A rapid method for species-level identification of Bacillus subtilis group strains via multiplex pan-genome-based PCR

A rapid method for species-level identification of Bacillus subtilis group strains via multiplex pan-genome-based PCR | 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 A rapid method for species-level identification of Bacillus subtilis group strains via multiplex pan-genome-based PCR Yuxiang Zhai, Jiayu Wen, Taiquan Wang, Dexin Bo, Fangkui Wang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7088511/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 The various species within the Bacillus subtilis group possess significant economic and practical value, but exhibit distinct functions and have divergent applications. Thus, there is an urgent need for a rapid, efficient, and cost-effective method to accurately distinguish species and their strains within the B. subtilis group, to enable bacterial resources to be precisely screened and classified. Here, we developed a comparative genomics-based multiplex PCR method for the species-level identification of B. subtilis group strains to facilitate the accumulation of B. subtilis group microbial resources. We constructed a pan-genome from 753 genomes spanning 12 species within the B. subtilis group, and used it to identify six marker genes that together could distinguish among the species: araE , ykqA , yicL , corC , gtaB , and gdpP . Specific primers for these marker genes were designed to generate distinct PCR product profiles that enabled species-level identification of strains. This method was used to successfully identify 21 B. subtilis group strains from a collection of 23 bacterial isolates obtained from soil, yielding an accuracy rate of 91.30%. Our results demonstrate the feasibility and reliability of this multiplex PCR approach, which could provide an efficient and accurate tool for screening and classifying B. subtilis group strains from soil microbial communities, and thereby support their exploration and utilization in various applications. Bacillus subtilis group Marker genes Multiplex PCR Identification Pan-genome Soil microorganism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Key Points This is frst study to mine novel targets for diferentiating Bacillus subtilis group species. This study developed a multiplex PCR method for identifying species of Bacillus subtilis group, achieving DNA free extraction and without the need for sequencing The PCR method efectively detected Bacillus subtilis group species in soil. Introduction The genus Bacillus encompasses a diverse range of species that are commonly divided into two clades based on phylogenetic analysis: the Bacillus subtilis group and the Bacillus cereus group (Bhandari et al. 2013 ). Members of the B. subtilis group typically share common characteristics, including rod-shaped morphology, aerobic or facultatively anaerobic metabolism, Gram-positive cell walls, and the ability to produce endospores (Khurana et al. 2020 ). The term " B. subtilis group" is not a formally defined taxonomic unit; rather, it encompasses species closely related to or newly derived from B. subtilis , B. licheniformis , and B. amyloliquefaciens (Priest et al. 1987 ). The group includes species such as B. subtilis , B. licheniformis , B. amyloliquefaciens , B. velezensis , B. siamensis , B. atrophaeus , B. vallismortis , B. mojavensis , B. sonorensis , B. spizizenii , B. inaquosorum , and B. stercoris (Priest et al. 1987 ; Fan et al. 2017 ; Harwood et al. 2018 ; Caulier et al. 2019 ). These species are widely utilized across various fields to produce a diverse array of industrially valuable compounds and products, such as enzymes, peptide antibiotics, surfactants, biofertilizers, chemicals, pharmaceuticals, and nutritional supplements (Gu et al. 2018 ; Park et al. 2021 ). The B. subtilis group species are well recognized for their significant economic and practical value, with reports estimating a market value of $ 18 billion in 2020 and a projected annual growth rate of approximately 8.7% from 2020 to 2024 (Herrmann et al. 2024 ). Therefore, it is essential to rapidly and efficiently collect many strains of these species from the natural environment in order to accumulate resources for product development. Furthermore, members of the B. subtilis group exhibit diverse functionalities and distinct application potentials. For instance: B. subtilis KU106 is utilized in the production of scyllo-inositol for Alzheimer's disease research (Halmschlag et al. 2020 ); and the secondary metabolite of B. licheniformis , lichenysin, has high surface activity, hemolytic activity, and antibacterial activity (Nerurkar 2010 ). Once B. subtilis group strains are acquired, it is important to perform efficient species-level identification to facilitate targeted development based on species-specific characteristics. The primary methods currently used to identify species of the B. subtilis group include phenotyping, 16S rRNA gene sequencing, and whole-genome sequencing (Gupta et al. 2020 ; Camacho et al. 2022 ; Amoah et al. 2024 ). Historically, identification relied predominantly on the analysis of phenotypic features, including physiological, morphological, and biochemical characteristics. However, this approach offers limited resolution (Bhandari et al. 2013 ). Advances in sequencing technologies, 16S rRNA gene sequencing and whole-genome sequencing have led to the widespread adoption of such techniques for species identification. These methods provide high resolution to capture the intrinsic characteristics that distinguish species. Nevertheless, the high cost of sequencing remains a significant barrier for large-scale bacterial species identification. Additionally, sequencing processes are time- and resource-intensive, especially for numerous samples. PCR technology can also be applied for bacterial species identification (Cousin et al. 2019 ; Wang et al. 2020 ; You and Kim 2020 ). This relatively fast, cost-effective, sensitive, specific, and versatile approach provides high resolution while reducing costs and saving time relative to sequencing-based methods, making it suitable for detecting and quantifying bacterial species in complex matrices. Most of the existing PCR-based identification methods rely on 16S rRNA and housekeeping gene sequences, which are ubiquitous, contain variable and highly conserved regions, and are widely available for many strains in public databases (Gómez-Rojo et al. 2015 ). However, the high sequence similarity of these genes often limits their ability to distinguish among closely related species or subspecies (Johnson et al. 2019 ). To address this limitation, researchers have turned their focus toward identifying specific marker genes. Recently, a real-time PCR assay was developed using specific genes to identify several Weissella species (Kim et al. 2022 ). Despite the promising potential of PCR technology, however, no study to date has used this strategy to identify species within the B. subtilis group. Here, we used pan-genome analysis of B. subtilis group strains to identify characteristic genes that are specific to the species of this group, and together form a profile that can be used for the species-level identification of B. subtilis group strains. From these genes, we designed multiple pairs of species-specific primers that produce PCR products of varying lengths and developed a multiplex colony PCR method that, upon resolution of products by gel electrophoresis, yielded species-specific profiles that could be used to identify B. subtilis group strains collected from the environment. This approach can facilitate the identification of B. subtilis group strains from large collections of Bacillus isolates, and thereby support the accumulation of potentially valuable strain resources. Materials and methods Identification of marker genes by pan-genomic analysis We downloaded 753 complete genomes of B. subtilis group strains and 383 complete genomes of outgroup strains (of B. cereus , B. thuringiensis , B. anthracis , B. mycoides , and B. wiedmannii ) from the NCBI RefSeq database (Supplemental Table S1 ). The genomes were filtered using CheckM v1.2.1 with the criteria of genome completeness ≥ 90% and contamination ≤ 5%. Species annotation was performed using GTDB-TK v2.3.2 with default parameters, and genomes with evident annotation errors were excluded. Ultimately, 753 high-quality genomes of the B. subtilis group and 383 high-quality genomes of the outgroup were obtained (Supplemental Table S1 ). Subsequently, the pan-genome for each B. subtilis group species was constructed using Roary v3.13.0. Roary v3.13.0 was used to construct a gene presence/absence matrix from these 1,136 genomes. Genes specific to B. subtilis group species were identified using Scoary v1.6.16. Genes were filtered using the criteria: Sensitivity ≥ 90%, Specificity = 100%​, ​Odds Ratio ≥ 10, and ​Bonferroni_p ≤ 0.05.