Speaker
Description
Sulfate-reducing bacteria (SRB) play a pivotal role in the global sulfur cycle and microbial metal transformations, influencing both ecological resilience and industrial challenges such as microbially induced corrosion (MIC). This research focuses on Oleidesulfovibrio alaskensis G20 (OA G20), a genetically tractable SRB model, to elucidate mechanisms underlying stress tolerance, biofilm formation, and adaptation to metal-contaminated environments.
Employing a systems biology framework, the study integrates multi-omics datasets, network biology, and literature-mining pipelines to define the functional landscape of biofilm-driven SRB physiology. A novel computational workflow was developed to identify core gene modules involved in environmental stress responses and biofilm regulation. Experimental results reveal that OA G20 exhibits distinct morphological and transcriptomic adaptations under acidic, alkaline, and copper-induced stress, with key alterations in exopolysaccharide (EPS) synthesis, energy metabolism, and metal detoxification pathways. Surface-resolved omics analyses demonstrate enhanced biofilm architecture and upregulation of genes associated with nanowire production, signal transduction, and ion homeostasis under copper exposure. Notably, this work presents the first epigenetic landscape of SRB biofilms subjected to metal stress, uncovering differential 5-methylcytosine (5mC) DNA methylation patterns in genes governing carbon metabolism and lipopolysaccharide (LPS) transport. Proteomic profiling further supports the copper-specific modulation of chemotaxis and cytoskeletal protein networks.
Given the complexity of the OMICS data and the intricacy of the mechanisms by which SRB interact with and adapt to metal surfaces, advanced artificial intelligence (AI) tools are essential for comprehensive integration and mechanistic interpretation.
