in

Genome-wide analysis reveals structured ecological and functional divergence within Geobacillus stearothermophilus


Abstract

Geobacillus stearothermophilus is a thermophilic bacterium widely used in food sterilization and industrial processes. Although it has long been treated as a single, well-defined species, its internal genomic diversity has not been systematically evaluated. Here, we analyzed 36 strains using comparative genomics to clarify the structure of diversity within this species. Phylogenetic analyses consistently revealed two major genomic groups. Genome similarity measurements showed that most strains met current species-level criteria, yet clear internal differentiation was present. The two groups differed in ecological origin and genome composition. Strains associated with food-related environments tended to have smaller genomes and fewer metabolic genes, whereas strains from natural thermal habitats possessed larger genomes and broader metabolic capabilities, including genes for carbohydrate and fatty acid utilization. A small number of strains displayed intermediate positions, suggesting gradual diversification rather than sharp separation. Despite pronounced internal structuring, the strains remain within accepted species boundaries. These findings demonstrate that substantial ecological and functional divergence can accumulate within a single bacterial species. Our results provide a genomic framework for understanding intraspecific diversity in thermophilic bacteria and illustrate the importance of interpreting genome similarity thresholds in the context of population structure.

Acknowledgements

Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics.

Funding

Yu Sato is supported by the HIRAKU-Global Program, which is funded by MEXT’s “Strategic Professional Development Program for Young Researchers”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to
Shintaro Maeno.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary Information 1. (download PDF )

Supplementary Information 2. (download XLSX )

Supplementary Information 3. (download XLSX )

Supplementary Information 4. (download XLSX )

Supplementary Information 5. (download XLSX )

Supplementary Information 6. (download XLSX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Arakane, S., Sato, Y., Hashino, M. et al. Genome-wide analysis reveals structured ecological and functional divergence within Geobacillus stearothermophilus.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-55928-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-026-55928-5

Keywords


  • Geobacillus stearothermophilus
  • Extremophiles
  • Phylogenetics
  • Comparative genomics
  • Genomic plasticity


Source: Ecology - nature.com

Urban Stressors Disrupt the Phenological Clock, Unravelling Urban Ecosystems and Services

Enzyme-aware soil fertility prediction using dual optimization with improved SCSO

Back to Top