DNA-based methodologies in food analysis can detect potential fraud and deter economically motivated adulteration.
The technique allows untargeted detection of organisms with no need for previous knowledge of the supply chain or the species to search for.
At AFNOR (Association Française de Normalisation) a working group was created to explore animal species identification by DNA sequencing methods, focused on NGS. This group (GT10) is led by a SGS molecular expert.
At ISO, SGS employees are involved in the ISO TC34/SC16/WG8 group working on varietal identification and are part of the expert panel of the ISO TC34/SC16/WG8 group relating to meat speciation.
NGS a recognised method for authenticity
Mario Gadanho, SGS molecular business development manager, is the liaison between ISO TC276 (Biotechnology) and ISO TC34/SC16 (horizontal methods for molecular analysis in food) on NGS.
Gadanho said the process of publishing standards takes several years in most cases.
“Therefore, an NGS standard is not expected to be available for another three to five years,” he told FoodQualityNews.
“The method is recognized by industry experts as the most appropriate DNA-based method for species identification in complex food products. Therefore, the introduction of NGS into the SGS portfolio is helping to bring the method to a worldwide audience.”
Gadanho added tests that can distinguish if the organism is dead or alive is a topic under discussion at the SGS Competence Center for future projects.
SGS has developed techniques and technologies to ensure clients know what is in complex food samples.
Routine turnaround time is seven to 10 days but can be reduced to one to two days if needed.
One workflow combines a broad range of short DNA fragments with PCR amplification.
Manufacturing processes like high temperatures and/or pressures used for sterilization can damage DNA and produce very short fragments.
An NGS approach, optimized to work with those short fragments, can avoid false negative results.
Gadanho said most of the fragment sizes used are from 50-150 base pairs, depending on the product to be analyzed.
This enables SGS to use the method for species identification in the most highly processed products.
A technique that is gaining traction
Gadanho said one of the challenges it faces is that NGS is not an officially recognized method.
“However, the expertise of the SGS Molecular team has been recognized internationally by many entities and NGS is presently recognized as the most reliable DNA-based method for species identification,” he said.
“Additionally, several new players are coming to the market with NGS-based approaches which also contribute to international recognition of this method, even in the absence of worldwide harmonization and standardization.”
The firm acquired a 70% stake in Biopremier in late 2016 after a partnership at the start of that year.
Biopremier specialises in molecular biology and DNA sequencing services. Technology is based on NGS which enables species identification of meat, plants, allergens and microorganisms in food.
Gadanho said the deal means SGS customers have access to the most advanced DNA-based technology for authenticity.
At the end of an NGS analysis, millions of individual sequences make it possible to identify species in foods containing multiple ingredients.
Following comparison with databases (containing thousands of species) NGS generates a list of all the species present in a sample, including the scientific name.
Traditionally, methods were based on polymerase chain reaction (PCR) amplification. This kind of targeting requires knowledge about which organism to search for and can be restricted by the range of commercially available test kits.
Results from direct PCR detection only give presence/absence for the targeted species but no additional information such as whether any other species is in the sample.
Whole Genome Sequencing (WGS) is not currently a method routinely used in epidemiological studies, said Gadanho.
“It is mainly used by reference and governmental entities to help clarify the relationship between microbial isolates and to try to establish similarity relationships between isolates that can be useful for comparing the origins of infections. The work involved for bioinformatics on this approach does not fit this type of routine application.”