Determination of bacterial toxin toxoflavin and fervenulin in food and identification of their degradation products

Wang, Hui; Hu, Lili; Chang, Xiaotu; Hu, Yuge; Zhang, Yan; Zhou, Peng; Cui, Xiaojiao

doi:10.1016/j.foodchem.2022.134010

Cited by 3 publications

(4 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sample pretreatment for toxoflavin extraction was modified from [11] and was as follows. Four grams of sample was added into 36.0 mL CH 3 OH with 1% CH 3 COOH.…”

Section: Uplc Analysis Pretreatmentmentioning

confidence: 99%

“…cocovenenans comes from the two secondary metabolites toxoflavin [8] and bongkrekic acid [9] produced by the strain. Toxoflavin inhibits the respiratory chain and produces peroxide, which causes damage to vascular smooth muscle and organs [10,11]. Another toxin, bongkrekic acid is a mitochondrial toxin, which affects the normal metabolism of cells by inhibiting mitochondrial adenine nucleotide translocatase.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of Burkholderia gladioli pv. cocovenenans in Black Fungus and Efficient Recognition of Bongkrekic Acid and Toxoflavin Producing Phenotype by Back Propagation Neural Network

Niu,

Song,

Hao

et al. 2024

Foods

View full text Add to dashboard Cite

Burkholderia gladioli pv. cocovenenans is a serious safety issue in black fungus due to the deadly toxin, bongkrekic acid. This has triggered the demand for an efficient toxigenic phenotype recognition method. The objective of this study is to develop an efficient method for the recognition of toxin-producing B. gladioli strains. The potential of multilocus sequence typing and a back propagation neural network for the recognition of toxigenic B. cocovenenans was explored for the first time. The virulent strains were isolated from a black fungus cultivation environment in Qinba Mountain area, Shaanxi, China. A comprehensive evaluation of toxigenic capability of 26 isolates were conducted using Ultra Performance Liquid Chromatography for determination of bongkrekic acid and toxoflavin production in different culturing conditions and foods. The isolates produced bongkrekic acid in the range of 0.05–6.24 mg/L in black fungus and a highly toxin-producing strain generated 201.86 mg/L bongkrekic acid and 45.26 mg/L toxoflavin in co-cultivation with Rhizopus oryzae on PDA medium. Multilocus sequence typing phylogeny (MLST) analysis showed that housekeeping gene sequences have a certain relationship with a strain toxigenic phenotype. We developed a well-trained, back-propagation neutral network for prediction of toxigenic phenotype in B. gladioli based on MLST sequences with an accuracy of 100% in the training set and an accuracy of 86.7% in external test set strains. The BP neutral network offers a highly efficient approach to predict toxigenic phenotype of strains and contributes to hazard detection and safety surveillance.

show abstract

“…Sample pretreatment for toxoflavin extraction was modified from [11] and was as follows. Four grams of sample was added into 36.0 mL CH 3 OH with 1% CH 3 COOH.…”

Section: Uplc Analysis Pretreatmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of Burkholderia gladioli pv. cocovenenans in Black Fungus and Efficient Recognition of Bongkrekic Acid and Toxoflavin Producing Phenotype by Back Propagation Neural Network

Niu,

Song,

Hao

et al. 2024

Foods

View full text Add to dashboard Cite

show abstract

“…UHPLC-Q-TOF/MS allowed for the detection of degradation products. The modified approach led to lower down the limits of detection of toxoflavin and fervenulin to 12 μg/kg and 24 μg/kg, respectively, with recovery of 70.1–108.7% . The MS approach also employed natural phenomena of antigen–antibody interactions for the detection of toxins and related antigens.…”

Section: Recent Advancements In Food Toxin Detection Using Msmentioning

confidence: 99%

“…The modified approach led to lower down the limits of detection of toxoflavin and fervenulin to 12 μg/kg and 24 μg/kg, respectively, with recovery of 70.1–108.7%. 152 The MS approach also employed natural phenomena of antigen–antibody interactions for the detection of toxins and related antigens. Salmonella typhi , Gram-negative enterobacteria, is responsible for typhoid fever and meningitis.…”

Section: Recent Advancements In Food Toxin Detection Using Msmentioning

confidence: 99%

Recent Advances in the Detection of Food Toxins Using Mass Spectrometry

Ahuja,

Singh,

Paul

et al. 2023

Chem. Res. Toxicol.

View full text Add to dashboard Cite

Edibles are the only source of nutrients and energy for humans. However, ingredients of edibles have undergone many physicochemical changes during preparation and storage. Aging, hydrolysis, oxidation, and rancidity are some of the major changes that not only change the native flavor, texture, and taste of food but also destroy the nutritive value and jeopardize public health. The major reasons for the production of harmful metabolites, chemicals, and toxins are poor processing, inappropriate storage, and microbial spoilage, which are lethal to consumers. In addition, the emergence of new pollutants has intensified the need for advanced and rapid food analysis techniques to detect such toxins. The issue with the detection of toxins in food samples is the nonvolatile nature and absence of detectable chromophores; hence, normal conventional techniques need additional derivatization. Mass spectrometry (MS) offers high sensitivity, selectivity, and capability to handle complex mixtures, making it an ideal analytical technique for the identification and quantification of food toxins. Recent technological advancements, such as high-resolution MS and tandem mass spectrometry (MS/MS), have significantly improved sensitivity, enabling the detection of food toxins at ultralow levels. Moreover, the emergence of ambient ionization techniques has facilitated rapid in situ analysis of samples with lower time and resources. Despite numerous advantages, the widespread adoption of MS in routine food safety monitoring faces certain challenges such as instrument cost, complexity, data analysis, and standardization of methods. Nevertheless, the continuous advancements in MS-technology and its integration with complementary techniques hold promising prospects for revolutionizing food safety monitoring. This review discusses the application of MS in detecting various food toxins including mycotoxins, marine biotoxins, and plant-derived toxins. It also explores the implementation of untargeted approaches, such as metabolomics and proteomics, for the discovery of novel and emerging food toxins, enhancing our understanding of potential hazards in the food supply chain.

show abstract

Bacterial panicle blight caused by Burkholderia glumae : a major disease in rice cultivation

Azzahra,

Miranti,

Prismantoro

et al. 2024

Cogent Food & Agriculture

View full text Add to dashboard Cite

Determination of bacterial toxin toxoflavin and fervenulin in food and identification of their degradation products

Cited by 3 publications

References 26 publications

Identification of Burkholderia gladioli pv. cocovenenans in Black Fungus and Efficient Recognition of Bongkrekic Acid and Toxoflavin Producing Phenotype by Back Propagation Neural Network

Identification of Burkholderia gladioli pv. cocovenenans in Black Fungus and Efficient Recognition of Bongkrekic Acid and Toxoflavin Producing Phenotype by Back Propagation Neural Network

Recent Advances in the Detection of Food Toxins Using Mass Spectrometry

Bacterial panicle blight caused by Burkholderia glumae : a major disease in rice cultivation

Contact Info

Product

Resources

About