Metabolomics aided by machine learning decodes adaptive remodeling of Bacillus biofilms in response to pasteurization stress
摘要
The popularity of low-temperature dairy products is challenged by Bacillus species, whose heat-resistant spores and biofilms often survive pasteurization. Moreover, heat treatment can paradoxically enhance biofilm formation in some Bacillus spp., a phenomenon whose metabolic basis is not fully understood. Combining untargeted metabolomics with random forest analysis, we decoded the metabolic adaptations behind this heat-induced biofilm enhancement in raw milk Bacillus isolates. Our results demonstrate strain-specific mechanisms: in BC01, heat stress activated glutaminase, depleting L-glutamine and free histidine to relieve metabolic inhibition and activate biofilm genes, while reduced xanthosine promoted the biofilm-state transition. In BS01, metabolic network restructuring led to decreased synthesis of arginine, D-amino acid, dopamine, and arachidonic acid, thereby mitigating their known inhibitory effects on biofilm formation. This study clarifies the metabolic drivers of biofilm adaptation under heat stress, highlighting novel targets for metabolic intervention in dairy safety.