e contains eight antibiotic resistance genes. Specifically, the clbA, BcI, and qacJ genes exhibit multi-drug resistance, leading to our speculation that \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e possesses a certain degree of antibiotic resistance.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAs an efficient detection technique, whole-genome sequencing has been widely used to predict and explore microbial function. Therefore in order to obtain the genomic sequence information of \u003cem\u003eB. velezensis ANY11\u003c/em\u003e, isolated from bamboo fiber humus, whole-genome sequencing was conducted. After initial contruction, correction, and optimization, the genome was assembled into a circular chromosome with a length of 3,949,880 bp with the predicted coding genes measuring 3,530,166 bp in length, accounting for 89.37% of the entire genome. Additionally, 190 scattered repeats and 176 tandem repeats came into sight when repetitive sequences in the genome were detected. The non-coding RNAs include 86 tRNAs, 9 16sRNAs, 9 23sRNAs, 9 5sRNAs, and 9 sRNAs.\u003c/p\u003e \u003cp\u003eAs genomic islands can harbor genes for pathogenicity, metabolism, antibiotic resistance and symbiosis, prediction of the genomic islands in \u003cem\u003eB. velezensis ANY11\u003c/em\u003e was carried out. Furthermore, we predicted the prophages that might contribute to bacteria's acquisition of antibiotic resistance, improved environmental adaptability, enhanced adhesiveness, or pathogenicity. The results suggested that there were seven GIs, eleven prophages and ten gene clusters predicted in the whole genome of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e. Annotation results of the PHI and VFDB databases, elucidated strain B1 contained a total of 349 virulence factor genes. Based on these annotations, it is speculated that \u003cem\u003eB. velezensis ANY11\u003c/em\u003e may release virulence factors to inhibit the growth of pathogenic bacteria. Previous studies on the antibacterial properties of \u003cem\u003eBacillus velezensis\u003c/em\u003e have illustrated that \u003cem\u003eBacillus velezensis ZF2\u003c/em\u003e demonstrates significant antagonistic activity against 14 plant pathogenic bacteria. Furthermore, it was predicted through genomic sequencing that the bacterium contains 14 gene clusters related to the synthesis of secondary metabolites. These gene clusters are capable of encoding various known antimicrobial compounds [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Previous studies have also delved into the genome of \u003cem\u003eB. velezensis Bvel1\u003c/em\u003e, which secretes metabolites that inhibit \u003cem\u003eBotrytis cinerea\u003c/em\u003e and indentified 13 antibacterial biosynthetic gene clusters. Further analysis confirmed that these gene clusters encode various known antibacterial compounds such as iturin A, fengycin, surfactin, bacilysin, difficidin, bacillaene, and bacillibactin [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Analysis of the genome of \u003cem\u003eBacillus velezensis HNA3\u003c/em\u003e strain revealed that it contains 77 genes encoding various antibacterial enzymes, including chitinase, endoglucanase, lysozyme, and peptidoglycan [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. \u003cem\u003eBacillus velezensis\u003c/em\u003e is a potential biocontrol agent owing to its excellent inhibitory effects against various pathogenic fungi. The \u003cem\u003eB. velezensis ANY11\u003c/em\u003e strain, isolated from the intestine of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e, has been found to possess considerable antibacterial capability based on genomic analysis. However, further gene mining is required to identify specific genes that encode antibacterial enzymes and gene clusters related to disease resistance. A comprehensive exploration of the antibacterial genes of \u003cem\u003eB. velezensis ANY11\u003c/em\u003e will provide crucial insights into its antibacterial mechanisms and potential applications and serves as a molecular basis for the development and utilization of \u003cem\u003eB. velezensis\u003c/em\u003e in agricultural production and biopesticide development.