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4439874075?profile=RESIZE_400xA novel method to identify animal species in complex or adulterated processed meat products has been developed by Chinese researchers, which combines a cytochrome oxidase I (COI) mini-barcode with next-generation sequencing (NGS).  A universal primer based on 140 sequences from 51 edible animal species was designed. A mixture of 12 species raw meat samples (beef, water buffalo, pork, sheep, chicken, partridge, grass carp, silver carp, blue scad, tile fish, pomfret, and prawn) were identified both with the clone sequencing and also with the mini-barcode (136 bp) sequence combined NGS method. The NGS method was superior in accuracy, sensitivity, and detection efficiency compared to the clone sequencing method, The edible animal species were identified both in the mixed raw samples and 7 heavily processed food products (different meatballs - beef, pork, fish, and shrimp), 'modified' beefsteak, sausages, and Chinese sausages. Moreover, some unlabelled species and dubious contamination were also detected as well, leading to stringent cleaning procedures.

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This paper reports the performance of a commercial NGS method that has been evaluated as an untargeted tool to identify meat species. The method was tested on pure meat samples, and all species were correctly identified including several exotic species. Closely related meat species were also correctly differentiated. Species were successfully detected and identified in mixtures down to 1% (w/w). The reliability of the method was further confirmed on several proficiency test samples, and promising quantification data were obtained. Finally, 45 minced meat samples sourced from local European and Asian markets were analysed, and 18% of them showed cases of adulteration with undeclared meat species.

3722359646?profile=RESIZE_710x Read the abstract here

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FSAI has worked with a commercial laboratory (Identigen) over the past two years to adapt NGS (next generation sequencing), so that it can be used as a DNA screening tool to check that the composition of the food matches what is stated on the product’s labelling or descripion. FSAI screened 45 plant-based foods and food supplements from Irish health food shops and supermarkets. It looked for the presence of all plant species in the selected products and identified 14 food products for further investigation that may contain undeclared plant species. Of these 14 products, one was confirmed to contain undeclared mustard at significant levels, which is an allergen that should be declared. Another product (oregano) was found to contain DNA from two undeclared plant species, one at significant levels. A third product was found to have no DNA from the plant species declared on the label, but instead rice DNA was identified. All three products are under further investigation. FSAI will apply the same technology for the screening of meat, poultry and fish products.

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In this study, NGS (next generation sequencing) using the Ion Torrent semiconductor platform was applied to identify meat species in several highly processed and complex meat products and meat derived broths (a döner kebab, a beef/pork paté, a meat based filling of tortellini, one instant granular preparation of broth stock made from meat, and two ready-to-use meat broths from different producers). Sequence analysis of reads from 6 libraries detected expected and unexpected meat species in the products. A measure of poor hygienic practice during production of the analysed products could be inferred using the number of human reads. In conclusion, NGS data is useful for authentication of highly processed products.

Read the abstract at: NGS of meat products

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Honey is a high value food which suffers from food fraud, and it is important to have methods to verify its floral and geographical origin. Italian researchers isolated DNA from nine honeys (six monofloral honeys produced in Italy, two polyfloral honeys produced in East Europe and Chile respectively, and one honeydew honey), and PCR amplified for a chloroplast trnL barcoding fragment. The amplicons were sequenced and the data bioinformatically analysed against a database of 150,000 botanical entries. A total of 254 botanical groups were identified from the nine analysed samples.

The prevalent expected botanical origin was confirmed in five out of six monofloral honeys. The plant signature of the labelled lime tree blossom honey did not confirm the expected botanical prevalence. The botanical composition of monofloral and polyfloral honey samples was useful to infer their geographical origin. 

Read the abstract at: NGS authentication of honey

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