​ Genes annotated as encoding hypothetical proteins were excluded. To further exclude genes that are evolutionarily conserved within B. subtilis group species, candidate markers were further processed through a two-tier filtering approach, as follows: Genes annotated as showing > 90% identity to ribosomal proteins (COG J), RNA/DNA polymerases (COG K/L), or core metabolic enzymes (COG C/E/G) were removed. Finally, to facilitate primer design, we removed genes shorter than 600 bp. After screening, we obtained 25 candidate genes. From among the remaining candidate genes, we randomly selected six genes for primer design. Primer design For the six selected genes, we used Primer-BLAST to design primers that would generate PCR products of different lengths for each target species. The length difference of products from different primers is greater than 30bp, with Primer melting temperatures (Tm) ranging from 55 ℃ to 65 ℃, and default parameters used for others. This process ultimately yielded 12 primer pairs. The primers used in this study are listed in Table 1 and were synthesized by AuGCT Biotech (Beijing, China). Table 1 Specific primers designed in this study Gene Primer sequence Product length Number F (5' − 3') R (5' − 3') araE ACGCTTCTGTTGTTTTGCCC CCTCGGGATTGGGATGGGAT 299 1 CCCACAGGAATATCGTCGCA TGCTTATCGTGCCGGAAAGT 609 2 GCTCTCGCCCGAAGATGATT TATGATTGGAGGAGTGGCGG 984 3 GTGACAAACCCCGCATTCTG AGAATCACCCGGCACCAATT 913 4 ykqA TCCTTTTTCAGCTGTCGCCT GCTGAGGAGGTGCTGTTTCT 158 5 TGCCCACAGCTGTTTTCAATG TCCGCTCTTGAACCGTCTTC 406 6 GCTTTGATGAGACACACGAGC CTCGTCACTTTCGGCACAAG 679 7 yicL GCCCAGTATCTGTTCCAGCA AGGACCACTCGCCTTCAAAT 574 8 corC CGCTTGAACAAATGGCCGAA TGAAGCCGTCCTGATGCATT 497 9 GATGTCCCGCCGTACTCATC TGCTGCATCCGGTCTTTGAA 730 10 gdpP CAAATGTACGCGAGCCAGTG TGGAAGAGCGACTGGTCAAC 255 11 gtaB ACGCATGATTTGAGGGGTGA GAGACCGAACAAGCTGGGAA 449 12 Table 2 ​ Comparative results of multiplex PCR genotyping versus whole-genome sequencing for strains from soil Strains Multiplex PCR Whole-genome sequencing 1 B. licheniformis B. licheniformis 2 B. velezensis B. velezensis 3 B. licheniformis B. licheniformis 4 B. licheniformis B. licheniformis 5 B. velezensis B. velezensis 6 B. velezensis B. velezensis 7 B. velezensis B. licheniformis 8 B. licheniformis B. licheniformis 9 B. licheniformis B. licheniformis 10 B. licheniformis B. licheniformis 11 B. licheniformis B. licheniformis 12 B. licheniformis B. licheniformis 13 B. licheniformis B. licheniformis 14 B. licheniformis B. licheniformis 15 B. velezensis B. velezensis 16 B. licheniformis B. licheniformis 17 B. licheniformis B. licheniformis 18 B. licheniformis B. licheniformis 19 B. licheniformis B. licheniformis 20 B. licheniformis B. licheniformis 21 B. licheniformis B. licheniformis 22 B. licheniformis B. licheniformis 23 B. velezensis B. licheniformis Bacterial strains and DNA extraction The strains used in this study were as follows: B. subtilis , B. amyloliquefaciens , B. licheniformis , B. velezensis , B. thuringiensis , B. inaquosorum , B. spizizenii , B. stercoris , B. siamensis , B. atrophaeus , B. vallismortis , B. mojavensis , B. sonorensis , and their detailed information were listed in Supplemental Table S2. All strains were cultured in Luria-Bertani (LB) medium at 38°C for 24 hours and then preserved in 25% (v/v) glycerol solution at -80°C. Before DNA extraction, all strains were cultured in LB medium at 38°C for 24 hours. Genomic DNA was extracted using a bacterial DNA extraction kit (Magen Biotechnology, Guangzhou, China), and the purity and concentration of the extracted genomic DNA were determined using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, USA). Multiplex PCR assay Firstly, we used the above-described DNA the 13 bacterial strains (Supplemental Table S2) to experimentally verify the designed primers. The multiplex PCR reaction system included 10 ng of DNA, 100 nM of each primer, 10 µL of 2 × Taq Master Mix (Vazyme BioTech, Nanjing, China), and distilled water to a final reaction volume of 20 µL. The PCR amplification cycle consisted of an initial denaturation step at 98°C for 10 minutes, followed by 30 cycles of denaturation at 95°C for 30 seconds, annealing at 60°C for 30 seconds, and extension at 72°C for 90 seconds. A final extension step was performed at 72°C for 10 minutes. After the reaction, agarose gel electrophoresis was performed to ensure that the bands reflected strain differences and there was no evidence of band loss. ​After PCR completion, 3 µL of PCR product was loaded into wells of a 1.5% agarose gel. Electrophoresis was performed at 130 V for 30 minutes, and the bands were visualized under UV light. To optimize the multiplex PCR reaction conditions, we used DNA from the 12 bacterial strains as templates, and tested annealing temperatures of 55°C, 56°C, 57°C, 58°C, 59°C, 60°C, 61°C, 62°C, 63°C, 64°C, and 65°C. The optimal annealing temperature was selected based on the results: the bands are displayed in each strain, and the combination of bands for each strain is different. To increase the future feasibility of using our method for large-scale bacterial identification, we sought to omit the DNA extraction step and use bacterial suspensions directly as templates for colony PCR. The optimal bacterial cell lysis conditions and detection sensitivity were investigated. Three bacterial cell lysis conditions were tested: ultrasonic treatment at 40 kHz, 120 W for 15 minutes; ultrasonic treatment at 40 kHz, 120 W for 30 minutes; and ultrasonic treatment at 40 kHz, 120 W for 30 minutes followed by immersion in a 90°C water bath for 10 minutes. PCR amplification was then performed using the reaction system and optimized temperature conditions, and the optimal bacterial lysis condition was determined based on the results: the band distribution that appears is the same as that of PCR using DNA. Finally, the sensitivity of the multiplex PCR was evaluated. Bacterial suspensions were diluted with ddH2O to 2.28×10 9 CFU/mL, 2.28×10 8 CFU/mL, 1.14×10 8 CFU/mL, 1.14×10 7 CFU/mL, 1.14×10 6 CFU/mL, and 1.14×10 5 CFU/mL. Using the optimized bacterial lysis and PCR conditions, the sensitivity of the multiplex PCR was assessed for each concentration. Select the minimum concentration with the same band distribution as when using DNA for PCR. Application of the developed multiplex PCR method ​​ To verify the practicality of the primers, we selected a dried soil sample collected from Wenshan, Yunnan. 1g of soil was placed in 20ml LB liquid medium for activation for 4 hours, and then the medium was incubated at 80 ℃ for 30 minutes. Then, 50 µl of the suspension was coated on LB solid medium and incubated at 28 ℃ for 24 hours. After that, 23 strains of bacteria were selected from the medium with a morphology resembling B. subtilis group strains. Then incubate in LB liquid medium at 38 ℃ for 48 hours. Use our designed primers to identify these 23 bacterial strains. Thereafter, genomic DNA was extracted from each strain using a bacterial DNA extraction kit (Magen Biotechnology, Guangzhou, China). Whole-genome sequencing was conducted on the DNBSEQ-T7 PE150 platform (MGI Tech, Shenzhen, China). Raw sequencing data were assembled into draft genomes using SPAdes v3.15.5, and taxonomic annotation was performed with GTDB-Tk v2.3.2 under default parameters. Results Pan-genomic analysis of B. subtilis group strains Genomic data for the B. subtilis group and outgroup ( B. cereus , B. thuringiensis , B. anthracis , B. mycoides , and B. wiedmannii ) strains used in this study were obtained from the NCBI RefSeq database. Quality control was performed on the collected genomic data using CheckM, and GTDB-TK was used to correct potential misclassifications in species annotations from the NCBI database. Ultimately, 753 high-quality genome datasets of B. subtilis group strains and 383 high-quality genome datasets of outgroup strains were obtained (Supplemental Table S1 ). Through comparative genomic analysis, we identified the core, accessory, and rare genes of the B. subtilis group members (Fig. 1 A). To search for group-specific genes, we used Roary v3.13.0 to construct a gene presence/absence matrix from these 1,136 genomes. We used Scoary v1.6.16 to filter for unique genes that were completely absent in the outgroup (Specificity = 100%) but present in over 90% of the B. subtilis group genomes (Sensitivity ≥ 90%). This yielded a total of 227 genes (Bonferroni_p ≤ 0.05). After we filtered genes for those with short sequence lengths, those annotated as hypothetical proteins, and those highly conserved across B. subtilis group species, we obtained 25 candidate genes (Supplemental Table S3). From them, we randomly selected six genes existing only in B. subtilis group strains (Fig. 1 B) for subsequent validation. The selected genes were: the arabinose-proton symporter-encoding gene, araE ; the gamma-glutamylcyclotransferase-encoding gene, ykqA ; the EamA family inner membrane transporter-encoding gene, yicL ; the CNNM family magnesium/cobalt transport protein-encoding gene, corC ; the UTP-glucose-1-phosphate uridylyltransferase-encoding gene, gtaB ; and the cyclic-di-AMP phosphodiesterase-encoding gene, gdpP . Specificity and sensitivity of primers The primers used in this study are shown in Table 1 . PCR amplification was performed using template DNA extracted from 12 B. subtilis group strains and one Bacillus thuringiensis strain, and the generated products were resolved by gel electrophoresis. As shown in Fig. 2 , the developed primers did not amplify any band in B. thuringiensis , whereas all strains of the B. subtilis group showed amplification products. Analysis of the combined profiles generated using all six marker genes enabled us to effectively differentiate among these closely related species. Our results suggest that the 12 sets of primers generated herein can be used to effectively identify B. subtilis group strains and identify species within the B. subtilis group. Next, we further optimized the multiplex PCR conditions. Using DNA extracted from the 12 B. subtilis group strains as templates, we tested PCR amplification with 11 different annealing temperatures ranging from 55°C to 65°C. As shown in Fig. 3 , the use of an annealing temperature below 60°C resulted in the generation of non-specific bands and did not allow us to distinguish between different strains, whereas the use of an annealing temperature above 60°C was associated with the loss of some bands. Thus, the optimal annealing temperature was determined to be 60°C. To better accommodate future large-scale bacterial identification using the developed method, we wanted to omit the DNA extraction step and use bacterial