Rapid identification of Hebeloma crustuliniforme species using real-time fluorescence and visual loop-mediated isothermal amplification based on the internal transcribed spacer sequence

Polymerase chain reaction-based methods for the rapid identification of Amanita exitialis

Amanita exitialis, a deadly mushroom found in eastern Asia, causes the highest death rates among all poisonous mushrooms in China. The aim of the present study was to develop an efficient, accurate, and user-friendly PCR-based method for identifying A. exitialis that could facilitate the prevention, diagnosis, and treatment of associated food poisoning. A. exitialis-specific primers and probes were designed based on the internal transcribed spacer region variations of 27 mushroom species. Specificity was confirmed using conventional and real-time PCR for 23 non-target mushroom species, including morphologically similar and closely related species. Compared to conventional PCR, real-time PCR was more sensitive (detectable DNA concentration: 1.36 × 10-2 ng/μL vs. 1.36 × 10-3) and efficient (analysis time: 1 h vs. 40 min). Furthermore, the real-time PCR results could be immediately visualized using amplification curve analysis. The results present two robust PCR-based methods for A. exitialis identification that can facilitate food safety.

Identification of toxic Gelsemium elegans in processed food and honey based on real-time PCR analysis

Gelsemium elegans (GE) is a widely distributed hypertoxic plant that has caused many food poisoning incidents. Its pollen can also be collected by bees to produce toxic honey, posing a great threat to the health and safety of consumers. However, for the complex matrices such as cooked food and honey, it is challenging to perform composition analysis. It is necessary to establish more effective strategies for investigating GE contamination. In this study, the real-time PCR (qPCR) analysis combined with DNA barcode matK was proposed for the identification and detection of GE. Fifteen honey samples along with twenty-eight individuals of GE and the common confusable objects Lonicera japonica, Ficus hirta, Stellera chamaejasme and Chelidonium majus were gathered. Additionally, the food mixtures treated with 20-min boiling and 30-min digestion were prepared. Specific primers were designed, and the detection capability and sensitivity of qPCR in honey and boiled and digested food matrices were tested. The results demonstrated that the matK sequence with sufficient mutation sites was an effective molecular marker for species differentiation. GE and the confusable species could be clearly classified by the fluorescence signal of qPCR assay with a high sensitivity of 0.001 ng/μl. In addition, this method was successfully employed for the detection of deeply processed food materials and honey containing GE plants which even accounted for only 0.1 %. The sequencing-free qPCR approach undoubtedly can serve as a robust support for the quality supervision of honey industry and the prevention and diagnosis of food poisoning.