scholarly journals Validation of New ELISA Technique for Detection of Aflatoxin B1 Contamination in Food Products versus HPLC and VICAM

Toxins ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 747
Author(s):  
Elsayed Hafez ◽  
Nourhan M. Abd El-Aziz ◽  
Amira Darwish ◽  
Mohamed Shehata ◽  
Amira Ibrahim ◽  
...  
Keyword(s):  
Aflatoxin B1 ◽  
Polyclonal Antibodies ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Molecular Size ◽  
Food Products ◽  
Food Samples ◽  
Pcr Products ◽  
Contaminated Food ◽  
Elisa Technique

Toxin-contaminated foods and beverages are a major source of illness, may cause death, and have a significant negative economic impact worldwide. Aflatoxin B1 (AFB1) is a potent toxin that may induce cancer after chronic low-level exposure. This study developed a quantitative recombinant AflR gene antiserum ELISA technique for aflatoxin B1 detection in contaminated food products. Aflatoxin B1 residuals from 36 food samples were analyzed with HPLC and VICAM. DNA was extracted from aflatoxin-contaminated samples and the AflR gene amplified using PCR. PCR products were purified and ligated into the pGEM-T vector. Recombinant plasmids were sequenced and transformed into competent E. coli (BL21). Molecular size and B-cell epitope prediction for the recombinant protein were assessed. The purified protein was used to induce the production of IgG antibodies in rabbits. Serum IgG was purified and labeled with alkaline phosphatase. Finally, indirect-ELISA was used to test the effectiveness of polyclonal antibodies for detection of aflatoxin B1 in food samples.

Characterization and Exposure Assessment of Emetic Bacillus cereus and Cereulide Production in Food Products on the Dutch Market

2016 ◽  
Vol 79 (2) ◽  
pp. 230-238 ◽  
Author(s):  
ELISABETH G. BIESTA-PETERS ◽  
SERGE DISSEL ◽  
MARTINE W. REIJ ◽  
MARCEL H. ZWIETERING ◽  
PAUL H. in 't VELD
Keyword(s):  
Bacillus Cereus ◽  
Exposure Assessment ◽  
Food Poisoning ◽  
Food Product ◽  
Food Products ◽  
Food Samples ◽  
Two Samples ◽  
Contaminated Food ◽  
Germination And Growth

ABSTRACT The emetic toxin cereulide, which can be produced by Bacillus cereus, can be the cause of food poisoning upon ingestion by the consumer. The toxin causes vomiting and is mainly produced in farinaceous food products. This article includes the prevalence of B. cereus and of cereulide in food products in The Netherlands, a characterization of B. cereus isolates obtained, cereulide production conditions, and a comparison of consumer exposure estimates with those of a previous exposure assessment. Food samples (n = 1,489) were tested for the presence of B. cereus; 5.4% of the samples contained detectable levels (>102 CFU/g), and 0.7% contained levels above 105 CFU/g. Samples (n = 3,008) also were tested for the presence of cereulide. Two samples (0.067%) contained detectable levels of cereulide at 3.2 and 5.4 μg/kg of food product. Of the 481 tested isolates, 81 produced cereulide and/or contained the ces gene. None of the starch-positive and hbl-containing isolates possessed the ces gene, whereas all strains contained the nhe genes. Culture of emetic B. cereus under nonoptimal conditions revealed a delay in onset of cereulide production compared with culture under optimal conditions, and cereulide was produced in all cases when B. cereus cells had been in the stationary phase for some time. The prevalence of cereulide-contaminated food approached the prevalence of contaminated products estimated in an exposure assessment. The main food safety focus associated with this pathogen should be to prevent germination and growth of any B. cereus present in food products and thus prevent cereulide production in foods.

Enzyme Immunoassay - Membrane Filter Method for Detection of Salmonellae in Foods

1985 ◽  
Vol 48 (9) ◽  
pp. 790-793 ◽  
Author(s):  
JEFFREY M. FARBER ◽  
PEARL I. PETERKIN ◽  
ANTHONY N. SHARPE ◽  
JEAN-YVES D'AOUST
Keyword(s):  
Membrane Filter ◽  
Protein A ◽  
Food Samples ◽  
Filter Method ◽  
Enzyme Linked Immunosorbent Assay ◽  
Salmonella Spp ◽  
Contaminated Food ◽  
Elisa Technique ◽  
Membrane Filter Method ◽  
Exact Correlation

An enzyme-linked immunosorbent assay (ELISA) technique using a horseradish peroxidase-protein A-Spicer Edwards antiserum complex was developed for the detection of Salmonella colonies on membrane filters. In pure culture, 64 Salmonella species tested gave a positive reaction (purple stain). Of 22 naturally contaminated food samples, there was an exact correlation between the AOAC hydrophobic grid-membrane filter procedure and the ELISA technique (40.9% positives). This technique is simple, requires little equipment and can be completed in less than 2.5 h, thus allowing the detection of Salmonella spp. in foods within 48 h from initiation of sampling.

scholarly journals Development and Optimization of Rabbit Polyclonal Antibodies for Cu/ZnSOD detection in Rice (Oryza sativa L.)

