Dataset Information

Differentiation of Bacillus thuringiensis From Bacillus cereus Group Using a Unique Marker Based on Real-Time PCR.

ABSTRACT: The efficiency of a novel biomarker (the transcriptional regulator, XRE) was tested and evaluated in differentiating Bacillus thuringiensis from Bacillus cereus group species in environmental and spiked samples based on PCR and real-time PCR. Totally 120 strains, representing two bacterial groups, B. cereus group and non-Bacillus sp., were used to evaluate the performance of XRE and crystal protein (cry2, an existing biomarker). Further, three diverse samples (kimbap, lettuce, and spinach) were inoculated with B. thuringiensis and prominent biomarkers XRE and cry2 were used as targets. Direct analysis of the detection results for the pure cultures of B. cereus group wild-types, references and type strains revealed an accuracy rate of 97.5% targeting XRE, and 83.3% targeting cry2. The real-time PCR was constructed with a R 2-value of 0.993. For the artificially contaminated samples, a concentration of 103 CFU/g of B. thuringiensis in spiked food samples could be detected using real-time PCR targeting XRE. A good performance was obtained with XRE in discriminating B. thuringiensis from B. cereus groups, as well as detecting B. thuringiensis in spiked food samples with PCR or real-time PCR. Therefore, this real-time PCR targeting XRE can be used as a dependable and promising tool to identify B. thuringiensis in foods.

SUBMITTER: Wei S

PROVIDER: S-EPMC6503103 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Differentiation of Bacillus thuringiensis From Bacillus cereus Group Using a Unique Marker Based on Real-Time PCR.

Wei Shuai S Chelliah Ramachandran R Park Byung-Jae BJ Kim Se-Hun SH Forghani Fereidoun F Cho Min Seok MS Park Dong-Suk DS Jin Yong-Guo YG Oh Deog-Hwan DH

Frontiers in microbiology 20190430

The efficiency of a novel biomarker (the transcriptional regulator, XRE) was tested and evaluated in differentiating Bacillus thuringiensis from Bacillus cereus group species in environmental and spiked samples based on PCR and real-time PCR. Totally 120 strains, representing two bacterial groups, B. cereus group and non-Bacillus sp., were used to evaluate the performance of XRE and crystal protein (cry2, an existing biomarker). Further, three div ...[more]

PMID: 31114555

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Project description:Background:It is possible to detect bacterial species in shotgun metagenome datasets through the presence of only a few sequence reads. However, false positive results can arise, as was the case in the initial findings of a recent New York City subway metagenome project. False positives are especially likely when two closely related are present in the same sample. Bacillus anthracis, the etiologic agent of anthrax, is a high-consequence pathogen that shares >99% average nucleotide identity with Bacillus cereus group (BCerG) genomes. Our goal was to create an analysis tool that used k-mers to detect B. anthracis, incorporating information about the coverage of BCerG in the metagenome sample. Methods:Using public complete genome sequence datasets, we identified a set of 31-mer signatures that differentiated B. anthracis from other members of the B. cereus group (BCerG), and another set which differentiated BCerG genomes (including B. anthracis) from other Bacillus strains. We also created a set of 31-mers for detecting the lethal factor gene, the key genetic diagnostic of the presence of anthrax-causing bacteria. We created synthetic sequence datasets based on existing genomes to test the accuracy of a k-mer based detection model. Results:We found 239,503 B. anthracis-specific 31-mers (the Ba31 set), 10,183 BCerG 31-mers (the BCerG31 set), and 2,617 lethal factor k-mers (the lef31 set). We showed that false positive B. anthracis k-mers-which arise from random sequencing errors-are observable at high genome coverages of B. cereus. We also showed that there is a "gray zone" below 0.184× coverage of the B. anthracis genome sequence, in which we cannot expect with high probability to identify lethal factor k-mers. We created a linear regression model to differentiate the presence of B. anthracis-like chromosomes from sequencing errors given the BCerG background coverage. We showed that while shotgun datasets from the New York City subway metagenome project had no matches to lef31 k-mers and hence were negative for B. anthracis, some samples showed evidence of strains very closely related to the pathogen. Discussion:This work shows how extensive libraries of complete genomes can be used to create organism-specific signatures to help interpret metagenomes. We contrast "specialist" approaches to metagenome analysis such as this work to "generalist" software that seeks to classify all organisms present in the sample and note the more general utility of a k-mer filter approach when taxonomic boundaries lack clarity or high levels of precision are required.

Dataset Information

Differentiation of Bacillus thuringiensis From Bacillus cereus Group Using a Unique Marker Based on Real-Time PCR.

Publications

Differentiation of <i>Bacillus thuringiensis</i> From <i>Bacillus</i> <i>cereus</i> Group Using a Unique Marker Based on Real-Time PCR.

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