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Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis
Published on: May 23, 2021
Whole-genome sequencing and comparative genomics reveal antimicrobial potential and adaptive traits of Bacillus
Qianqian Lin1, Fengzhi Pan1, JinJin Yang2
1College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, 524088, China.
Abstract:
The global rise of antimicrobial resistance has intensified the demand for novel antimicrobial agents with broad-spectrum efficacy and unique mechanisms of action. Herein, a marine-derived strain, Bacillus velezensis (B. velezensis) AM12, exhibiting clear inhibitory activity against eight major foodborne pathogens, was isolated from coastal seawater near Zhanjiang, China. Whole-genome sequencing revealed a 3,992,266 bp circular chromosome with a GC content of 46%, and functional annotation indicated extensive metabolic potential. Genome mining using the antiSMASH platform identified 14 secondary metabolite biosynthetic gene clusters, including those encoding surfactin, macrolactin H, bacillaene, fengycin, difficidin, bacillibactin, and bacilysin, as well as several additional clusters potentially responsible for the biosynthesis of novel antimicrobial compounds. Analysis using the BAGEL4 database further detected four bacteriocin/RiPP biosynthetic loci, corresponding to Competence/ComX, Amylocyclicin, LCI, and a Lichenicidin-like cluster. These collectively explain the broad-spectrum antibacterial activity of AM12 and suggest potential antifungal capability. Notably, the core genes of ComX and LCI exhibited relatively low similarity (46.67% and 73.91%, respectively) to known references, and B. velezensis AM12-origin lichenicidin component 2 showed no detectable homology, suggesting that AM12 may encode structurally and functionally distinct novel bacteriocins. Comparative genomic analysis with closely related terrestrial B. velezensis strains revealed that AM12-specific genes are predominantly enriched in functions associated with marine environmental adaptation and antimicrobial activity. Furthermore, machine learning-based prediction using the AM12-specific gene set identified seven high-confidence antimicrobial peptide candidates characterized by cationic charge, amphipathicity, and structural stability. This study elucidates the genomic and molecular basis of the broad-spectrum antibacterial activity pertaining to B. velezensis AM12, and establishes a systematic framework for the identification of novel antimicrobial peptides, offering candidate genes for subsequent functional characterization.
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