Skip to main content
Microbiology Resource Announcements logoLink to Microbiology Resource Announcements
. 2026 Mar 10;15(4):e01424-25. doi: 10.1128/mra.01424-25

Draft genome sequence of Bacillus pumilus SP1, a soil isolate with antagonistic activity toward Staphylococcus epidermidis

Sean Pauly 1, Fatemah Hermes 2,
Editor: Atmika Paudel3
PMCID: PMC13064154  PMID: 41805186

ABSTRACT

A Bacillus pumilus soil isolate displayed antagonistic activity against Staphylococcus epidermidis ATCC 14990. Here, we present a draft genome sequence for this isolate.

KEYWORDS: soil microbiology, antagonism, Bacillus

ANNOUNCEMENT

Soil microbes drive carbon, nitrogen, and phosphorus cycling and modulate mineral availability (1). They support plant growth through chemical signaling and protect plants against pests and pathogens through antibiotic production (2). The central role of these microbes in soil health directly links them to the well-being of animals and humans (3, 4). Maintaining healthy soils reduces the need for fertilizers and therefore contributes to climate change mitigation (5). Many of these microorganisms have valuable industrial applications, further underscoring their importance (6).

As part of a microbiology course at the University of Health Sciences and Pharmacy, a sample of surface soil was collected in a sterile 50-mL tube in spring 2025 from the St. Louis area. After serial dilution in sterile water of a suspension of 1 g of the soil, aliquots were plated on brain heart infusion (BHI) agar plates containing 25 µg/mL cycloheximide and incubated at 33°C for 48 h. Several of the colonies that appeared were colony-purified by repeated quadrant streaking and then tested for antagonistic behavior against a collection of lab strains as described in the legend to Fig. 1. Isolate SP1 inhibited the growth of Staphylococcus epidermidis ATCC 14990 (Fig. 1) and was thus chosen for genome sequencing. The bacterium was grown to mid-log phase in Luria-Bertani, Miller (LB) broth (4 h) at 37°C with shaking at 180 rpm. About 6 × 109 cells were collected, washed with saline phosphate buffer, and resuspended in 500 µL DNA/RNA stabilization solution from Zymo. The suspension was sent to Plasmidsaurus for genomic DNA extraction, library prep, and sequencing.

Fig 1.

Bacterial culture plate displaying SP1 antagonism against S. epidermidis. A circular SP1 colony in the center has created a clear inhibition zone surrounded by the S. epidermidis lawn, demonstrating antimicrobial activity after incubation.

SP1 antagonism of S. epidermidis ATCC 14990. Both strains were grown overnight in LB, Miller broth with aeration; 50 µL of the S. epidermidis culture was spread on BHI agar, and 10 µL of the SP1 culture was spotted on the lawn. The plate was incubated overnight at 33°C. This image shows SP1 growth surrounded by a clear zone, then the S. epidermidis lawn.

DNA extraction was conducted using the Zymo Quick DNA Miniprep Plus Kit. DNA quantity was assessed using Qubit. Library prep was performed using the ultra-long DNA sequencing kit v14 from Oxford Nanopore Technologies (ONT). Sequencing was conducted on a PromethION instrument using an R10.4.1 flow cell. Base calling, adapter trimming, and read filtering were performed by ONT’s Dorado v.0.5.0 with quality filter set to Q10. A total of 133,214 reads were obtained.

The 16S rRNA gene was parsed using Mash v2.3 (7) and Sourmash v4.9.4 (8) and identified the bacterium as Bacillus pumilus. De novo genome assembly was carried out on the BV-BRC platform (9) using Canu v2.0 (10) with an estimated genome size set to 5 Mbp and target genome coverage set to 100×. The assembly was polished with four iterations of Racon v1.5.0 (11). Assembly quality was assessed using QUAST v5.2.0 (12). Annotation was automatically performed by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v6.10 (13). CheckM completeness was 99.9% (14). Unless otherwise noted, all software settings were set to default.

The SP1 genome is 4067923 bp long and consists of 12 contigs with an average depth of coverage of 118.73×, N50 and N90 = 3,845,078 bp, and 41.08% GC content. Contig 7 may be part of a plasmid as it has almost 2× coverage relative to the longest read. There are a total of 4,195 predicted genes in the genome. Information about the assembly and annotation is summarized in Table 1.

TABLE 1.