suspensions directly as templates for colony PCR. To this end, we investigated the optimal bacterial cell lysis conditions and the detection sensitivity of the adjusted protocol. To explore the best bacterial cell lysis condition, 1-µL aliquots of bacterial suspension (2.28×10 9 CFU/mL) were mixed with 6.4 µL ddH 2 O in PCR tubes, and the tubes were subjected to 40 kHz, 120 W ultrasonic lysis for 15 minutes, for 30 minutes, or for 30 minutes followed by immersion in a 90°C water bath for 10 minutes. The lysates were amplified using the optimized PCR conditions. As shown in Fig. 4 , ultrasonic lysis at 40 kHz and 120 W for 15 or 30 minutes resulted in lower amplification efficiency, the presence of non-specific bands, and missing bands, suggesting that these lysis conditions did not completely release the DNA from the bacteria. Ultrasonic lysis at 40 kHz and 120 W for 30 minutes followed by immersion in a 90°C water bath for 10 minutes yielded the same band as when using DNA for PCR, indicating that this lysis procedure successfully released the bacterial DNA for amplification. Finally, we tested the sensitivity of the multiplex PCR assay. Bacterial suspensions of the 12 strains were serially diluted to 2.28×10 9 CFU/mL, 2.28×10 8 CFU/mL, 1.14×10 8 CFU/mL, 1.14×10 7 CFU/mL, 1.14×10 6 CFU/mL, and 1.14×10 5 CFU/mL, and sensitivity tests were performed. As shown in Fig. 4 , when the bacterial concentration was 1.14×10 8 CFU/mL or higher, bands of the expected fragment sizes were successfully amplified. At lower concentrations, the amplification efficiency decreased due to there being an insufficient amount of template, resulting in non-specific and missing bands. These results indicate that the multiplex PCR assay has a sensitivity of 1.14×10 8 CFU/mL. The final optimized multiplex PCR procedure was as follows: One microliter of bacterial suspension (concentration ≥ 1.14×10 8 CFU/mL) was mixed with 6.6 µL ddH2O, ultrasonicated for 30 minutes at 40 kHz, 120 W, and immersed in a 90°C water bath for 10 minutes. Then, 0.2 µL of each of the 12 primer pairs (0.1 µL for each forward and reverse primer, concentration 100 µM) and 10 µL of 2 × Taq Master Mix were added to the reaction volume. Finally, ddH 2 O was added to a final reaction volume of 20 µl. The thermocycling program consisted of an initial denaturation step at 98°C for 10 minutes, followed by 30 cycles of denaturation at 95°C for 30 seconds, annealing at 60°C for 30 seconds, and extension at 72°C for 90 seconds. A final extension step was performed at 72°C for 10 minutes. Then, 1.5% agarose gel was used for electrophoresis at 130v for 30min, and the distribution of bands was observed under ultraviolet light. Identification of B. subtilis group strains from soil-derived isolates Application of the aforementioned multiplex PCR workflow to 23 soil-derived isolates yielded 22 presumptive B. subtilis group members, including six strains of B. velezensis and 17 strains of B. licheniformis (Fig. 5 ). Whole-genome sequencing followed by GTDB-Tk-based taxonomic assignment (v2.3.2, default parameters) revealed two discordant classifications: Isolates 7 and 23, which were initially identified as B. velezensis by PCR, were reclassified as B. licheniformis (Table. 2). Thus, our multiplex PCR demonstrated 91.30% concordance (21/23) with genomic taxonomy at the species level. Discussion Many B. subtilis group strains are widely utilized in the production of enzymes, vitamins, antibiotics, amino acids and their derivatives, pharmaceuticals, and health products (Muras et al. 2021; Luo et al. 2023). The significant economic and practical value of such strains has been widely recognized, and there is growing interest in the development of novel Bacillus subtilis group strains or related products. In the development and utilization of microbial resources, microbial strain resource libraries serve as a critical source of diverse microbial strains, forming the foundation for discovering and developing novel microbial functions or products (Janssens et al. 2010 ; Heylen et al. 2012 ). However, it is labor-intensive and time-consuming to build a strain library enriched with microorganisms possessing specific target traits. This typically involves collecting samples from various environments, such as soil, water, plants, and animals, and using a series of screening steps to identify strains with desired activities or functions (Prakash et al. 2013 ). Therefore, it would be very useful to have a method capable of rapidly identifying and classifying B. subtilis group strains from a vast array of environmental microorganisms. Given the diverse properties of these strains, it is also essential to accurately differentiate among species within this group. Here, we developed a sensitive, rapid, and specific detection method based on marker genes for B. subtilis group species. This approach facilitates the identification and species-level classification of strains within the group. The multiplex PCR method developed in this study enables the detection of 12 target species within the B. subtilis group directly through PCR amplification, does not require sequencing to determine the species. This assay utilizes bacterial colonies directly as template DNA, significantly reducing both processing time and associated costs. Designed for diverse industrial settings, the method streamlines detection workflows to shorten turnaround times and offers a highly cost-effective solution for species differentiation. The selection of target genes and the development of specific primers are among the most critical factors in the generation of successful PCR-based methods for identifying bacteria (Gómez-Rojo et al. 2015 ). In previous studies, the 16S rRNA gene was commonly used as the target gene for species differentiation. However, this approach has certain limitations (Yu et al. 2015 ; Gómez-Rojo et al. 2015 ). The 16S rRNA gene often exhibits high sequence similarity, making it inadequate for distinguishing closely related species or subspecies. Within the Bacillus subtilis group, the 16S rRNA gene shows particularly high similarity among species, with reported sequence identities ranging from 98.1–99.8% (Wang et al. 2007 ). Therefore, there is a need to identify novel marker genes to replace the 16S rRNA gene and enhance the resolution of PCR-based identification methods for B. subtilis group species. Previous studies demonstrated that marker genes identified through pan-genomic analysis can effectively differentiate closely related species, such as lactic acid bacteria and Weissella (You and Kim 2020 ; Kim et al. 2022 ). Following this approach, we conducted a pan-genomic analysis of genomic data from 753 B. subtilis group strains. We identified six B. subtilis group-specific marker genes: araE , ykqA , yicL , corC , gtaB , and gdpP . During primer design, we developed species-specific primer sets for these 12 bacterial species, each yielding PCR amplicons of distinct lengths. We assessed the specificity of the PCR products using the default parameters in Primer-BLAST, with the initial hope that each primer set would generate a unique band for its target species. However, due to the high genetic similarity among these species, some of our designed primers exhibited limited specificity against individual species. For instance, primer pair #6 amplified products across five different species. Nevertheless, we observed that even with this limited specificity of individual primer sets, the resulting banding patterns were unique to each of the 12 species. This distinct combination of amplified bands for each species allows reliable differentiation between them, achieving the intended goal of species identification.​ PCR is cost-effective, relatively simple, and easy to use, and has been successfully applied for the species-level identification of lactic acid bacteria and Weissella (You and Kim 2020 ; Kim et al. 2022 ). In this study, we developed a PCR-based method for identifying B. subtilis group strains. By designing specific primers, we ensured that amplification occurred exclusively with B. subtilis group strains. Species-level identification was achieved by analyzing the unique band patterns formed by PCR products of different lengths following gel electrophoresis. We further optimized the method for large-scale use by developing it into a colony PCR technique, which eliminates the need for bacterial DNA extraction and thus streamlines the process. We applied this multiplex PCR method to identify 23 bacterial strains previously isolated from soil, and successfully classified 22 strains as belonging to the B. subtilis group. Comparison between PCR-based identification and whole-genome sequencing with GTDB-Tk annotation revealed misclassification of two strains, for an accuracy rate of 91.30%. This demonstrates that the PCR method established in this study is fully applicable for screening B. subtilis group strains in soil samples. In the two misidentified strains, the PCR products showed faint band intensities with uneven brightness between the two target bands, leading to interpretation errors. In summary, our newly developed PCR-based method provides a rapid, convenient, and efficient means for identifying B. subtilis group strains from soil samples. This method could provide technical support for the accumulation, development, and utilization of B. subtilis -group microbial resources. Declarations Author contribution J.Z. andY.Z. conceived the project. J.Z. administrated the project and acquired the funding. Y.Z. designed the experiments. Y.Z., T.W. and D.B constructed a pan-genome, identified specific genes and analyzed data. Y.Z., J.W. and F.W. conducted experiments. Y.Z. wrote the manuscript. J.Z. performed the revision and editing of the original draft. All authors have read and approved the manuscript. Funding This study was supported by grants from the Hubei Provincial Major Special Project for Agricultural Microbial Industry Development (NYWSWZX2025-2027-11), the National Natural Science Foundation of China (32470070). Data availability The data used to support the fndings of this study are available from the corresponding author upon reasonable request. Ethics approval This article does not contain any studies with human participants performed by any of the authors. Conflict of interest The authors declare no competing interests. References Amoah K, Cai J, Huang Y, Wang B, Shija VM, Wang Z, Jin X, Cai S, Lu Y, Jian J (2024) Identification and characterization of four Bacillus species from the intestine of hybrid grouper ( Epinephelus fuscoguttatus ? × E. lanceolatus ?), their antagonistic role on common pathogenic bacteria, and effects on intestinal health. 