Dataset Information

Cloning and nucleotide sequence analysis of gyrB of Bacillus cereus, B. thuringiensis, B. mycoides, and B. anthracis and their application to the detection of B. cereus in rice.

ABSTRACT: As 16S rRNA sequence analysis has proven inadequate for the differentiation of Bacillus cereus from closely related species, we employed the gyrase B gene (gyrB) as a molecular diagnostic marker. The gyrB genes of B. cereus JCM 2152(T), Bacillus thuringiensis IAM 12077(T), Bacillus mycoides ATCC 6462(T), and Bacillus anthracis Pasteur #2H were cloned and sequenced. Oligonucleotide PCR primer sets were designed from within gyrB sequences of the respective bacteria for the specific amplification and differentiation of B. cereus, B. thuringiensis, and B. anthracis. The results from the amplification of gyrB sequences correlated well with results obtained with the 16S rDNA-based hybridization study but not with the results of their phenotypic characterization. Some of the reference strains of both B. cereus (three serovars) and B. thuringiensis (two serovars) were not positive in PCR amplification assays with gyrB primers. However, complete sequencing of 1.2-kb gyrB fragments of these reference strains showed that these serovars had, in fact, lower homology than their originally designated species. We developed and tested a procedure for the specific detection of the target organism in boiled rice that entailed 15 h of preenrichment followed by PCR amplification of the B. cereus-specific fragment. This method enabled us to detect an initial inoculum of 0.24 CFU of B. cereus cells per g of boiled rice food homogenate without extracting DNA. However, a simple two-step filtration step is required to remove PCR inhibitory substances.

SUBMITTER: Yamada S

PROVIDER: S-EPMC91211 | biostudies-literature | 1999 Apr

REPOSITORIES: biostudies-literature

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Cloning and nucleotide sequence analysis of gyrB of Bacillus cereus, B. thuringiensis, B. mycoides, and B. anthracis and their application to the detection of B. cereus in rice.

Yamada S S Ohashi E E Agata N N Venkateswaran K K

Applied and environmental microbiology 19990401 4

As 16S rRNA sequence analysis has proven inadequate for the differentiation of Bacillus cereus from closely related species, we employed the gyrase B gene (gyrB) as a molecular diagnostic marker. The gyrB genes of B. cereus JCM 2152(T), Bacillus thuringiensis IAM 12077(T), Bacillus mycoides ATCC 6462(T), and Bacillus anthracis Pasteur #2H were cloned and sequenced. Oligonucleotide PCR primer sets were designed from within gyrB sequences of the respective bacteria for the specific amplification a ...[more]

PMID: 10103241

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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.

Project description:BACKGROUND:Bacillus cereus biovar anthracis (Bcbva) is an emergent bacterium closely related to Bacillus anthracis, the etiological agent of anthrax. The latter has a worldwide distribution and usually causes infectious disease in mammals associated with savanna ecosystems. Bcbva was identified in humid tropical forests of Côte d'Ivoire in 2001. Here, we characterize the potential geographic distributions of Bcbva in West Africa and B. anthracis in sub-Saharan Africa using an ecological niche modeling approach. METHODOLOGY/PRINCIPAL FINDINGS:Georeferenced occurrence data for B. anthracis and Bcbva were obtained from public data repositories and the scientific literature. Combinations of temperature, humidity, vegetation greenness, and soils values served as environmental variables in model calibrations. To predict the potential distribution of suitable environments for each pathogen across the study region, parameter values derived from the median of 10 replicates of the best-performing model for each pathogen were used. We found suitable environments predicted for B. anthracis across areas of confirmed and suspected anthrax activity in sub-Saharan Africa, including an east-west corridor from Ethiopia to Sierra Leone in the Sahel region and multiple areas in eastern, central, and southern Africa. The study area for Bcbva was restricted to West and Central Africa to reflect areas that have likely been accessible to Bcbva by dispersal. Model predicted values indicated potential suitable environments within humid forested environments. Background similarity tests in geographic space indicated statistical support to reject the null hypothesis of similarity when comparing environments associated with B. anthracis to those of Bcbva and when comparing humidity values and soils values individually. We failed to reject the null hypothesis of similarity when comparing environments associated with Bcbva to those of B. anthracis, suggesting that additional investigation is needed to provide a more robust characterization of the Bcbva niche. CONCLUSIONS/SIGNIFICANCE:This study represents the first time that the environmental and geographic distribution of Bcbva has been mapped. We document likely differences in ecological niche-and consequently in geographic distribution-between Bcbva and typical B. anthracis, and areas of possible co-occurrence between the two. We provide information crucial to guiding and improving monitoring efforts focused on these pathogens.

Dataset Information

Cloning and nucleotide sequence analysis of gyrB of Bacillus cereus, B. thuringiensis, B. mycoides, and B. anthracis and their application to the detection of B. cereus in rice.

Publications

Cloning and nucleotide sequence analysis of gyrB of Bacillus cereus, B. thuringiensis, B. mycoides, and B. anthracis and their application to the detection of B. cereus in rice.

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