\u003c/p\u003e \u003cp\u003eSignificant genetic performance of \u003cem\u003eB. velezensis ANY11\u003c/em\u003e in carbohydrate degradation was observed by annotating its genes using functional databases such as NR, GO, KEGG, COG, and CAZy. The NR database annotations indicate a high correlation between the genes on the genome of strain \u003cem\u003eB. velezensis ANY11\u003c/em\u003e and those of \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e, \u003cem\u003eBacillus subtilis\u003c/em\u003e, and \u003cem\u003eBacillus velezensis\u003c/em\u003e. Previous study has found that both \u003cem\u003eBacillus amyloliquefaciens\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and \u003cem\u003eBacillus subtilis\u003c/em\u003e are capable of decomposing lignocellulose. There has been extensive research on various cellulases produced by \u003cem\u003eBacillus subtilis\u003c/em\u003e, investigating their impact on the digestibility and structural modification of lignocellulosic biomass [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The \u003cem\u003eBacillus velezensis SSF6\u003c/em\u003e strain, isolated from humus soil, has been found to possess the ability to decompose lignocellulose. The \u003cem\u003eBacillus velezensis SSF6\u003c/em\u003e strain underwent physiological and biochemical analysis using the Biolog Gen III MicroStation automatic microbial identification system and the carbon source utilization test revealed 24 positive reactions including the ability to utilize cellobiose, sucrose, and fructose as substrates [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, \u003cem\u003eBacillus velezensis LC1\u003c/em\u003e, which was also isolated from bamboo fiber humus in the intestine of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e, has the ability to decompose lignocellulose. When cultured on media and stained with Congo red, it produces clear zones around the colonies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Through analysis and annotation using the KEGG database, 230 genes were identified related to carbohydrate metabolism pathways. Additionally, the five main types of carbohydrate enzymes were obtained present in the genome of \u003cem\u003eB. velezensis ANY11 with the help of\u003c/em\u003e the CAZy database. These include genes from different glycoside hydrolase (GH) families that are essential for the degradation of cellulose and hemicellulose [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e compares the numbers of genes encoding glycoside hydrolases(GH), glycosyltransferases(GT), polysaccharide lyases(PL), carbohydrate esterases(CE), and auxiliary activities(AA) in several \u003cem\u003eBacillus velezensis\u003c/em\u003e strains with lignocellulose-degrading capabilities to those of \u003cem\u003eB. velezensis ANY11\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of CAZy database classification annotation results for other \u003cem\u003eBacillus velezensis\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCBM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAA\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\u003eB. velezensis B1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis SSF6\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Zhang et al. 2023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis LC1\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Li et al. 2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis 157\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Chen et al. 