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Adv Exp Med Biol 672: 304-315. https://doi.org/10.1007/978-1-4419-5979-9_23 Park SA, Bhatia SK, Park HA, Kim SY, Sudheer PDVN, Yang YH, Choi KY (2021) Bacillus subtilis as a robust host for biochemical production utilizing biomass. Crit Rev Biotechnol 41: 827-848. https://doi.org/10.1080/07388551.2021.1888069 Priest FG, Goodfellow M, Shute LA, Berkeley RCW (1987) Bacillus amyloliquefaciens sp. nov., nom. rev. Int J Syst Evol Microbiol 37: 69-71. http://dx.doi.org/10.1099/00207713-37-1-69 Prakash O, Shouche Y, Jangid K, Kostka JE (2013) Microbial cultivation and the role of microbial resource centers in the omics era. Appl Microbiol Biotechnol 97: 51-62. https://doi.org/10.1007/s00253-012-4533-y Wang LT, Lee FL, Tai CJ, Kasai H (2007) Comparison of gyrB gene sequences, 16S rRNA gene sequences and DNA-DNA hybridization in the Bacillus subtilis group. Int J Syst Evol Microbiol 57: 1846-1850. https://doi.org/10.1099/ijs.0.64685-0 Wang Y, She M, Liu K, Zhang Z, Shuang Q (2020) Evaluation of the bacterial diversity of Inner Mongolian acidic gruel using Illumina MiSeq and PCR-DGGE. Curr Microbiol 77: 434–442. https://doi.org/10.1007/s00284-019-01848-9 You I, Kim EB (2020) Genome-based species-specific primers for rapid identification of six species of Lactobacillus acidophilus group using multiplex PCR. PLoS One 15: e0230550. https://doi.org/10.1371/journal.pone.0230550 Yu J, Wang HM, Zha MS, Qing YT, Bai N, Ren Y, Xi XX, Liu WJ, Menghe BLG, Zhang HP (2015) Molecular identification and quantification of lactic acid bacteria in traditional fermented dairy foods of Russia. J Dairy Sci 98:5143–5154. https://doi.org/10.3168/jds.2015-9460 Additional Declarations No competing interests reported. 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15:39:53","extension":"xml","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":132322,"visible":true,"origin":"","legend":"","description":"","filename":"d0b4a57b8cbe4bdbafd1822ace41cff21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/7ef955abac4eac3ae9210633.xml"},{"id":92663746,"identity":"5998b944-edd6-4cc1-acc5-ceb68c698d97","added_by":"auto","created_at":"2025-10-02 15:39:54","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141136,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/511b453e45f8e1246b2ecfb6.html"},{"id":92663742,"identity":"58eace17-be40-41a2-932a-64ccceba43ef","added_by":"auto","created_at":"2025-10-02 15:39:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":126617,"visible":true,"origin":"","legend":"\u003cp\u003eGene set size of the \u003cem\u003eB. subtilis\u003c/em\u003e group species and proportion of target genes present. \u003cstrong\u003eA\u003c/strong\u003e, The gene set size, based on the number of core, accessory, and rare genes for each species within the group used in this study. \u003cstrong\u003eB\u003c/strong\u003e, The proportion of target genes present, and the proportion of \u003cem\u003eB. subtilis\u003c/em\u003e group and outgroup genomes carrying the six genes used as markers in this study.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/84e4ce76e7898774aa1f69f4.png"},{"id":92663734,"identity":"6abdd6d1-2a3b-45d5-8ffe-81954d8feee2","added_by":"auto","created_at":"2025-10-02 15:39:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":121641,"visible":true,"origin":"","legend":"\u003cp\u003eElectrophoresis gel image of multiplex PCR amplification products of \u003cem\u003eB. subtilis\u003c/em\u003e group strains amplified using 12 primer combinations. M represents the Trans2K Plus II DNA Marker, N is the blank control, and Bt corresponds to \u003cem\u003eBacillus thuringiensis\u003c/em\u003e. The table on the right indicates the strain corresponding to each number.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/735eb4a4c0c98bb40e9780fc.png"},{"id":92663750,"identity":"e9a2bf3c-9251-446c-870e-cbf9092fdda7","added_by":"auto","created_at":"2025-10-02 15:39:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":126290,"visible":true,"origin":"","legend":"\u003cp\u003eOptimization of the annealing temperature for multiplex PCR. A-K correspond to annealing temperatures of 55°C, 56°C, 57°C, 58°C, 59°C, 60°C, 61°C, 62°C, 63°C, 64°C, and 65°C, respectively. M represents the Trans2K Plus II DNA Marker, and N is the blank control.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/998d21ce0d59a426465ce2a4.png"},{"id":92664002,"identity":"0fab1a6b-f4b8-4cab-87e4-c5af2cf45105","added_by":"auto","created_at":"2025-10-02 15:47:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":181170,"visible":true,"origin":"","legend":"\u003cp\u003eOptimization of bacterial lysis conditions and sensitivity detection of multiplex PCR. A, B, and C correspond to ultrasonic lysis at 40 kHz, 120 W for 15 minutes, for 30 minutes, and for 30 minutes followed by a 10-minute water bath at 90°C, respectively. D-I correspond to bacterial suspension concentrations of 2.28×10\u003csup\u003e9\u003c/sup\u003e CFU/mL, 2.28×10\u003csup\u003e8\u003c/sup\u003e CFU/mL, 1.14×10\u003csup\u003e8\u003c/sup\u003e CFU/mL, 1.14×10\u003csup\u003e7\u003c/sup\u003e CFU/mL, 1.14×10\u003csup\u003e6\u003c/sup\u003e CFU/mL, and 1.14×10\u003csup\u003e5\u003c/sup\u003e CFU/mL, respectively. M represents the Trans2K Plus II DNA Marker, and N is the blank control.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/9619bbb0d9c535054bdc4b83.png"},{"id":92663745,"identity":"e279efd0-d9fe-47a0-975c-d01f3fd0f2f0","added_by":"auto","created_at":"2025-10-02 15:39:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":122565,"visible":true,"origin":"","legend":"\u003cp\u003eElectrophoretogram of multiplex PCR applied for identifying \u003cem\u003eBacillus subtilis\u003c/em\u003e group species isolated from soil. The numbers 1-20 represent bacterial strains isolated from soil samples by our laboratory. M represents the Trans2K Plus II DNA Marker, and N is the blank control.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/b5999e466525004557970ccd.png"},{"id":95799309,"identity":"55177880-5a55-42d3-af67-0f025957fa1e","added_by":"auto","created_at":"2025-11-13 08:19:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1436813,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/bc34142f-ca7c-47e5-9c9f-4c4c0617c04d.pdf"},{"id":92664003,"identity":"b31cb4d0-8b70-4310-af03-67d392d741d9","added_by":"auto","created_at":"2025-10-02 15:47:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":7648678,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/5f745d28f815fab41a739dcb.docx"},{"id":92663737,"identity":"51eabf3f-43b7-4193-8efd-587df2aebfc2","added_by":"auto","created_at":"2025-10-02 15:39:54","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":20789,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7088511/v1/a17035b2cbf01acd47b9537b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A rapid method for species-level identification of Bacillus subtilis group strains via multiplex pan-genome-based PCR","fulltext":[{"header":"Key Points","content":"\u003cul start=\"50\"\u003e\n \u003cli\u003eThis is frst study to mine novel targets for diferentiating \u003cem\u003eBacillus subtilis\u003c/em\u003e group species.\u003c/li\u003e\n \u003cli\u003eThis study developed a multiplex PCR method for identifying species of \u003cem\u003eBacillus subtilis\u003c/em\u003e group, achieving DNA free extraction and without the need for sequencing\u003c/li\u003e\n \u003cli\u003eThe PCR method efectively detected \u003cem\u003eBacillus subtilis\u003c/em\u003e group species in soil.