Genomic adaptability and virulence of Bacillus anthracis: a machine learning-based pan-genome and comparative analysis

Bacillus anthracis (B. anthracis), a Gram-positive bacterium, poses significant threats to both livestock and humans, with known potential use in bioterrorism. Despite its zoonotic importance, the pathogen’s evolutionary dynamics and metabolic genes remain poorly understood, limiting insights into its virulence mechanisms. This study aimed to: (i) evaluate the distribution of toxin genes across B. anthracis isolates, (ii) employ a machine learning algorithm to identify genetic differences among toxin- and capsule synthesis gene-carrying B. anthracis isolates, and (iii) identify shared metabolic genes of B. anthracis in humans and locate key hub genes. Comprehensive genomic analyses revealed important new insights into B. anthracis diversity and pathogenesis. The study identified the thiol-activated cytolysin BAS3109 toxin as conserved across all isolates, highlighting its fundamental role alongside the canonical toxin genes (pagA, lef, cya) in virulence. Variations in the pXO1 and pXO2 plasmids significantly drive strain-specific virulence profiles and adaptation across globally diverse isolates. Using machine learning and clustering approaches, we also discovered that GuaA, a gene involved in guanine nucleotide biosynthesis, acts as a key metabolic hub gene. GuaA’s central role in metabolic pathways makes it a promising biomarker and potential target for therapeutic intervention. This study demonstrates that while the chromosomal genome remains closed and stable, plasmid variability, particularly in pXO2 constitutes the primary source of genomic diversity within B. anthracis. The conserved presence of BAS3109 and the identification of GuaA as a central metabolic hub emphasizes new avenues for understanding B. anthracis pathogenesis and for developing diagnostic and therapeutic strategies. Our findings establish that plasmid-driven genomic diversity combined with core metabolic functions shapes the virulence and evolutionary potential of B. anthracis. This enhanced understanding provides a robust framework for future research aimed at controlling and preventing anthrax infections.

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Journal
BMC Genomics
Published
2026-01-07
DOI
https://doi.org/10.1186/s12864-025-12348-5
Primary Topic
Bacillus and Francisella bacterial research
Type
article
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article

Genomic adaptability and virulence of Bacillus anthracis: a machine learning-based pan-genome and comparative analysis

Swati Rani, S. Saranya, Divakar Hemadri, Jayashree Anand et al.
BMC Genomics
Bacillus and Francisella bacterial research
article

Genomic adaptability and virulence of Bacillus anthracis: a machine learning-based pan-genome and comparative analysis

Swati Rani, S. Saranya, Divakar Hemadri, Jayashree Anand, Baldev Raj Gulati, Raghavendra G G Amachawadi, P. Chellapandi, Kuralayanapalya Puttahonnappa Suresh, Mohan Kumar Papanna, Mehnaj Khatoon, Yamini Sri Sekar, Chamalapura Ashwathama Archana, Azhahianambi Palavesam, Archana Patil, Sharanagouda S. Patil, Ningegowda Sagar
article en

Abstract

Bacillus anthracis (B. anthracis), a Gram-positive bacterium, poses significant threats to both livestock and humans, with known potential use in bioterrorism. Despite its zoonotic importance, the pathogen’s evolutionary dynamics and metabolic genes remain poorly understood, limiting insights into its virulence mechanisms. This study aimed to: (i) evaluate the distribution of toxin genes across B. anthracis isolates, (ii) employ a machine learning algorithm to identify genetic differences among toxin- and capsule synthesis gene-carrying B. anthracis isolates, and (iii) identify shared metabolic genes of B. anthracis in humans and locate key hub genes. Comprehensive genomic analyses revealed important new insights into B. anthracis diversity and pathogenesis. The study identified the thiol-activated cytolysin BAS3109 toxin as conserved across all isolates, highlighting its fundamental role alongside the canonical toxin genes (pagA, lef, cya) in virulence. Variations in the pXO1 and pXO2 plasmids significantly drive strain-specific virulence profiles and adaptation across globally diverse isolates. Using machine learning and clustering approaches, we also discovered that GuaA, a gene involved in guanine nucleotide biosynthesis, acts as a key metabolic hub gene. GuaA’s central role in metabolic pathways makes it a promising biomarker and potential target for therapeutic intervention. This study demonstrates that while the chromosomal genome remains closed and stable, plasmid variability, particularly in pXO2 constitutes the primary source of genomic diversity within B. anthracis. The conserved presence of BAS3109 and the identification of GuaA as a central metabolic hub emphasizes new avenues for understanding B. anthracis pathogenesis and for developing diagnostic and therapeutic strategies. Our findings establish that plasmid-driven genomic diversity combined with core metabolic functions shapes the virulence and evolutionary potential of B. anthracis. This enhanced understanding provides a robust framework for future research aimed at controlling and preventing anthrax infections.

BMC GenomicsVol. 27(1)
Pennsylvania State University (US), Kansas State University (US), Bharathidasan University (IN), National Institute Of Veterinary Epidemiology And Disease Informatics (IN), Translational Research Platform for Veterinary Biologicals (India) (IN), Tamil Nadu Veterinary and Animal Sciences University (IN)
Openalex Percentile: Top 94%
Bacillus and Francisella bacterial research
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