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis SQR9\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Zhang et al. 2015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis UCMB5113\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Niazi et al. 2014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis SYBC_H47\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Li et al. 2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eB. velezensis FZB42\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(Li et al. 2020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\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\u003eBased on the results presented above, it was found that \u003cem\u003eB. velezensis ANY11\u003c/em\u003e possesses a large number of genes necessary for the metabolism of carbohydrates and other nutrients, indicating that the strain has a remarkable ability to degrade carbohydrate polysaccharides. Upon comparison with other strains that have lignocellulose degradation ability and cellulase activity, it is speculated that \u003cem\u003eB. velezensis ANY11\u003c/em\u003e also has the ability to degrade lignocellulose. Furthermore, it was observed that this strain has more GH family genes related to the degradation of cellulose and hemicellulose compared to most \u003cem\u003eBacillus velezensis\u003c/em\u003e strains, suggesting that it possesses a higher lignocellulose degradation capacity. Therefore, \u003cem\u003eB. velezensis ANY11\u003c/em\u003e, which was isolated from the bamboo fiber humus in intestines of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e, is able to decompose lignocellulose and assist in its conversion to ethanol, this makes it a potential functional strain for the production of new energy ethanol through biomass decomposition. However, further exploration is required to identify the specific cellulase genes within the genome of the strain which will eventually help improve the lignocellulose degradation rate and ethanol production efficiency.\u003c/p\u003e \u003cp\u003eIn this experiment, we analyzed the genome of \u003cem\u003eB. velezensis ANY11\u003c/em\u003e, isolated from bamboo fiber humus in the intestines of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e and obtained the complete genome sequence of the strain. The genome was annotated using functional databases to infer the functions of the strain. Initial tests were also conducted on the virulence and pathogenicity of this strain, with virulence factors annotated using the Pathogen-Host Interactions (PHI) database and VFDB database. In addition, drug resistance genes were annotated using the databases. The analysis of these data reveals that \u003cem\u003eB. velezensis ANY11\u003c/em\u003e contains genes associated with antibacterial activity. This indicates that it may have a certain inhibitory effect on pathogenic fungi, making it a potential biocontrol agent for improving agricultural production. In addition, it was discovered that the strain has the potential to degrade lignocellulose. This was determined through a comparative analysis of annotations from the CAZy database. Further research on the specific genes responsible for degrading enzyme in this strain can provide important bioinformatics evidence for revealing the genetic basis of lignocellulose degradation and the production of clean fuel ethanol from lignocellulose. Genomic sequencing and analysis in this study adds new microbial resources for lignocellulose degradation, promising to open up broad prospects for industrial production application.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e HW, YC, and JT conceived and designed the project. YC, JT, WX, XX, BM, JL, and FL performed the experiments. YC, WX, HW, CF, WL, HL, XH, and LY performed the data analysis. YC, JT, WX, and WX wrote the manuscript. HW, YY, and MM revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was financially supported by the Scientific Research and Cultivation Plan of Leshan Normal University (No. 2022SSDJS009, KYPY2024-0005, KYCXTD2023-10, and KYPY2024-0012).