Proteomic and machine learning analyses reveal the mechanism of baicalin in inhibiting biofilm formation of Escherichia coli

Biofilm formation is a key survival strategy by which Escherichia coli ( E. coli ) resists environmental stress and sustains persistent infections. Baicalin, a natural flavonoid compound, has been reported to possess antibacterial and antivirulence activities; however, its antibiofilm mechanism remains incompletely understood. This study integrated phenotypic assays, Data‑Independent Acquisition (DIA)-based quantitative proteomics, bioinformatics, machine learning and Scanning Electron Microscopy (SEM) to investigate the effect of baicalin on E. coli D5 biofilm formation. Baicalin markedly inhibited biofilm formation in a concentration-dependent manner. Importantly, viable cell counts under biofilm-inducing culture conditions showed no significant reduction, indicating that the inhibitory effect of baicalin on biofilm formation was not caused by changes in the total number of viable bacteria in the wells. Proteomic analysis indicated that baicalin treatment was associated with changes in energy metabolism, chemotaxis and flagellar assembly. Consistently, baicalin increased intracellular ROS levels, reduced intracellular ATP levels, whereas extracellular ATP remained unchanged, suggesting metabolic and redox remodeling rather than nonspecific membrane leakage. Baicalin also impaired swimming and swarming motility and reduced flagellar abundance. Machine learning further identified the flagellin-associated protein A0A140NAX2 as a candidate feature linked to the antibiofilm phenotype. Collectively, these findings suggest that baicalin suppresses E. coli D5 biofilm formation mainly by altering metabolic state and impairing motility- and flagella-associated early adhesion processes, rather than by directly reducing total bacterial viability under biofilm-inducing conditions.