Biotechnology Bulletin ›› 2019, Vol. 35 ›› Issue (10): 130-136.doi: 10.13560/j.cnki.biotech.bull.1985.2019-0266

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Pan-Genome Analysis and Secondary Metabolic Pathway Mining of Bacillus circulans

YAO Cai-miao1, ZHAO Wen-ya2,3, WANG Bu-qing2,3, ZHENG Li-yan2,3, ZHANG Li-ping2,3, LIU Hong-wei2,3   

  1. 1. Department of Laboratory Medicine,980 Hospital of PLA Joint Logistics Support Force,Shijiazhuang 050000;
    2. Institute of Biology,Hebei Academy of Science,Shijiazhuang 050081;
    3. Main Crops Disease of Microbial Control Engineering Technology Research Center in Hebei Province,Shijiazhuang 050081
  • Received:2019-04-02 Online:2019-10-26 Published:2019-09-30

Abstract: This study aimed to deeply understand the genomes of Bacillus circulans and to mine these secondary metabolic pathways. The genomes of 9 B. circulans were downloaded from NCBI database and analyzed by phylogenetic analysis software,pan-genome analysis software and secondary metabolite mining software. The genome size of 9 strains was between 5.01-9.63 Mb and was divided into two branches in the evolutionary tree. Through the analysis of pan-genome and core genome,it was found that the pan-genome contained 9 572 cluster genes,the core genome was composed of 3 622 cluster genes,and a total of 4 593 specific cluster genes were identified. Among them,strain NCTC2610 had the most specific cluster genes(3 030)and strain NBRC 13626 had the least specific cluster genes(39). After the analysis of secondary metabolite synthesis gene clusters,6 types and 32 secondary metabolic gene clusters were found in 9 B. circulansgenomes,and the most repeated metabolic pathways were lanthipeptide,lassopeptide and terpene compounds synthesis pathways. In sum,through this study the pan-genome and core genome of 9 B. circulans were clarified,and their secondary metabolic pathways were predicted. These results will help us to fully understand B. circulans,and will provide us some clues to better use those strains.

Key words: Bacillus circulans, pan-genome, secondary metabolic, genome mining