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe genus \u003cem\u003eBacillus\u003c/em\u003e encompasses a diverse range of species that are commonly divided into two clades based on phylogenetic analysis: the \u003cem\u003eBacillus subtilis\u003c/em\u003e group and the \u003cem\u003eBacillus cereus\u003c/em\u003e group (Bhandari et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Members of the \u003cem\u003eB. subtilis\u003c/em\u003e group typically share common characteristics, including rod-shaped morphology, aerobic or facultatively anaerobic metabolism, Gram-positive cell walls, and the ability to produce endospores (Khurana et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The term \"\u003cem\u003eB. subtilis\u003c/em\u003e group\" is not a formally defined taxonomic unit; rather, it encompasses species closely related to or newly derived from \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eB. licheniformis\u003c/em\u003e, and \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e (Priest et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The group includes species such as \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eB. licheniformis\u003c/em\u003e, \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e, \u003cem\u003eB. velezensis\u003c/em\u003e, \u003cem\u003eB. siamensis\u003c/em\u003e, \u003cem\u003eB. atrophaeus\u003c/em\u003e, \u003cem\u003eB. vallismortis\u003c/em\u003e, \u003cem\u003eB. mojavensis\u003c/em\u003e, \u003cem\u003eB. sonorensis\u003c/em\u003e, \u003cem\u003eB. spizizenii\u003c/em\u003e, \u003cem\u003eB. inaquosorum\u003c/em\u003e, and \u003cem\u003eB. stercoris\u003c/em\u003e (Priest et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Fan et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Harwood et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Caulier et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These species are widely utilized across various fields to produce a diverse array of industrially valuable compounds and products, such as enzymes, peptide antibiotics, surfactants, biofertilizers, chemicals, pharmaceuticals, and nutritional supplements (Gu et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The \u003cem\u003eB. subtilis\u003c/em\u003e group species are well recognized for their significant economic and practical value, with reports estimating a market value of \u003cspan\u003e$\u003c/span\u003e18\u0026nbsp;billion in 2020 and a projected annual growth rate of approximately 8.7% from 2020 to 2024 (Herrmann et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, it is essential to rapidly and efficiently collect many strains of these species from the natural environment in order to accumulate resources for product development. Furthermore, members of the \u003cem\u003eB. subtilis\u003c/em\u003e group exhibit diverse functionalities and distinct application potentials. For instance: \u003cem\u003eB. subtilis\u003c/em\u003e KU106 is utilized in the production of scyllo-inositol for Alzheimer's disease research (Halmschlag et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); and the secondary metabolite of \u003cem\u003eB. licheniformis\u003c/em\u003e, lichenysin, has high surface activity, hemolytic activity, and antibacterial activity (Nerurkar \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Once \u003cem\u003eB. subtilis\u003c/em\u003e group strains are acquired, it is important to perform efficient species-level identification to facilitate targeted development based on species-specific characteristics.\u003c/p\u003e\u003cp\u003eThe primary methods currently used to identify species of the \u003cem\u003eB. subtilis\u003c/em\u003e group include phenotyping, 16S rRNA gene sequencing, and whole-genome sequencing (Gupta et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Camacho et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Amoah et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Historically, identification relied predominantly on the analysis of phenotypic features, including physiological, morphological, and biochemical characteristics. However, this approach offers limited resolution (Bhandari et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Advances in sequencing technologies, 16S rRNA gene sequencing and whole-genome sequencing have led to the widespread adoption of such techniques for species identification. These methods provide high resolution to capture the intrinsic characteristics that distinguish species. Nevertheless, the high cost of sequencing remains a significant barrier for large-scale bacterial species identification. Additionally, sequencing processes are time- and resource-intensive, especially for numerous samples.\u003c/p\u003e\u003cp\u003ePCR technology can also be applied for bacterial species identification (Cousin et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; You and Kim \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This relatively fast, cost-effective, sensitive, specific, and versatile approach provides high resolution while reducing costs and saving time relative to sequencing-based methods, making it suitable for detecting and quantifying bacterial species in complex matrices. Most of the existing PCR-based identification methods rely on 16S rRNA and housekeeping gene sequences, which are ubiquitous, contain variable and highly conserved regions, and are widely available for many strains in public databases (G\u0026oacute;mez-Rojo et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, the high sequence similarity of these genes often limits their ability to distinguish among closely related species or subspecies (Johnson et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). To address this limitation, researchers have turned their focus toward identifying specific marker genes. Recently, a real-time PCR assay was developed using specific genes to identify several \u003cem\u003eWeissella\u003c/em\u003e species (Kim et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Despite the promising potential of PCR technology, however, no study to date has used this strategy to identify species within the \u003cem\u003eB. subtilis\u003c/em\u003e group.\u003c/p\u003e\u003cp\u003eHere, we used pan-genome analysis of \u003cem\u003eB. subtilis\u003c/em\u003e group strains to identify characteristic genes that are specific to the species of this group, and together form a profile that can be used for the species-level identification of \u003cem\u003eB. subtilis\u003c/em\u003e group strains. From these genes, we designed multiple pairs of species-specific primers that produce PCR products of varying lengths and developed a multiplex colony PCR method that, upon resolution of products by gel electrophoresis, yielded species-specific profiles that could be used to identify \u003cem\u003eB. subtilis\u003c/em\u003e group strains collected from the environment. This approach can facilitate the identification of \u003cem\u003eB. subtilis\u003c/em\u003e group strains from large collections of \u003cem\u003eBacillus\u003c/em\u003e isolates, and thereby support the accumulation of potentially valuable strain resources.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003eIdentification of marker genes by pan-genomic analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe downloaded 753 complete genomes of \u003cem\u003eB. subtilis\u003c/em\u003e group strains and 383 complete genomes of outgroup strains (of \u003cem\u003eB. cereus\u003c/em\u003e, \u003cem\u003eB. thuringiensis\u003c/em\u003e, \u003cem\u003eB. anthracis\u003c/em\u003e, \u003cem\u003eB. mycoides\u003c/em\u003e, and \u003cem\u003eB. wiedmannii\u003c/em\u003e) from the NCBI RefSeq database (Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The genomes were filtered using CheckM v1.2.1 with the criteria of genome completeness\u0026thinsp;\u0026ge;\u0026thinsp;90% and contamination\u0026thinsp;\u0026le;\u0026thinsp;5%. Species annotation was performed using GTDB-TK v2.3.2 with default parameters, and genomes with evident annotation errors were excluded. Ultimately, 753 high-quality genomes of the \u003cem\u003eB. subtilis\u003c/em\u003e group and 383 high-quality genomes of the outgroup were obtained (Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Subsequently, the pan-genome for each \u003cem\u003eB. subtilis\u003c/em\u003e group species was constructed using Roary v3.13.0.\u003c/p\u003e\u003cp\u003eRoary v3.13.0 was used to construct a gene presence/absence matrix from these 1,136 genomes. Genes specific to \u003cem\u003eB. subtilis\u003c/em\u003e group species were identified using Scoary v1.6.16. Genes were filtered using the criteria: Sensitivity\u0026thinsp;\u0026ge;\u0026thinsp;90%, Specificity\u0026thinsp;=\u0026thinsp;100%​, ​Odds Ratio\u0026thinsp;\u0026ge;\u0026thinsp;10, and ​Bonferroni_p\u0026thinsp;\u0026le;\u0026thinsp;0.05.​ Genes annotated as encoding hypothetical proteins were excluded. To further exclude genes that are evolutionarily conserved within \u003cem\u003eB. subtilis\u003c/em\u003e group species, candidate markers were further processed through a two-tier filtering approach, as follows: Genes annotated as showing\u0026thinsp;\u0026gt;\u0026thinsp;90% identity to ribosomal proteins (COG J), RNA/DNA polymerases (COG K/L), or core metabolic enzymes (COG C/E/G) were removed. Finally, to facilitate primer design, we removed genes shorter than 600 bp. After screening, we obtained 25 candidate genes. From among the remaining candidate genes, we randomly selected six genes for primer design.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrimer design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the six selected genes, we used Primer-BLAST to design primers that would generate PCR products of different lengths for each target species. The length difference of products from different primers is greater than 30bp, with Primer melting temperatures (Tm) ranging from 55 ℃ to 65 ℃, and default parameters used for others. This process ultimately yielded 12 primer pairs. The primers used in this study are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and were synthesized by AuGCT Biotech (Beijing, China).