Screening of Antagonistic Bacteria against Three Aquatic Pathogens and Characterization of Lipopeptides in <i>Bacillus cereus</i> BA09
Screening for antagonistic bacteria on aquatic pathogens and identification of antagonistic ingredients are essential to reduce the use of chemicals in aquaculture. In this study, strain BA09, subsequently identified as <i>Bacillus cereus</i>, simultaneously displayed strong antagonistic effects on <i>Edwardsiella tarda</i>, <i>Vibrio harveyi</i>, and <i>Streptococcus anisopliae</i> in the initial screening and rescreening. In addition, the methanol extract of BA09 was subjected to antibacterial activity verification and one-dimensional (1D) reversed-phase liquid chromatography (RPLC) preparation. A total of 27 fractions were collected, 6 of which were subjected to two-dimensional (2D) RPLC separation and tracked as antibacterial. A total of 14 lipopeptides that included 9 fengycin homologs, 3 bacillomycin homologs, and 2 surfactin homologs were identified by tandem high-resolution mass spectrometry. Through characterization of the antibacterial substance in <i>Bacillus cereus</i> BA09, which simultaneously inhibited <i>E. tarda</i>, <i>V. harveyi</i>, and <i>S. agalactiae</i>, the current study provides a theoretical basis for the development of antibacterial drugs in aquaculture.
Authors
- Weijia Zhou (ORCID: https://orcid.org/0000-0003-4339-0435)
- Shigen Ye
- Xiaocen Lu (ORCID: https://orcid.org/0000-0002-8269-3837)
- Xinran Shi
- Cuiyan Cao (ORCID: https://orcid.org/0000-0003-1764-9351)
- Shengnan Cao
- Zhixin Guo (ORCID: https://orcid.org/0000-0003-0510-6851)
- Ning Jin
- Sheng Dong (ORCID: https://orcid.org/0000-0002-0452-5221)
- Xu Ren (ORCID: https://orcid.org/0000-0003-2225-6229)
- Yu Zhang (ORCID: https://orcid.org/0000-0001-8296-154X)
Institutions
- Dalian Ocean University (CN)
- Dalian Institute of Chemical Physics (CN)
- Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Journal of Microbiology and Biotechnology
- Published
- 2024-08-25
- DOI
- https://doi.org/10.4014/jmb.2404.04017
- Citations
- 2
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.47