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors declared that they have no conflict of interests related to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003eThe datasets presented in this study can be found in NCBI publicdatabase. The accession number for genome sequence of Bacillus velezensis strain ANY11 is PRJNA1089309\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003eThis is not applicable because this study does not involve human participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e This is not applicable because this study does not involve human participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e This is not applicable because this study does not involve human participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang J, Xing J, Lu J, Sun Y, Zhao J, Miao S, Xiong Q, Zhang Y, Zhang G: \u003cstrong\u003eComplete Genome Sequencing of Bacillus velezensis WRN014, and Comparison with Genome Sequences of other Bacillus velezensis Strains\u003c/strong\u003e. \u003cem\u003eJ Microbiol Biotechnol \u003c/em\u003e2019, \u003cstrong\u003e29\u003c/strong\u003e(5):794-808.\u003c/li\u003e\n\u003cli\u003eYe M, Tang X, Yang R, Zhang H, Li F, Tao F, Li F, Wang Z: \u003cstrong\u003eCharacteristics and Application of a Novel Species of Bacillus: Bacillus velezensis\u003c/strong\u003e. \u003cem\u003eACS Chem Biol \u003c/em\u003e2018, \u003cstrong\u003e13\u003c/strong\u003e(3):500-505.\u003c/li\u003e\n\u003cli\u003eLalloo R, Maharajh D, G\u0026ouml;rgens J, Gardiner N: \u003cstrong\u003eA downstream process for production of a viable and stable Bacillus cereus aquaculture biological agent\u003c/strong\u003e. \u003cem\u003eAppl Microbiol Biotechnol \u003c/em\u003e2010, \u003cstrong\u003e86\u003c/strong\u003e(2):499-508.\u003c/li\u003e\n\u003cli\u003ePark G, Nam J, Kim J, Song J, Kim PI, Min HJ, Lee CWJBotKCS: \u003cstrong\u003eStructure and mechanism of surfactin peptide from Bacillus velezensis antagonistic to fungi plant pathogens\u003c/strong\u003e. \u003cem\u003eB Korean Chem Soc\u003c/em\u003e 2019, \u003cstrong\u003e40\u003c/strong\u003e(7):704-709.\u003c/li\u003e\n\u003cli\u003eMansour AA, Da Costa A, Arnaud T, Lu-Chau TA, Fdz-Polanco M, Moreira MT, Cacho Rivero JA: \u003cstrong\u003eReview of lignocellulolytic enzyme activity analyses and scale-down to microplate-based assays\u003c/strong\u003e. \u003cem\u003eTalanta \u003c/em\u003e2016, \u003cstrong\u003e150\u003c/strong\u003e:629-637.\u003c/li\u003e\n\u003cli\u003eZhang H, Jackson TA: \u003cstrong\u003eAutochthonous bacterial flora indicated by PCR-DGGE of 16S rRNA gene fragments from the alimentary tract of Costelytra zealandica (Coleoptera: Scarabaeidae)\u003c/strong\u003e. \u003cem\u003eJ Appl Microbiol \u003c/em\u003e2008, \u003cstrong\u003e105\u003c/strong\u003e(5):1277-1285.\u003c/li\u003e\n\u003cli\u003ePeixoto SB, Cladera‐Olivera F, Daroit DJ, Brandelli AJAR: \u003cstrong\u003eCellulase‐producing Bacillus strains isolated from the intestine of Amazon basin fish\u003c/strong\u003e. \u003cem\u003eAquac Res\u003c/em\u003e 2011, \u003cstrong\u003e42\u003c/strong\u003e(6):887-891.\u003c/li\u003e\n\u003cli\u003eChen L, Gu W, Xu H-y, Yang G-L, Shan X-F, Chen G, Kang Y-h, Wang C-F, Qian A-DJB: \u003cstrong\u003eComparative genome analysis of Bacillus velezensis reveals a potential for degrading lignocellulosic biomass\u003c/strong\u003e. \u003cem\u003e3 Biotech\u003c/em\u003e 2018, \u003cstrong\u003e8\u003c/strong\u003e:1-5.\u003c/li\u003e\n\u003cli\u003eLi Y, Lei L, Zheng L, Xiao X, Tang H, Luo C: \u003cstrong\u003eGenome sequencing of gut symbiotic Bacillus velezensis LC1 for bioethanol production from bamboo shoots\u003c/strong\u003e. \u003cem\u003eBiotechnol Biofuels \u003c/em\u003e2020, \u003cstrong\u003e13\u003c/strong\u003e:34.\u003c/li\u003e\n\u003cli\u003eWick RR, Judd LM, Gorrie CL, Holt KE: \u003cstrong\u003eUnicycler: Resolving bacterial genome assemblies from short and long sequencing reads\u003c/strong\u003e. \u003cem\u003ePLoS Comput Biol \u003c/em\u003e2017, \u003cstrong\u003e13\u003c/strong\u003e(6):e1005595.