\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\u003eSpecific primers designed in this study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePrimer sequence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c5\" namest=\"c4\" rowspan=\"2\"\u003e\u003cp\u003eProduct length\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF (5' \u0026minus;\u0026thinsp;3')\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR (5' \u0026minus;\u0026thinsp;3')\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cem\u003earaE\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACGCTTCTGTTGTTTTGCCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eCCTCGGGATTGGGATGGGAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCCCACAGGAATATCGTCGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTGCTTATCGTGCCGGAAAGT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCTCTCGCCCGAAGATGATT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTATGATTGGAGGAGTGGCGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGTGACAAACCCCGCATTCTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eAGAATCACCCGGCACCAATT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e913\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cem\u003eykqA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTCCTTTTTCAGCTGTCGCCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eGCTGAGGAGGTGCTGTTTCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e158\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTGCCCACAGCTGTTTTCAATG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTCCGCTCTTGAACCGTCTTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e406\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCTTTGATGAGACACACGAGC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eCTCGTCACTTTCGGCACAAG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e679\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eyicL\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGCCCAGTATCTGTTCCAGCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eAGGACCACTCGCCTTCAAAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e574\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003ecorC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCGCTTGAACAAATGGCCGAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTGAAGCCGTCCTGATGCATT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGATGTCCCGCCGTACTCATC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTGCTGCATCCGGTCTTTGAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e730\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003egdpP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCAAATGTACGCGAGCCAGTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTGGAAGAGCGACTGGTCAAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003egtaB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eACGCATGATTTGAGGGGTGA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eGAGACCGAACAAGCTGGGAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e449\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12\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\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\u003e\u003cb\u003e​\u003c/b\u003eComparative results of multiplex PCR genotyping versus whole-genome sequencing for strains from soil\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\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\u003eMultiplex PCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWhole-genome sequencing\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eB. velezensis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eB. licheniformis\u003c/em\u003e\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\u003e\u003cb\u003eBacterial strains and DNA extraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe strains used in this study were as follows: \u003cem\u003eB. subtilis\u003c/em\u003e, \u003cem\u003eB. amyloliquefaciens\u003c/em\u003e, \u003cem\u003eB. licheniformis\u003c/em\u003e, \u003cem\u003eB. velezensis\u003c/em\u003e, \u003cem\u003eB. thuringiensis\u003c/em\u003e, \u003cem\u003eB. inaquosorum\u003c/em\u003e, \u003cem\u003eB. spizizenii\u003c/em\u003e, \u003cem\u003eB. stercoris\u003c/em\u003e, \u003cem\u003eB. siamensis\u003c/em\u003e, \u003cem\u003eB. atrophaeus\u003c/em\u003e, \u003cem\u003eB. vallismortis\u003c/em\u003e, \u003cem\u003eB. mojavensis\u003c/em\u003e, \u003cem\u003eB. sonorensis\u003c/em\u003e, and their detailed information were listed in Supplemental Table S2. All strains were cultured in Luria-Bertani (LB) medium at 38\u0026deg;C for 24 hours and then preserved in 25% (v/v) glycerol solution at -80\u0026deg;C. Before DNA extraction, all strains were cultured in LB medium at 38\u0026deg;C for 24 hours. Genomic DNA was extracted using a bacterial DNA extraction kit (Magen Biotechnology, Guangzhou, China), and the purity and concentration of the extracted genomic DNA were determined using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, USA).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMultiplex PCR assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFirstly, we used the above-described DNA the 13 bacterial strains (Supplemental Table S2) to experimentally verify the designed primers. The multiplex PCR reaction system included 10 ng of DNA, 100 nM of each primer, 10 \u0026micro;L of 2 \u0026times; Taq Master Mix (Vazyme BioTech, Nanjing, China), and distilled water to a final reaction volume of 20 \u0026micro;L.\u003c/p\u003e\u003cp\u003eThe PCR amplification cycle consisted of an initial denaturation step at 98\u0026deg;C for 10 minutes, followed by 30 cycles of denaturation at 95\u0026deg;C for 30 seconds, annealing at 60\u0026deg;C for 30 seconds, and extension at 72\u0026deg;C for 90 seconds. A final extension step was performed at 72\u0026deg;C for 10 minutes. After the reaction, agarose gel electrophoresis was performed to ensure that the bands reflected strain differences and there was no evidence of band loss. ​After PCR completion, 3 \u0026micro;L of PCR product was loaded into wells of a 1.5% agarose gel. Electrophoresis was performed at 130 V for 30 minutes, and the bands were visualized under UV light.\u003c/p\u003e\u003cp\u003eTo optimize the multiplex PCR reaction conditions, we used DNA from the 12 bacterial strains as templates, and tested annealing temperatures of 55\u0026deg;C, 56\u0026deg;C, 57\u0026deg;C, 58\u0026deg;C, 59\u0026deg;C, 60\u0026deg;C, 61\u0026deg;C, 62\u0026deg;C, 63\u0026deg;C, 64\u0026deg;C, and 65\u0026deg;C. The optimal annealing temperature was selected based on the results: the bands are displayed in each strain, and the combination of bands for each strain is different.\u003c/p\u003e\u003cp\u003eTo increase the future feasibility of using our method for large-scale bacterial identification, we sought to omit the DNA extraction step and use bacterial suspensions directly as templates for colony PCR. The optimal bacterial cell lysis conditions and detection sensitivity were investigated. Three bacterial cell lysis conditions were tested: ultrasonic treatment at 40 kHz, 120 W for 15 minutes; ultrasonic treatment at 40 kHz, 120 W for 30 minutes; and ultrasonic treatment at 40 kHz, 120 W for 30 minutes followed by immersion in a 90\u0026deg;C water bath for 10 minutes. PCR amplification was then performed using the reaction system and optimized temperature conditions, and the optimal bacterial lysis condition was determined based on the results: the band distribution that appears is the same as that of PCR using DNA.\u003c/p\u003e\u003cp\u003eFinally, the sensitivity of the multiplex PCR was evaluated. Bacterial suspensions were diluted with ddH2O to 2.28\u0026times;10\u003csup\u003e9\u003c/sup\u003e CFU/mL, 2.28\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL, 1.14\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL, 1.14\u0026times;10\u003csup\u003e7\u003c/sup\u003e CFU/mL, 1.14\u0026times;10\u003csup\u003e6\u003c/sup\u003e CFU/mL, and 1.14\u0026times;10\u003csup\u003e5\u003c/sup\u003e CFU/mL. Using the optimized bacterial lysis and PCR conditions, the sensitivity of the multiplex PCR was assessed for each concentration. Select the minimum concentration with the same band distribution as when using DNA for PCR.\u003c/p\u003e\u003cp\u003e\u003cb\u003eApplication of the developed multiplex PCR method\u003c/b\u003e\u003c/p\u003e\u003cp\u003e​​ To verify the practicality of the primers, we selected a dried soil sample collected from Wenshan, Yunnan. 1g of soil was placed in 20ml LB liquid medium for activation for 4 hours, and then the medium was incubated at 80 ℃ for 30 minutes. Then, 50 \u0026micro;l of the suspension was coated on LB solid medium and incubated at 28 ℃ for 24 hours. After that, 23 strains of bacteria were selected from the medium with a morphology resembling \u003cem\u003eB. subtilis\u003c/em\u003e group strains. Then incubate in LB liquid medium at 38 ℃ for 48 hours. Use our designed primers to identify these 23 bacterial strains. Thereafter, genomic DNA was extracted from each strain using a bacterial DNA extraction kit (Magen Biotechnology, Guangzhou, China). Whole-genome sequencing was conducted on the DNBSEQ-T7 PE150 platform (MGI Tech, Shenzhen, China). Raw sequencing data were assembled into draft genomes using SPAdes v3.15.5, and taxonomic annotation was performed with GTDB-Tk v2.3.2 under default parameters.