Summary of B. pumilus SP1 genome assembly and annotation

Contig Length Coverage normalized to the longest contig No. of predicted genes
1 3,845,078 1 3,954
2 28,793 0.26 30
3 27,188 0.21 28
4 17,103 0.48 19
5 42,965 0.48 47
6 14,430 0.14 17
7 16,551 1.9 20
8 20,736 0.34 22
9 15,597 0.12 18
10 12,181 0.28 15
11 17,633 0.39 15
12 9,668 0.15 10

Contributor Information

Fatemah Hermes, Email: Fatemah.hermes@uhsp.edu.

Atmika Paudel, Fluxus Inc., Sunnyvale, California, USA.

DATA AVAILABILITY

This work is registered at the NCBI under BioProject PRJNA1372794. The BioSample identifier of SP1 is SAMN53626511. The raw sequence data file is SRX31311881. The Whole Genome Shotgun project has been deposited in GenBank under the accession no. JBSQHT000000000. The version described in this paper is the first version, JBSQHT01000000

REFERENCES

  • 1. Iqbal S, Begum F, Nguchu BA, Claver UP, Shaw P. 2025. The invisible architects: microbial communities and their transformative role in soil health and global climate changes. Environ Microbiome 20:36. doi: 10.1186/s40793-025-00694-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Wang X, Chi Y, Song S. 2024. Important soil microbiota’s effects on plants and soils: a comprehensive 30-year systematic literature review. Front Microbiol 15:1347745. doi: 10.3389/fmicb.2024.1347745 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Banerjee S, van der Heijden MGA. 2023. Soil microbiomes and one health. Nat Rev Microbiol 21:6–20. doi: 10.1038/s41579-022-00779-w [DOI] [PubMed] [Google Scholar]
  • 4. Sabater C, Neacsu M, Duncan SH. 2025. Harnessing beneficial soil bacteria to promote sustainable agriculture and food security: a one health perspective. Front Microbiol 16:1638553. doi: 10.3389/fmicb.2025.1638553 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Kiprotich K, Muema E, Wekesa C, Ndombi T, Muoma J, Omayio D, Ochieno D, Motsi H, Mncedi S, Tarus J. 2025. Unveiling the roles, mechanisms and prospects of soil microbial communities in sustainable agriculture. Discov Soil 2:10. doi: 10.1007/s44378-025-00037-4 [DOI] [Google Scholar]
  • 6. Sharma N, Ahlawat YK, Stalin N, Mehmood S, Morya S, Malik A, H M, Nellore J, Bhanot D. 2024. Microbial enzymes in industrial biotechnology: sources, production, and significant applications of lipases. J Ind Microbiol Biotechnol 52:kuaf010. doi: 10.1093/jimb/kuaf010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM. 2016. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 17:132. doi: 10.1186/s13059-016-0997-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Pierce NT, Irber L, Reiter T, Brooks P, Brown CT. 2019. Large-scale sequence comparisons with sourmash. F1000Res 8:1006. doi: 10.12688/f1000research.19675.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Olson RD, Assaf R, Brettin T, Conrad N, Cucinell C, Davis JJ, Dempsey DM, Dickerman A, Dietrich EM, Kenyon RW, et al. 2023. Introducing the bacterial and viral bioinformatics resource center (BV-BRC): a resource combining PATRIC, IRD and ViPR. Nucleic Acids Res 51:D678–D689. doi: 10.1093/nar/gkac1003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH, Phillippy AM. 2017. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 27:722–736. doi: 10.1101/gr.215087.116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Vaser R, Sović I, Nagarajan N, Šikić M. 2017. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 27:737–746. doi: 10.1101/gr.214270.116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Gurevich A, Saveliev V, Vyahhi N, Tesler G. 2013. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072–1075. doi: 10.1093/bioinformatics/btt086 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, Lomsadze A, Pruitt KD, Borodovsky M, Ostell J. 2016. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res 44:6614–6624. doi: 10.1093/nar/gkw569 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. 2015. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 25:1043–1055. doi: 10.1101/gr.186072.114 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

This work is registered at the NCBI under BioProject PRJNA1372794. The BioSample identifier of SP1 is SAMN53626511. The raw sequence data file is SRX31311881. The Whole Genome Shotgun project has been deposited in GenBank under the accession no. JBSQHT000000000. The version described in this paper is the first version, JBSQHT01000000


Articles from Microbiology Resource Announcements are provided here courtesy of American Society for Microbiology (ASM)

RESOURCES