ABSTRACT
Bacillus cereus is a common pathogen causing foodborne diseases, secreting and producing a large number of toxins that can cause a variety of diseases and pose many threats to human health. In this study, 73 strains of Bacillus cereus were isolated and identified from six types of foods from seven different cities in a province, and the antibiotic-resistant phenotype was detected by using the Bauer-Kirby method. Results showed that the 73 isolates were completely sensitive to gentamicin and 100% resistant to chloramphenicol, in addition to which all strains showed varying degrees of resistance to 13 other common antibiotics, and a large number of strains resistant to multiple antibiotics were found. A bioinformatic analysis of the expression of resistance genes in Bacillus cereus showed three classes of antibiotic-resistant genes, which were three of the six classes of antibiotics identified according to the resistance phenotype. The presence of other classes of antibiotic-resistant genes was identified from genome-wide information. Antibiotic-resistant phenotypes were analyzed for correlations with genotype, and remarkable differences were found among the phenotypes. The spread of antibiotic-resistant strains is a serious public health problem that requires the long-term monitoring of antimicrobial resistance in Bacillus cereus, and the present study provides important information for monitoring antibiotic resistance in bacteria from different types of food.
ABSTRACT
Bacillus cereus is an important zoonotic foodborne conditional pathogen. It is found in vegetables, dairy products, rice, and other foods, thereby greatly endangering human health. Investigations on B. cereus contamination in China primarily focus on raw milk, dairy products, meat, and others, and limited research has been conducted on plant-based foodstuffs. The rapid development of sequencing technology and the application of bioinformatics-related techniques means that analysis based on whole-genome sequencing has become an important tool for the molecular-epidemiology investigation of B. cereus. In this study, we investigated the contamination of B. cereus in six types of commercially available plant foods from eight regions of a province. The molecular epidemiology of the isolated B. cereus was analyzed by whole-genome sequencing. We aimed to provide fundamental data for the surveillance and epidemiology analysis of B. cereus in food products in China. The rapid traceability system of B. cereus established in this study can provide a basis for rapid molecular epidemiology analysis of B. cereus, as well as for the prevention and surveillance of B. cereus. Moreover, it can also be expanded to monitoring and rapid tracing of more foodborne pathogens.
ABSTRACT
Shigella and Bacillus cereus are two common foodborne pathogens that cause intestinal diseases and seriously affect human life and health. Traditional microbiological culture methods are time-consuming and laborious, and polymerase chain reaction (PCR)-based methods rely on expensive thermal cyclers and lengthy reaction times. In this study, on the basis of the specific gene ipaH7 of Shigella and the virulence gene nheABC of B. cereus, a duplex detection system was established for the first time by using the recombinase polymerase amplification technique (D-RPA). After optimization, D-RPA could be effectively amplified at 42 °C for 25 min with excellent specificity, and the detection limits of D-RPA for Shigella and B. cereus in artificially contaminated samples were 2.7 × 101 and 5.2 × 102 CFU/mL, respectively. This study provides a certain research basis for multiple detection with RPA, an isothermal amplification technology. Furthermore, it lays a good foundation for high-throughput rapid detection of foodborne pathogens.
ABSTRACT
In this paper, a "turn-off" biosensor for detecting copper (II) ions based on Cu2+-dependent DNAzyme and a "blocker" beacon were developed. Upon the copper ion being added, the Cu2+-dependent DNAzyme substrate strand was irreversibly cleaved, thereby blocking the occurrence of the ligation reaction and PCR, which inhibited the G-rich sequence from forming the G-quadruplex structure, efficiently reducing the detection signal. This method had the characteristics of strong specificity and high sensitivity compared with the existing method due to the application of ligation-dependent probe signal recognition and amplification procedures. Under the optimized conditions, this method proved to be highly sensitive. The signal decreased as the concentration of copper ions increased, exhibiting a linear calibration from 0.03125 µM to 0.5 µM and a limit of detection of 18.25 nM. Subsequently, the selectivity of this biosensor was verified to be excellent by testing different relevant metal ions. Furthermore, this detection system of copper (II) ions was successfully applied to monitor Cu2+ contained in actual water samples, which demonstrated the feasibility of the biosensor.