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003ePan-genomic analysis of\u003c/b\u003e \u003cb\u003eB. subtilis\u003c/b\u003e \u003cb\u003egroup strains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGenomic data for the \u003cem\u003eB. subtilis\u003c/em\u003e group and outgroup (\u003cem\u003eB. cereus\u003c/em\u003e, \u003cem\u003eB. thuringiensis\u003c/em\u003e, \u003cem\u003eB. anthracis\u003c/em\u003e, \u003cem\u003eB. mycoides\u003c/em\u003e, and \u003cem\u003eB. wiedmannii\u003c/em\u003e) strains used in this study were obtained from the NCBI RefSeq database. Quality control was performed on the collected genomic data using CheckM, and GTDB-TK was used to correct potential misclassifications in species annotations from the NCBI database. Ultimately, 753 high-quality genome datasets of \u003cem\u003eB. subtilis\u003c/em\u003e group strains and 383 high-quality genome datasets of outgroup strains were obtained (Supplemental Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThrough comparative genomic analysis, we identified the core, accessory, and rare genes of the \u003cem\u003eB. subtilis\u003c/em\u003e group members (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). To search for group-specific genes, we used Roary v3.13.0 to construct a gene presence/absence matrix from these 1,136 genomes. We used Scoary v1.6.16 to filter for unique genes that were completely absent in the outgroup (Specificity\u0026thinsp;=\u0026thinsp;100%) but present in over 90% of the \u003cem\u003eB. subtilis\u003c/em\u003e group genomes (Sensitivity\u0026thinsp;\u0026ge;\u0026thinsp;90%). This yielded a total of 227 genes (Bonferroni_p\u0026thinsp;\u0026le;\u0026thinsp;0.05). After we filtered genes for those with short sequence lengths, those annotated as hypothetical proteins, and those highly conserved across \u003cem\u003eB. subtilis\u003c/em\u003e group species, we obtained 25 candidate genes (Supplemental Table S3). From them, we randomly selected six genes existing only in \u003cem\u003eB. subtilis\u003c/em\u003e group strains (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) for subsequent validation. The selected genes were: the arabinose-proton symporter-encoding gene, \u003cem\u003earaE\u003c/em\u003e; the gamma-glutamylcyclotransferase-encoding gene, \u003cem\u003eykqA\u003c/em\u003e; the EamA family inner membrane transporter-encoding gene, \u003cem\u003eyicL\u003c/em\u003e; the CNNM family magnesium/cobalt transport protein-encoding gene, \u003cem\u003ecorC\u003c/em\u003e; the UTP-glucose-1-phosphate uridylyltransferase-encoding gene, \u003cem\u003egtaB\u003c/em\u003e; and the cyclic-di-AMP phosphodiesterase-encoding gene, \u003cem\u003egdpP\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSpecificity and sensitivity of primers\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe primers used in this study are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. PCR amplification was performed using template DNA extracted from 12 \u003cem\u003eB. subtilis\u003c/em\u003e group strains and one \u003cem\u003eBacillus thuringiensis\u003c/em\u003e strain, and the generated products were resolved by gel electrophoresis. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the developed primers did not amplify any band in \u003cem\u003eB. thuringiensis\u003c/em\u003e, whereas all strains of the \u003cem\u003eB. subtilis\u003c/em\u003e group showed amplification products. Analysis of the combined profiles generated using all six marker genes enabled us to effectively differentiate among these closely related species. Our results suggest that the 12 sets of primers generated herein can be used to effectively identify \u003cem\u003eB. subtilis\u003c/em\u003e group strains and identify species within the \u003cem\u003eB. subtilis\u003c/em\u003e group.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we further optimized the multiplex PCR conditions. Using DNA extracted from the 12 \u003cem\u003eB. subtilis\u003c/em\u003e group strains as templates, we tested PCR amplification with 11 different annealing temperatures ranging from 55\u0026deg;C to 65\u0026deg;C. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the use of an annealing temperature below 60\u0026deg;C resulted in the generation of non-specific bands and did not allow us to distinguish between different strains, whereas the use of an annealing temperature above 60\u0026deg;C was associated with the loss of some bands. Thus, the optimal annealing temperature was determined to be 60\u0026deg;C.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo better accommodate future large-scale bacterial identification using the developed method, we wanted to omit the DNA extraction step and use bacterial suspensions directly as templates for colony PCR. To this end, we investigated the optimal bacterial cell lysis conditions and the detection sensitivity of the adjusted protocol.\u003c/p\u003e\u003cp\u003eTo explore the best bacterial cell lysis condition, 1-\u0026micro;L aliquots of bacterial suspension (2.28\u0026times;10\u003csup\u003e9\u003c/sup\u003e CFU/mL) were mixed with 6.4 \u0026micro;L ddH\u003csub\u003e2\u003c/sub\u003eO in PCR tubes, and the tubes were subjected to 40 kHz, 120 W ultrasonic lysis for 15 minutes, for 30 minutes, or for 30 minutes followed by immersion in a 90\u0026deg;C water bath for 10 minutes. The lysates were amplified using the optimized PCR conditions. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, ultrasonic lysis at 40 kHz and 120 W for 15 or 30 minutes resulted in lower amplification efficiency, the presence of non-specific bands, and missing bands, suggesting that these lysis conditions did not completely release the DNA from the bacteria. Ultrasonic lysis at 40 kHz and 120 W for 30 minutes followed by immersion in a 90\u0026deg;C water bath for 10 minutes yielded the same band as when using DNA for PCR, indicating that this lysis procedure successfully released the bacterial DNA for amplification.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFinally, we tested the sensitivity of the multiplex PCR assay. Bacterial suspensions of the 12 strains were serially diluted to 2.28\u0026times;10\u003csup\u003e9\u003c/sup\u003e CFU/mL, 2.28\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL, 1.14\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL, 1.14\u0026times;10\u003csup\u003e7\u003c/sup\u003e CFU/mL, 1.14\u0026times;10\u003csup\u003e6\u003c/sup\u003e CFU/mL, and 1.14\u0026times;10\u003csup\u003e5\u003c/sup\u003e CFU/mL, and sensitivity tests were performed. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, when the bacterial concentration was 1.14\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL or higher, bands of the expected fragment sizes were successfully amplified. At lower concentrations, the amplification efficiency decreased due to there being an insufficient amount of template, resulting in non-specific and missing bands. These results indicate that the multiplex PCR assay has a sensitivity of 1.14\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL.\u003c/p\u003e\u003cp\u003eThe final optimized multiplex PCR procedure was as follows: One microliter of bacterial suspension (concentration\u0026thinsp;\u0026ge;\u0026thinsp;1.14\u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL) was mixed with 6.6 \u0026micro;L ddH2O, ultrasonicated for 30 minutes at 40 kHz, 120 W, and immersed in a 90\u0026deg;C water bath for 10 minutes. Then, 0.2 \u0026micro;L of each of the 12 primer pairs (0.1 \u0026micro;L for each forward and reverse primer, concentration 100 \u0026micro;M) and 10 \u0026micro;L of 2 \u0026times; Taq Master Mix were added to the reaction volume. Finally, ddH\u003csub\u003e2\u003c/sub\u003eO was added to a final reaction volume of 20 \u0026micro;l. The thermocycling program consisted of an initial denaturation step at 98\u0026deg;C for 10 minutes, followed by 30 cycles of denaturation at 95\u0026deg;C for 30 seconds, annealing at 60\u0026deg;C for 30 seconds, and extension at 72\u0026deg;C for 90 seconds. A final extension step was performed at 72\u0026deg;C for 10 minutes. Then, 1.5% agarose gel was used for electrophoresis at 130v for 30min, and the distribution of bands was observed under ultraviolet light.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIdentification of\u003c/b\u003e \u003cb\u003eB. subtilis\u003c/b\u003e \u003cb\u003egroup strains from soil-derived isolates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eApplication of the aforementioned multiplex PCR workflow to 23 soil-derived isolates yielded 22 presumptive \u003cem\u003eB. subtilis\u003c/em\u003e group members, including six strains of \u003cem\u003eB. velezensis\u003c/em\u003e and 17 strains of \u003cem\u003eB. licheniformis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Whole-genome sequencing followed by GTDB-Tk-based taxonomic assignment (v2.3.2, default parameters) revealed two discordant classifications: Isolates 7 and 23, which were initially identified as \u003cem\u003eB. velezensis\u003c/em\u003e by PCR, were reclassified as \u003cem\u003eB. licheniformis\u003c/em\u003e (Table. 2). Thus, our multiplex PCR demonstrated 91.30% concordance (21/23) with genomic taxonomy at the species level.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMany \u003cem\u003eB. subtilis\u003c/em\u003e group strains are widely utilized in the production of enzymes, vitamins, antibiotics, amino acids and their derivatives, pharmaceuticals, and health products (Muras et al. 2021; Luo et al. 2023). The significant economic and practical value of such strains has been widely recognized, and there is growing interest in the development of novel \u003cem\u003eBacillus subtilis\u003c/em\u003e group strains or related products. In the development and utilization of microbial resources, microbial strain resource libraries serve as a critical source of diverse microbial strains, forming the foundation for discovering and developing novel microbial functions or products (Janssens et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Heylen et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, it is labor-intensive and time-consuming to build a strain library enriched with microorganisms possessing specific target traits. This typically involves collecting samples from various environments, such as soil, water, plants, and animals, and using a series of screening steps to identify strains with desired activities or functions (Prakash et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Therefore, it would be very useful to have a method capable of rapidly identifying and classifying \u003cem\u003eB. subtilis\u003c/em\u003e group strains from a vast array of environmental microorganisms. Given the diverse properties of these strains, it is also essential to accurately differentiate among species within this group. Here, we developed a sensitive, rapid, and specific detection method based on marker genes for \u003cem\u003eB. subtilis\u003c/em\u003e group species. This approach facilitates the identification and species-level classification of strains within the group.