Decoding Biothreats With FT-ICR-MS: Metabotyping of Bacillus cereus Spores Through Untargeted Metabolomics.

Abstract

Genome sequencing is the gold standard for microbial identification. However, it fails to distinguish closely related species with overlapping genetic features. This is the case of Bacillus cereus and Bacillus cytotoxicus, two members of the B. cereus group with distinct pathogenic profiles. While B. cereus, a well-known opportunistic pathogen involved in intestinal and extraintestinal infections, produces the tissue-destructive exoenzymes hemolysin BL (HBL), nonhemolytic enterotoxin (NHE), and cytotoxin K (CytK-2) as well as the plasmid-encoded emetic toxin cereulide, the thermotolerant species B. cytotoxicus is primarily characterized by producing cytotoxin K-1 (CytK-1), implicated in severe diarrheal outbreaks. Despite these differences, genomic data alone often fail to clearly differentiate the two species. Moreover, these bacteria primarily exist as highly resilient spores in environmental samples, further complicating their identification using traditional methods and hindering accurate classification and risk assessment. This distinction becomes particularly relevant in the context of biowarfare. The B. cereus group includes strains that possess genetic elements similar to Bacillus anthracis, the causative agent of anthrax, and some B. cereus strains can acquire virulence plasmids, making them capable of causing anthrax-like infections. Misidentification or delayed differentiation of these resilient bacteria at spore level is of severe consequences in the event of a biological attack or an accident, where rapid and accurate detection is critical for an effective and timely response. Here, we show that FT-ICR-MS-based untargeted metabolomics enables B. cereus and B. cytotoxicus discrimination, while providing critical insights into spore-specific metabolomic signatures, ultimately contributing to improved microbial forensics and bio-surveillance strategies.