Development of an Online Genome Sequence Comparison Resource for Bacillus cereus sensu lato Strains Using the Efficient Composition Vector Method.
Kui WangChanglong ShuAlejandra BravoMario SoberónHongjun ZhangNeil CrickmoreJie ZhangPublished in: Toxins (2023)
An automated method was developed for differentiating closely related B. cereus sensu lato ( s.l. ) species, especially biopesticide Bacillus thuringiensis, from other human pathogens, B. anthracis and B. cereus sensu stricto ( s.s. ). In the current research, four typing methods were initially compared, including multi-locus sequence typing (MLST), single-copy core genes phylogenetic analysis (SCCGPA), dispensable genes content pattern analysis (DGCPA) and composition vector tree (CVTree), to analyze the genomic variability of 23 B. thuringiensis strains from aizawai , kurstaki , israelensis , thuringiensis and morrisoni serovars. The CVTree method was the best option to be used for typing B. thuringiensis strains since it proved to be the fastest method, whilst giving high-resolution data about the strains. In addition, CVTree agrees well with ANI-based method, revealing the relationship between B. thuringiensis and other B. cereus s.l. species. Based on these data, an online genome sequence comparison resource was built for Bacillus strains called the Bacillus Typing Bioinformatics Database to facilitate strain identification and characterization.
Keyphrases
- escherichia coli
- genetic diversity
- genome wide
- high resolution
- bacillus subtilis
- electronic health record
- endothelial cells
- mass spectrometry
- amino acid
- gene expression
- emergency department
- big data
- transcription factor
- deep learning
- machine learning
- genome wide identification
- multidrug resistant
- gram negative
- data analysis
- bioinformatics analysis
- artificial intelligence
- antimicrobial resistance