\u003c/li\u003e\n\u003cli\u003eLiu G, Kong Y, Fan Y, Geng C, Peng D, Sun M: \u003cstrong\u003eData on genome analysis of Bacillus velezensis LS69\u003c/strong\u003e. \u003cem\u003eData Brief \u003c/em\u003e2017, \u003cstrong\u003e13\u003c/strong\u003e:1-5.\u003c/li\u003e\n\u003cli\u003eHsiao W, Wan I, Jones SJ, Brinkman FSL: \u003cstrong\u003eIslandPath: aiding detection of genomic islands in prokaryotes\u003c/strong\u003e. \u003cem\u003eBioinformatics \u003c/em\u003e2003, \u003cstrong\u003e19\u003c/strong\u003e(3):418-420.\u003c/li\u003e\n\u003cli\u003eAshburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JTJNg: \u003cstrong\u003eGene ontology: tool for the unification of biology\u003c/strong\u003e. \u003cem\u003eNat Genet\u003c/em\u003e 2000, \u003cstrong\u003e25\u003c/strong\u003e(1):25-29.\u003c/li\u003e\n\u003cli\u003eKanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M: \u003cstrong\u003eFrom genomics to chemical genomics: new developments in KEGG\u003c/strong\u003e. \u003cem\u003eNucleic Acids Res \u003c/em\u003e2006, \u003cstrong\u003e34\u003c/strong\u003e(Database issue):D354-D357.\u003c/li\u003e\n\u003cli\u003eGalperin MY, Makarova KS, Wolf YI, Koonin EV: \u003cstrong\u003eExpanded microbial genome coverage and improved protein family annotation in the COG database\u003c/strong\u003e. \u003cem\u003eNucleic Acids Res \u003c/em\u003e2015, \u003cstrong\u003e43\u003c/strong\u003e(Database issue):D261-D269.\u003c/li\u003e\n\u003cli\u003eUrban M, Pant R, Raghunath A, Irvine AG, Pedro H, Hammond-Kosack KE: \u003cstrong\u003eThe Pathogen-Host Interactions database (PHI-base): additions and future developments\u003c/strong\u003e. \u003cem\u003eNucleic Acids Res \u003c/em\u003e2015, \u003cstrong\u003e43\u003c/strong\u003e(Database issue):D645-D655.\u003c/li\u003e\n\u003cli\u003eChen L, Xiong Z, Sun L, Yang J, Jin Q: \u003cstrong\u003eVFDB 2012 update: toward the genetic diversity and molecular evolution of bacterial virulence factors\u003c/strong\u003e. \u003cem\u003eNucleic Acids Res \u003c/em\u003e2012, \u003cstrong\u003e40\u003c/strong\u003e(Database issue):D641-D645.\u003c/li\u003e\n\u003cli\u003eXu X, Huang L, Su Y, Yan Q: \u003cstrong\u003eThe complete genome sequence of Vibrio aestuarianus W-40 reveals virulence factor genes\u003c/strong\u003e. \u003cem\u003eMicrobiologyopen \u003c/em\u003e2018, \u003cstrong\u003e7\u003c/strong\u003e(3):e00568.\u003c/li\u003e\n\u003cli\u003eKern J, Schneewind OJMm: \u003cstrong\u003eBslA, the S‐layer adhesin of B. anthracis, is a virulence factor for anthrax pathogenesis\u003c/strong\u003e. \u003cem\u003eMol Microbiol\u003c/em\u003e 2010, \u003cstrong\u003e75\u003c/strong\u003e(2):324-332.\u003c/li\u003e\n\u003cli\u003eRoy S, Zhu Y, Ma J, Roy AC, Zhang Y, Zhong X, Pan Z, Yao H: \u003cstrong\u003eRole of ClpX and ClpP in Streptococcus suis serotype 2 stress tolerance and virulence\u003c/strong\u003e. \u003cem\u003eMicrobiol Res \u003c/em\u003e2019, \u003cstrong\u003e223-225\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eTaylor CM, Roberts ISJCibv: \u003cstrong\u003eCapsular polysaccharides and their role in virulence\u003c/strong\u003e. \u003cem\u003eNephron\u003c/em\u003e 2005, \u003cstrong\u003e12\u003c/strong\u003e:55-66.\u003c/li\u003e\n\u003cli\u003eXu S, Xie X, Zhao Y, Shi Y, Chai A, Li L, Li B: \u003cstrong\u003eWhole-genome analysis of bacillus velezensis ZF2, a biocontrol agent that protects cucumis sativus against corynespora leaf spot diseases\u003c/strong\u003e. \u003cem\u003e3 Biotech \u003c/em\u003e2020, \u003cstrong\u003e10\u003c/strong\u003e(4):186.\u003c/li\u003e\n\u003cli\u003eNifakos K, Tsalgatidou PC, Thomloudi E-E, Skagia A, Kotopoulis D, Baira E, Delis C, Papadimitriou K, Markellou E, Venieraki A\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGenomic Analysis and Secondary Metabolites Production of the Endophytic Bacillus velezensis Bvel1: A Biocontrol Agent against Botrytis cinerea Causing Bunch Rot in Post-Harvest Table Grapes\u003c/strong\u003e. \u003cem\u003ePlants (Basel) \u003c/em\u003e2021, \u003cstrong\u003e10\u003c/strong\u003e(8).