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

被引:2
|
作者
Wang, Gang [1 ]
Ren, Ying [1 ]
Su, Yuying [1 ]
Zhang, Hui [1 ]
Li, Jinfeng [1 ]
Zhao, Hongxia [2 ]
Zhang, Huixia [3 ]
Han, Jianping [1 ]
机构
[1] Chinese Acad Med Sci & Peking Union Med Coll, Inst Med Plant Dev, Beijing, Peoples R China
[2] Guangdong Acad Sci, Inst Zool, Guangzhou, Peoples R China
[3] Agrotech Extens Ctr Guangdong Prov, Guangzhou, Peoples R China
关键词
Food poisoning; Boiling; Digestion; Pollen; Identification; High sensitivity; PLANTS; QUANTIFICATION; KONG;
D O I
10.1016/j.foodres.2024.114188
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
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/mu l. 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.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] Gluten Detection by Real-Time PCR: an Alternative for Tracking Processed Foods
    Oliveira, Wemerson de Castro
    Froder, Hans
    Righi, Eleia
    BRAZILIAN ARCHIVES OF BIOLOGY AND TECHNOLOGY, 2025, 68
  • [32] Quantification of DNA fragmentation in processed foods using real-time PCR
    Mano, Junichi
    Nishitsuji, Yasuyuki
    Kikuchi, Yosuke
    Fukudome, Shin-ichi
    Hayashida, Takuya
    Kawakami, Hiroyuki
    Kurimoto, Youichi
    Noguchi, Akio
    Kondo, Kazunari
    Teshima, Reiko
    Takabatake, Reona
    Kitta, Kazumi
    FOOD CHEMISTRY, 2017, 226 : 149 - 155
  • [33] Quantitative identification of rice cultivars by real-time PCR
    Okunishi, T
    Nakamura, S
    Ohtsubo, K
    FOOD SCIENCE AND TECHNOLOGY RESEARCH, 2005, 11 (03) : 344 - 348
  • [34] Real-Time PCR Identification of Six Malassezia Species
    Ilahi, Amin
    Hadrich, Ines
    Neji, Sourour
    Trabelsi, Houaida
    Makni, Fattouma
    Ayadi, Ali
    CURRENT MICROBIOLOGY, 2017, 74 (06) : 671 - 677
  • [35] Real-Time PCR Identification of Six Malassezia Species
    Amin Ilahi
    Inès Hadrich
    Sourour Neji
    Houaida Trabelsi
    Fattouma Makni
    Ali Ayadi
    Current Microbiology, 2017, 74 : 671 - 677
  • [36] Multiplex real-time PCR for dermatophytes detection and identification
    Arabatzis, M.
    van Coppenraet, L. Bruijnesteijn
    Kuijper, E.
    de Hoog, S.
    Lavrijsen, A.
    Templeton, K.
    van der Raaij-Helmer, E.
    Velegraki, A.
    Summerbell, R.
    JOURNAL OF INVESTIGATIVE DERMATOLOGY, 2006, 126 : 128 - 128
  • [37] Identification of insect sources of honey in China based on real-time fluorescent LAMP technology
    Gao, Jie
    Jin, Xiue
    Gong, Bo
    Li, Jingjing
    Chen, Ailiang
    Tan, Jianxin
    Wang, Jun
    JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2023, 115
  • [38] A comparison of ELISA and real-time PCR kits for meat species identification analysis
    Yoruk, Nuray Gamze
    EUROPEAN FOOD RESEARCH AND TECHNOLOGY, 2021, 247 (10) : 2421 - 2429
  • [39] A comparison of ELISA and real-time PCR kits for meat species identification analysis
    Nuray Gamze YÖRÜK
    European Food Research and Technology, 2021, 247 : 2421 - 2429
  • [40] Identification of meat species by TaqMan-based real-time PCR assay
    Kesmen, Z.
    Gulluce, A.
    Sahin, F.
    Yetim, H.
    MEAT SCIENCE, 2009, 82 (04) : 444 - 449