The complete genome sequences of Bacillus velezensis B26: a promising biocontrol agent and biofertilizer

Whole genome analysis of bacteria

The genome of B. velezensis B26 strain was analysed to explore its microbial genomic characteristics. HiMedia Laboratories Pvt Ltd, Maharashtra, INDIA performed the whole-genome analysis.

Sample preparation workflow

Genomic DNA (gDNA) from B. velezensis B26 was isolated using DNA Mini Kit (Qiagen). The integrity of the gDNA was assessed spectrophotometrically to measure the A260/280 ratio and its concentration. For library preparation, 250ng of DNA was processed with the QIASeq FX DNA Kit (Qiagen), following manufacturer’s protocol to generate fragmented, adapter-ligated and indexed libraries. The Illumina NextSeq 550 with 300-cycle paired-end sequencing chemistry was employed for sequencing the finalized library.

Tapestation analysis of NGS libraries

For fragment analysis, 2 μL of high-sensitivity D1000 sample buffer and 2 μL of the final library sample were mixed using vortexer for 1 min. The mixture was then loaded onto the D1000 ScreenTape and analyzed using the Agilent 4200 TapeStation System. This system employs DNA electrophoresis to separate fragments up to 1000 base pairs. The trace analysis revealed an average fragment size of 301 base pairs, which, along with the library concentration, indicates the library’s suitability for next-generation sequencing.

Analysis workflow

In data analysis all reads are checked for quality and then the quality control (QC’)-quality reads are passed through the process flows simultaneously. The detailed steps involved in each process flow are included within each section below.

Reads quality control

Briefly, raw fastq files were verified using FastQc v0.11.9.8 The details of parameters checked are added in a MultiQC report (Ewels et al. 2016) (Supplementary file 1). The fastp tool (v0.12.4) was utilized to remove adapter contamination from the sequencing data (Chen et al. 2018). A quality score of Q30 or higher indicates a basecall accuracy of 99.9%, meaning that only 1 in 1000 bases is likely to be incorrect. The resulting files for each read were subjected for genome assembly.

Genome assembly and annotations

A denovo assembly using a De-Brujin graph was performed to organize the short DNA reads into longer contiguous sequences, referred to as contigs. These contigs served as a starting material used for performing a genome annotation, facilitating the assignment of functional roles to various genomic regions of the organism under investigation.

The quality of the genome assemblies produced by the Spades (Bankevich et al. 2012) and Megahit (Li et al. 2015) assemblers was evaluated using the Quast tool (Gurevich et al. 2013). Compared with the megahit assembler, the Spades assembler had longer assembled contigs with better N50 values. Hence, the assembly generated by Spades was selected for further downstream analyses.

RAST Server: Rapid annotations using subsystems technology

The RAST server is an automated platform developed for the bacterial genome annotation. It detects protein-coding regions, along with genes coding for ribosomal and transfer RNAs, allots functional roles to these elements (Aziz et al. 2008). Additionally, it allows comparative analysis through the SEED environment (Overbeek et al. 2014). The RAST server remains a viable tool for efficient and reliable genome annotation.

Whole-genome analysis of B. velezensis B26

We performed a genome analysis of B. velezensis B26 to understand the biochemical potential of the organism. Figure. 1 depicts the sample preparation and sequencing workflow. Importantly, the assembled genomes may not be 100% complete. However, the assembly generated here meets the standards acceptable to general bioinformatics repositories as part of the data gathered for a publication. These whole-genome shotgun data have been provided with the accession number JAYKOV000000000 (NCBI database). The master record data is available from our various Entrez servers. The individual sequences are available from a hyperlink at the bottom of the WGS master record JAYKOV000000000.

Figure 1. Sample preparation and sequencing workflow.

The genome assembly method employed was Megahit v. 2023-07-12 tool, the genome representation was full, the genome coverage was 100.0x and the sequencing technology employed was Illumina. Genome annotation was carried out using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) (Haft et al. 2018; Li et al. 2021). The annotation results are summarized in Table 1, which provides an overview of the genome features and information. Table 2 summarizes key assembly statistics, including the number of contigs, total length of the sequenced genome, and the number of proteins annotated.

Identification of subsystem features by The RAST Server: Rapid Annotations using Subsystems Technology (RAST)

In addition to utilizing the NCBI PGAP, we also submitted the sequenced genome data of B. velezensis B26 to the RAST server. This service provides fully automated annotation for bacterial genomes. Using the RAST annotation platform, we recognized genes coding for proteins, ribosomal and transfer RNAs, assigned functional roles to these genes, and predicted the subsystems present in the B. velezensis B26 genome (Supplementary Table 1). Furthermore, the annotated genome is presented on a platform that allows for comparative analysis in the SEED environment ( Figure 2).

Figure 2. Subsystem statistics of the B. velezensis B26 genome annotations.

The genome of B. velezensis B26 was annotated using the RAST server, and the features in subsystem are compared within the SEED environment. The figure highlights key subsystems identified in the genome, including genes associated with carbohydrate metabolism, stress response, virulence, disease and defense, as well as genes involved in metabolism.

Our analysis revealed the presence of 216 genes involved in carbohydrate metabolism, 3 genes related to phages, prophages, transposable elements, and plasmids, 43 genes for stress response, and 35 genes linked to virulence, disease and defense. The genes related to the stress response and virulence might be responsible for the biocontrol properties of B. velezensis B26 (Supplementary Table 2).

Additionally, several genes involved in metabolic processes were identified, including 59 genes related to DNA metabolism, 10 related to phosphorus metabolism, 20 related to nitrogen metabolism, 6 related to sulfur metabolism, 12 related to metabolism of aromatic compounds, 3 related to potassium metabolism, 10 related to phosphorus metabolism, and 24 related to acquisition and metabolism. These metabolic pathways suggest potential biofertilizer activity (Supplementary Table 2).

B. velezensis B26 pangenome analysis

Pangenome analysis provides valuable understandings into the genome of prokaryotes. Using Roary software, a large-scale pangenomes are constructed by identifying both core and accessory genes. This method aids in understanding the conserved genes within an organism, as well as accessory genome, to understand the fundamentals linked with natural selection and evolutionary dynamics.

Pangenome analysis of B. velezensis B26 identified a total of 5,576 genes. Among these genes, 3,480 genes were considered core genes and were found in 99% to 100% of strains. A total of 1, 143 genes were classified as shell genes, which were present in 15% to 95% of strains, whereas 953 genes were identified as cloud genes, which were found in fewer than 15% of strains ( Table 3). These analyses indicate that the major portion of the genome is conserved across species.