\u003c/li\u003e\n\u003cli\u003eZaid DS, Cai S, Hu C, Li Z, Li Y: \u003cstrong\u003eComparative Genome Analysis Reveals Phylogenetic Identity of Bacillus velezensis HNA3 and Genomic Insights into Its Plant Growth Promotion and Biocontrol Effects\u003c/strong\u003e. \u003cem\u003eMicrobiol Spectr \u003c/em\u003e2022, \u003cstrong\u003e10\u003c/strong\u003e(1):e0216921.\u003c/li\u003e\n\u003cli\u003eMei J, Shen X, Gang L, Xu H, Wu F, Sheng L: \u003cstrong\u003eA novel lignin degradation bacteria-Bacillus amyloliquefaciens SL-7 used to degrade straw lignin efficiently\u003c/strong\u003e. \u003cem\u003eBioresour Technol \u003c/em\u003e2020, \u003cstrong\u003e310\u003c/strong\u003e:123445.\u003c/li\u003e\n\u003cli\u003eMalik WA, Javed S: \u003cstrong\u003eBiochemical Characterization of Cellulase From Bacillus subtilis Strain and its Effect on Digestibility and Structural Modifications of Lignocellulose Rich Biomass\u003c/strong\u003e. \u003cem\u003eFront Bioeng Biotechnol \u003c/em\u003e2021, \u003cstrong\u003e9\u003c/strong\u003e:800265.\u003c/li\u003e\n\u003cli\u003eZhang T, Wei S, Liu Y, Cheng C, Ma J, Yue L, Gao Y, Cheng Y, Ren Y, Su S\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eScreening and genome-wide analysis of lignocellulose-degrading bacteria from humic soil\u003c/strong\u003e. \u003cem\u003eFront Microbiol \u003c/em\u003e2023, \u003cstrong\u003e14\u003c/strong\u003e:1167293.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bacillus velezensis, Gene annotation, Gene function prediction, Whole genome, Whole genome sequencing","lastPublishedDoi":"10.21203/rs.3.rs-4254829/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4254829/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eBacillus velezensis\u003c/em\u003e\u003cstrong\u003e, \u003c/strong\u003ea member of phylum firmicutes, is a gram-positive rod-shaped and endospore-forming bacterium inhabiting diverse environments. The preliminary analysis of the whole genome of \u003cem\u003eBacillus velezensis ANY11\u003c/em\u003e, isolated from bamboo fiber humus in the intestines of \u003cem\u003eCyrtotrachelus buqueti\u003c/em\u003e, revealed that the genome is approximately 3,949,880 bp in length and contains 4265 coding genes. Among these, 12815, 2473, 3193, and 171 genes were annotated in the GO, KEGG, COG, and CAZy databases, respectively. Additionally, the virulence, pathogenicity, and antibiotic resistance of \u003cem\u003eBacillus velezensis ANY11 \u003c/em\u003ewere analyzed using PHI, VFDB, and CARD databases. Based on the genomic sequencing and gene function analysis, \u003cem\u003eBacillus velezensis\u003c/em\u003eis believed to possesses certain disease resistance and the capability to hydrolyze lignocellulose, predicting its potential role in plant disease prevention and control as well as in the hydrolysis and reuse of lignocellulose lays The bioinformatics from this study may lay a foundation for the production of biofertilizers and biopesticides, as well as for the utilization of biomass in the production of clean energy ethanol.\u003c/p\u003e","manuscriptTitle":"Complete Genome Sequencing and Functional Prediction of Bacillus velezensis ANY11","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-24 16:55:23","doi":"10.21203/rs.3.rs-4254829/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4b88c25a-f319-4772-928f-d6cf8657efef","owner":[],"postedDate":"May 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-02T10:51:55+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-24 16:55:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4254829","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4254829","identity":"rs-4254829","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}