Biocontrol potential of Bacillus spp. against Ralstonia solanacearum and Alternaria alternata: antimicrobial metabolites identification and comparative genomics

Plant diseases caused by bacterial and fungal pathogens pose a major threat to agricultural productivity, highlighting the need for effective biocontrol agents. Soil microorganisms, particularly Bacillus species, represent important sources of antimicrobial metabolites and are widely considered promising biocontrol resources due to their metabolic versatility and ecological adaptability. In this study, bacteria isolated from diseased tobacco rhizosphere soil were comparatively evaluated for their antagonistic effect against two typical plant pathogens: Ralstonia solanacearum RS10 and Alternaria alternata CX06. Four Bacillus species ( Bacillus velezensis AQ171, Bacillus spizizenii cmc7, Bacillus halotolerans WL51, and Bacillus cereus HTDT4) were further subjected to integrated metabolite profiling and comparative genomic analysis. Marked differences in antagonistic performance among the strains may be associated with variation in secondary metabolite biosynthetic potential. LC–MS/MS analysis revealed distinct antimicrobial metabolite profiles, whereas comparative genomics identified substantial differences in secondary metabolite biosynthetic genes and predicted gene clusters. Among the tested strains, B. velezensis AQ171 exhibited the strongest overall antagonistic activity against R. solanacearum RS10 and A. alternata CX06. The 100% methanol fraction of AQ171 was the only one showing antibacterial activity against R. solanacearum RS10 and exhibited an inhibition rate of 85.71% against A. alternata CX06 at 2 mg/mL. AQ171 also exhibited the most diverse metabolite profile, with putatively identified metabolites corresponding to macrolactin, iturin, fengycin, and surfactin families, together with a relatively comprehensive repertoire of predicted secondary metabolite biosynthetic gene clusters involved in lipopeptide and polyketide biosynthesis. These findings demonstrate that genetic and metabolic diversity are closely associated with biocontrol efficacy and support genome-guided selection of effective biocontrol agents.