\u003c/p\u003e\u003cp\u003eThe multiplex PCR method developed in this study enables the detection of 12 target species within the \u003cem\u003eB. subtilis\u003c/em\u003e group directly through PCR amplification, does not require sequencing to determine the species. This assay utilizes bacterial colonies directly as template DNA, significantly reducing both processing time and associated costs. Designed for diverse industrial settings, the method streamlines detection workflows to shorten turnaround times and offers a highly cost-effective solution for species differentiation. The selection of target genes and the development of specific primers are among the most critical factors in the generation of successful PCR-based methods for identifying bacteria (G\u0026oacute;mez-Rojo et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In previous studies, the 16S rRNA gene was commonly used as the target gene for species differentiation. However, this approach has certain limitations (Yu et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; G\u0026oacute;mez-Rojo et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The 16S rRNA gene often exhibits high sequence similarity, making it inadequate for distinguishing closely related species or subspecies. Within the \u003cem\u003eBacillus subtilis\u003c/em\u003e group, the 16S rRNA gene shows particularly high similarity among species, with reported sequence identities ranging from 98.1\u0026ndash;99.8% (Wang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Therefore, there is a need to identify novel marker genes to replace the 16S rRNA gene and enhance the resolution of PCR-based identification methods for \u003cem\u003eB. subtilis\u003c/em\u003e group species. Previous studies demonstrated that marker genes identified through pan-genomic analysis can effectively differentiate closely related species, such as lactic acid bacteria and \u003cem\u003eWeissella\u003c/em\u003e (You and Kim \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kim et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Following this approach, we conducted a pan-genomic analysis of genomic data from 753 \u003cem\u003eB. subtilis\u003c/em\u003e group strains. We identified six \u003cem\u003eB. subtilis\u003c/em\u003e group-specific marker genes: \u003cem\u003earaE\u003c/em\u003e, \u003cem\u003eykqA\u003c/em\u003e, \u003cem\u003eyicL\u003c/em\u003e, \u003cem\u003ecorC\u003c/em\u003e, \u003cem\u003egtaB\u003c/em\u003e, and \u003cem\u003egdpP\u003c/em\u003e. During primer design, we developed species-specific primer sets for these 12 bacterial species, each yielding PCR amplicons of distinct lengths. We assessed the specificity of the PCR products using the default parameters in Primer-BLAST, with the initial hope that each primer set would generate a unique band for its target species. However, due to the high genetic similarity among these species, some of our designed primers exhibited limited specificity against individual species. For instance, primer pair #6 amplified products across five different species. Nevertheless, we observed that even with this limited specificity of individual primer sets, the resulting banding patterns were unique to each of the 12 species. This distinct combination of amplified bands for each species allows reliable differentiation between them, achieving the intended goal of species identification.​\u003c/p\u003e\u003cp\u003ePCR is cost-effective, relatively simple, and easy to use, and has been successfully applied for the species-level identification of lactic acid bacteria and \u003cem\u003eWeissella\u003c/em\u003e (You and Kim \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kim et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In this study, we developed a PCR-based method for identifying \u003cem\u003eB. subtilis\u003c/em\u003e group strains. By designing specific primers, we ensured that amplification occurred exclusively with \u003cem\u003eB. subtilis\u003c/em\u003e group strains. Species-level identification was achieved by analyzing the unique band patterns formed by PCR products of different lengths following gel electrophoresis. We further optimized the method for large-scale use by developing it into a colony PCR technique, which eliminates the need for bacterial DNA extraction and thus streamlines the process. We applied this multiplex PCR method to identify 23 bacterial strains previously isolated from soil, and successfully classified 22 strains as belonging to the \u003cem\u003eB. subtilis\u003c/em\u003e group. Comparison between PCR-based identification and whole-genome sequencing with GTDB-Tk annotation revealed misclassification of two strains, for an accuracy rate of 91.30%. This demonstrates that the PCR method established in this study is fully applicable for screening \u003cem\u003eB. subtilis\u003c/em\u003e group strains in soil samples. In the two misidentified strains, the PCR products showed faint band intensities with uneven brightness between the two target bands, leading to interpretation errors.\u003c/p\u003e\u003cp\u003eIn summary, our newly developed PCR-based method provides a rapid, convenient, and efficient means for identifying \u003cem\u003eB. subtilis\u003c/em\u003e group strains from soil samples. This method could provide technical support for the accumulation, development, and utilization of \u003cem\u003eB. subtilis\u003c/em\u003e-group microbial resources.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u0026nbsp;\u003c/strong\u003eJ.Z. andY.Z. conceived the project. J.Z. administrated the project and acquired the funding. Y.Z. designed the experiments. Y.Z., T.W. and D.B constructed a pan-genome, identified specific genes and analyzed data. Y.Z., J.W. and F.W. conducted experiments. Y.Z. wrote the manuscript. J.Z. performed the revision and editing of the original draft. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis study was supported by grants from the Hubei Provincial Major Special Project for Agricultural Microbial Industry Development (NYWSWZX2025-2027-11), the National Natural Science Foundation of China (32470070).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e The data used to support the fndings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eThis article does not contain any studies with human participants performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmoah K, Cai J, Huang Y, Wang B, Shija VM, Wang Z, Jin X, Cai S, Lu Y, Jian J (2024) Identification and characterization of four \u003cem\u003eBacillus species\u003c/em\u003e from the intestine of hybrid grouper (\u003cem\u003eEpinephelus fuscoguttatus\u003c/em\u003e? \u0026times; \u003cem\u003eE. lanceolatus\u003c/em\u003e?), their antagonistic role on common pathogenic bacteria, and effects on intestinal health. 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J Dairy Sci 98:5143\u0026ndash;5154. https://doi.org/10.3168/jds.2015-9460\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 subtilis group, Marker genes, Multiplex PCR, Identification, Pan-genome, Soil microorganism","lastPublishedDoi":"10.21203/rs.3.rs-7088511/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7088511/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe various species within the \u003cem\u003eBacillus subtilis\u003c/em\u003e group possess significant economic and practical value, but exhibit distinct functions and have divergent applications. Thus, there is an urgent need for a rapid, efficient, and cost-effective method to accurately distinguish species and their strains within the \u003cem\u003eB. subtilis\u003c/em\u003e group, to enable bacterial resources to be precisely screened and classified. Here, we developed a comparative genomics-based multiplex PCR method for the species-level identification of \u003cem\u003eB. subtilis\u003c/em\u003e group strains to facilitate the accumulation of \u003cem\u003eB. subtilis\u003c/em\u003e group microbial resources. We constructed a pan-genome from 753 genomes spanning 12 species within the \u003cem\u003eB. subtilis\u003c/em\u003e group, and used it to identify six marker genes that together could distinguish among the species: \u003cem\u003earaE\u003c/em\u003e, \u003cem\u003eykqA\u003c/em\u003e, \u003cem\u003eyicL\u003c/em\u003e, \u003cem\u003ecorC\u003c/em\u003e, \u003cem\u003egtaB\u003c/em\u003e, and \u003cem\u003egdpP\u003c/em\u003e. Specific primers for these marker genes were designed to generate distinct PCR product profiles that enabled species-level identification of strains. This method was used to successfully identify 21 \u003cem\u003eB. subtilis\u003c/em\u003e group strains from a collection of 23 bacterial isolates obtained from soil, yielding an accuracy rate of 91.30%. Our results demonstrate the feasibility and reliability of this multiplex PCR approach, which could provide an efficient and accurate tool for screening and classifying \u003cem\u003eB. subtilis\u003c/em\u003e group strains from soil microbial communities, and thereby support their exploration and utilization in various applications.\u003c/p\u003e","manuscriptTitle":"A rapid method for species-level identification of Bacillus subtilis group strains via multiplex pan-genome-based PCR","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-02 15:39:19","doi":"10.21203/rs.3.rs-7088511/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":"52fc7618-e46c-4d27-90a7-456cffd16e9c","owner":[],"postedDate":"October 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-12T07:54:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-02 15:39:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7088511","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7088511","identity":"rs-7088511","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}