We aimed to establish a method for the rapid identification of three common Gram-positive bacteria (Bacillus cereus, Listeria monocytogenes, and Micrococcus luteus) associated with foodborne diseases. MALDI-TOF-MS was used to determine the effects of sample pretreatment, culture medium, and culture time on the identification results. Then, MALDI-TOF-TOF-MS was used to establish an optimized method and further explore the effects of culture time on secondary proteins. Among the three sample pretreatment methods, formic acid extraction outperformed direct transfer and extended direct transfer, resulting in more protein peaks and higher peak intensity in B. cereus culture samples. However, with different culture times (1-7 d), ion peaks of all bacterial proteins were relatively stable according to MALDI-TOF-TOF-MS data. The protein peaks of B. cereus (1430 m/z), L. monocytogenes (2100 m/z), and M. luteus (2140 m/z) were split into small ion peaks at 1162, 1465, and 1625 m/z, respectively. After 7 d of culture, the secondary spectra, peak intensities, and peak values of formic acid-treated samples were relatively stable, indicating that secondary protein peaks were less affected by culture time. It provides a new approach for the routine identification and market supervision of food safety in China.
The trend of low breastfeeding rates increases the demand for infant milk formula (IMF) worldwide, but the use of IMF may be one of the causes of bacterial infections in infants. Complete sterility in the whole production line of IMF cannot be guaranteed; therefore, it is necessary to closely monitor the microbial content in the process. In the present study, an IMF powder production line based on the wet mixing process was sampled at 27 suspicious points in spring and summer to analyze the bacterial diversity by high-throughput sequencing. We found that 70 and 69 different bacterial phyla were present in spring and summer samples, respectively, with Proteobacteria and Firmicutes being the dominant phyla (>80% relative abundance). Moreover, 13 dominant genera each were present in spring (e. g., Pseudomonas and Lactococcus) and summer (e. g., Pseudomonas, Bacillus, and Streptococcus). Samples associated with workers showed higher bacterial species diversity (Shannon index) and richness (Chao1 index) in summer than in spring. The bacterial community composition showed high similarity between liquid milk after pasteurization and concentrated milk after evaporation. The potential bacterial pathogens were identified as Pseudomonas aeruginosa in spring and Acinetobacter baumannii in summer. Through retrospective analysis of the two opportunistic pathogens identified, it was found that the workshop environment was the potential contamination point in spring, whereas the auxiliary ingredients were the potential source of contamination in summer. The results highlight the effect of season on bacterial diversity associated with the production process of IMF and are useful in controlling the microbial quality and safety of infant dairy products.
Genetically modified soybean strains are trade monitoring object by China. Currently, the genetically modified soybean MON89788 has been approved in China to be imported as processing raw material. Therefore, there is an urgent need to establish a method to quantitatively assess MON89788. This study used droplet digital PCR technology to quantitatively detect MON89788. The results showed that the genomic DNA concentration and its copy number of genetically modified soybeans showed a certain linear relationship. The formula was y = 2.5967x + 3.1437, where R2 = 0.999. When the same 4.5% genetically modified sample was contained, the results of the droplet digital PCR ratio and linear methods were 5.88% and 3.599%, respectively. Comparing the two results showed that the droplet digital PCR ratio method has a larger error than the linear relationship method. The novel droplet digital PCR linear relationship method established in this study has high sensitivity and specificity, and thus is a good prospect for quantitative research.
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