2021 ◽  
Author(s):  
Dan Xiong ◽  
Weisong pan ◽  
Biao Luo ◽  
Chuwei Liu ◽  
Ting Zhou ◽  
...  
Keyword(s):  
Oryza Sativa ◽  
Oryza Sativa L ◽  
Polyclonal Antibodies ◽  
Plant Stress ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Leaf Extracts ◽  
Sod Activity ◽  
Asian Rice ◽  
Rabbit Polyclonal Antibody

Abstract Superoxide dismutase (SOD) activity is an important measure of plant stress tolerance used in cultivar improvement. At present, we are unaware of any widely available immunological reagents for the detection of SOD in Oryza sativa (common Asian rice) or other plants. In this study, we used insilico B-cell epitope prediction tools to generate peptides which were immunized into rabbits to yield polyclonal antibodies against Cu/Zn SODs. Immunoblotting demonstrated that the antibody specifically recognized both native and denatured Cu/Zn SODs in rice. In addition, this antibody can confirm the expression tendency of endogenous OsCu/Zn SODs under heat stress by immunoblotting, and has a positive reaction in tomato leaf extracts, as well as human Hela cells. Chloroplast content of Cu/Zn SODs in rice can be identified by ELISA indirect competition method using this antibody. These results suggest that this Cu/Zn SOD rabbit polyclonal antibody may be a useful tool for elucidating the biological functions of Cu/Zn SODs in plants.

scholarly journals The Occurrence of Aflatoxins in Nuts and Dry Nuts Packed in Four Different Plastic Packaging from the Romanian Market

2020 ◽  
Vol 9 (1) ◽  
pp. 61
Author(s):  
Adrian Maximilian Macri ◽  
Ioana Pop ◽  
Daniel Simeanu ◽  
Diana Toma ◽  
Ion Sandu ◽  
...  
Keyword(s):  
Aflatoxin B1 ◽  
Plastic Material ◽  
Storage Conditions ◽  
Aflatoxin Contamination ◽  
Heat Current ◽  
Dried Fruits ◽  
Pistachio Nuts ◽  
Contaminated Food ◽  
Cleanup Procedure ◽  
Elisa Technique

Mycotoxins are secondary metabolites produced by various fungi. A very important category of mycotoxins are aflatoxins, considered to be the most dangerous in humans. Aflatoxin B1, well known as a favorable factor in the occurrence of hepatocellular carcinoma in humans, is the most controversial of all mycotoxins. Aflatoxins, found in naturally contaminated food, are resistant to degradation by heat. Current food processing practices and conventional storage conditions do not completely eliminate aflatoxin contamination from the food supply chain. Long storage food products—such as peanuts, pistachio, nuts in general, and dried fruits—are susceptible to aflatoxins contamination. The type of plastic material can influence the concentration of aflatoxins during storage due to the permeability to gas and moisture exchange with the external milieu. Nuts in general and dried fruits are consumed in large quantities worldwide. Therefore, herein we investigated the effect of plastic material on the total aflatoxins and aflatoxin B1 content in 64 samples of nuts and dried fruits packed and stored in low-density polyethylene (LDPE), polypropylene (PP), polyethylene (PE), and polyethylene terephthalate (PET). The method consisted in a cleanup procedure using immunoaffinity columns coupled with RIDASCREEN FAST immunoenzymatic competitive assays based on the ELISA technique. Collected data were subjected to statistical analysis and multiple comparisons tests were applied. From the total analyzed samples, 14.06% exceeded the maximum admitted European levels for total aflatoxins. The highest concentrations of total aflatoxins were obtained from samples packed in LDPE, followed by PP, PE, and PET. Aflatoxin B1 was detected in all samples packed in LDPE, PP, and PE. Most of the samples packed in PET had concentrations <1 µg/kg. These results indicate that nuts in general packed and stored in LDPE are more prone to contamination with aflatoxins, while PET is more suitable for maintaining the quality and safety of these products.

Recovery tests of cytopathogenic viruses from artificially contaminated food samples

2009 ◽  
Vol 1 (3) ◽  
pp. 191-194
Author(s):  
R. Zoni ◽  
R. Zanelli ◽  
S. Salsi ◽  
M. E. Colucci ◽  
G. Sansebastiano
Keyword(s):  
Food Samples ◽  
Contaminated Food

scholarly journals Data curation to improve the pattern recognition performance of B-cell epitope prediction by support vector machine

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Li Cen Lim ◽  
Yee Ying Lim ◽  
Yee Siew Choong
Keyword(s):  
Pattern Recognition ◽  
Support Vector Machine ◽  
B Cell ◽  
Recognition Performance ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Support Vector ◽  
B Cell Epitopes ◽  
Prediction Module ◽  
B Cell Epitope

Abstract B-cell epitope will be recognized and attached to the surface of receptors in B-lymphocytes to trigger immune response, thus are the vital elements in the field of epitope-based vaccine design, antibody production and therapeutic development. However, the experimental approaches in mapping epitopes are time consuming and costly. Computational prediction could offer an unbiased preliminary selection to reduce the number of epitopes for experimental validation. The deposited B-cell epitopes in the databases are those with experimentally determined positive/negative peptides and some are ambiguous resulted from different experimental methods. Prior to the development of B-cell epitope prediction module, the available dataset need to be handled with care. In this work, we first pre-processed the B-cell epitope dataset prior to B-cell epitopes prediction based on pattern recognition using support vector machine (SVM). By using only the absolute epitopes and non-epitopes, the datasets were classified into five categories of pathogen and worked on the 6-mers peptide sequences. The pre-processing of the datasets have improved the B-cell epitope prediction performance up to 99.1 % accuracy and showed significant improvement in cross validation results. It could be useful when incorporated with physicochemical propensity ranking in the future for the development of B-cell epitope prediction module.

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