Project description:This series represents the work described in the publication Bacillus subtilis Genome Diversity by Earl et al. (Journal of Bacteriology, accepted) Keywords: comparative genomic hybridization
Project description:Bacillus cytotoxicus is the thermotolerant representative of the Bacillus cereus group. This group, also known as B. cereus sensu lato, comprises both beneficial and pathogenic members and includes psychrotolerant and thermotolerant species. Bacillus cytotoxicus was originally recovered from a fatal outbreak in France in 1998. This species forms a remote cluster from the B. cereus group members and reliably contains the cytk-1 gene, coding for a cytotoxic variant of cytotoxin K. Although this species was originally thought to be homogenous, intra-species diversity has been recently described with four clades, six random amplified polymorphic DNA (RAPD) patterns, and 11 plasmids profiles. This study aimed to get new insights into the genomic diversity of B. cytotoxicus and to decipher the underlying chromosomal and plasmidial variations among six representative isolates through whole genome sequencing (WGS). Among the six sequenced strains, four fitted the previously described genomic clades A and D, while the remaining two constituted new distinct branches. As for the plasmid content of these strains, three large plasmids were putatively conjugative and three small ones potentially mobilizable, harboring coding genes for putative leaderless bacteriocins. Mobile genetic elements, such as prophages, Insertion Sequences (IS), and Bacillus cereus repeats (bcr) greatly contributed to the B. cytotoxicus diversity. As for IS elements and bcr, IS3 and bcr1 were the most abundant elements and, along with the group II intron B.c.I8, were found in all analyzed B. cytotoxicus strains. When compared to other B. cytotoxicus strains, the type-strain NVH 391-98 displayed a relatively low number of IS. Our results shed new light on the contribution of mobile genetic elements to the genome plasticity of B. cytotoxicus and their potential role in horizontal gene transfer.
Project description:Geothermal areas are the niches of a rich microbial diversity that is not only part of the intangible patrimony of a country but also the source of many microbial species with potential biotechnological applications. Particularly, microbial species in geothermal areas in Argentina have been scarcely explored regarding their possible biotechnological uses. The purpose of this work was to explore the proteolytic and keratinolytic enzymatic potential of microorganisms that inhabit in the Domuyo geothermal area in the Neuquén Province. To this end, we did enrichment cultures from two high-temperature natural samples in mineral media only supplemented with whole chicken feathers. After the isolation and the phylogenetic and morphologic characterization of different colonies, we obtained a collection of Bacillus cytotoxicus isolates, a species with no previous report of keratinolytic activity and only reported in rehydrated meals connected with food poisoning outbreaks. Its natural habitat has been unknown up to now. We characterized the proteolytic and keratinolytic capacities of the B.cytotoxicus isolates in different conditions, which proved to be remarkably high compared with those of other similar species. Thus, our work represents the first report of the isolation as well as the keratinolytic capacity characterization of strains of B. cytotixicus obtained from a natural environment.
Project description:Soybeans fermented by Bacillus subtilis BJ3-2 exhibits strong ammonia taste in medium temperature below 37℃ and prominent soy sauce-like aroma moderate temperatures above 45℃. The transcriptome sequencing of Bacillus subtilis BJ3-2 (incubating at 37°C and 45°C) has been completed, screening of differentially expressed genes (DEGs) through data analysis, and analyzing their metabolic pathways, laying a foundation for exploring the regulatory mechanism of soy sauce-like aroma formation.
Project description:The Bacillus cereus group comprises genetical closely related species with variable toxigenic characteristics. However, detection and differentiation of the B. cereus group species in routine diagnostics can be difficult, expensive and laborious since current species designation is linked to specific phenotypic characteristic or the presence of species-specific genes. Especially the differentiation of Bacillus cereus and Bacillus thuringiensis, the identification of psychrotolerant Bacillus mycoides and Bacillus weihenstephanensis, as well as the identification of emetic B. cereus and Bacillus cytotoxicus, which are both producing highly potent toxins, is of high importance in food microbiology. Thus, we investigated the use of a machine learning approach, based on artificial neural network (ANN) assisted Fourier transform infrared (FTIR) spectroscopy, for discrimination of B. cereus group members. The deep learning tool box of Matlab was employed to construct a one-level ANN, allowing the discrimination of the aforementioned B. cereus group members. This model resulted in 100% correct identification for the training set and 99.5% correct identification overall. The established ANN was applied to investigate the composition of B. cereus group members in soil, as a natural habitat of B. cereus, and in food samples originating from foodborne outbreaks. These analyses revealed a high complexity of B. cereus group populations, not only in soil samples but also in the samples from the foodborne outbreaks, highlighting the importance of taking multiple isolates from samples implicated in food poisonings. Notable, in contrast to the soil samples, no bacteria belonging to the psychrotolerant B. cereus group members were detected in the food samples linked to foodborne outbreaks, while the overall abundancy of B. thuringiensis did not significantly differ between the sample categories. None of the isolates was classified as B. cytotoxicus, fostering the hypothesis that the latter species is linked to very specific ecological niches. Overall, our work shows that machine learning assisted (FTIR) spectroscopy is suitable for identification of B. cereus group members in routine diagnostics and outbreak investigations. In addition, it is a promising tool to explore the natural habitats of B. cereus group, such as soil.