Barcoding animal species

Abstract

Food Science and TechnologyVolume 34, Issue 4 p. 34-37 FeaturesFree Access Barcoding animal species First published: 11 December 2020 https://doi.org/10.1002/fsat.3404_10.xAboutSectionsPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Bert Popping, Nele Matthes, Gabriele Näumann, Klaus Pietsch, Anke Rullmann and Kathrin Szabo describe the development of tools for food authenticity testing and chart the move from targeted to semi- and untargeted testing methods using DNA barcoding. Introduction In past decades, competent authorities have directed much of their budgets for the surveillance of contaminants in the food supply chain towards mycotoxins, polyaromatic hydrocarbons and heavy metals, as well as residues like pesticides and veterinary drugs. This situation changed in 2008 when melamine was discovered in powdered milk as an adulterant, causing severe adverse health effects and in some cases the death of infants. Only five years later, unlabeled horsemeat in minced beef was uncovered, first in Ireland and subsequently in most other European Member States. Publicity surrounding both these food contamination incidents made consumers, the food industry and governments realise their vulnerability to food fraud and in particular to food adulteration. Some fraudsters have essentially discredited large parts of the food industry and generated uncertainty amongst consumers about the authenticity of different foods. The sale of meat in the UK dropped by 3% following the horsemeat scandal1, representing a value of approximately £80m (~€87m)2; sales of minced beef products decreased by more than 7%. The melamine and horsemeat scandals were followed in 2016 by a Sudan Dye adulteration incident, in which group-3 carcinogenic azo dyes were discovered in paprika powder. These dyes were used to embellish the appearance of the spice by increasing colour intensity. It became very apparent that there was a need for the food industry, as well as the governments, to improve monitoring of the food supply chain and products in the marketplace for potential adulteration and to require suppliers and manufacturers to undertake vulnerability assessments to guard against food fraud. In 2014, the European Parliament's resolution Food crisis, fraud in the food chain and the control thereof3 proposed establishing an EU reference laboratory for food authenticity. It stated that ‘official controls should focus not only on food safety issues, but also on preventing fraud and the risk of consumers being misled’ and in 2017, this led to the Official Controls Regulation4. In addition to analytical activities, the European Commission has established the Administrative Assistance and Cooperation5, which allows the informal exchange of information between European Union (EU) Member States in cases of suspected fraud, and the European Commission Knowledge Center for Food Fraud and Quality6 (p24). This two-tear system combines data analysis with the development of analytical detection systems. Some fraudsters have essentially discredited large parts of the food industry and generated uncertainty amongst consumers about the authenticity of different foods. The need for improved analytical systems While the combination of data analysis and development of analytical detection systems is valuable, one of the challenges in monitoring food fraud is the number of possible adulterants per product category. Olive oil, according to a European Parliament report7, is the most frequently adulterated product in which 52 different adulterants8 have been found. For meat, the number of adulterants identified is 78 and for milk 163. These numbers only include adulterants for which food products have been tested. Individual analysis and detection of all possible adulterants in these products is not economically feasible. This is why scientists have developed a different approach to monitoring adulteration, which moves from exclusiveness to inclusiveness, meaning that individual adulterants are not measured, but the profile of a product is compared to a reference profile. If the product profile is within the range of the reference profile, the likelihood of the product being adulterated is significantly lower. If the profile (or parts thereof) is outside the range of the reference profile, it could indicate adulteration of the product. These types of analyses are called non-targeted or untargeted. Since 2008, the year of the melamine crisis, the number of non-targeted methods published has increased almost exponentially (Figure 1). Figure 1Open in figure viewerPowerPoint PubMed Query (‘non-targeted’ or ‘untargeted’) on 2020-09-25 One of the challenges in monitoring food fraud is the number of possible adulterants per product category. Abbreviations AAC-FF EU Administrative Assistance and Cooperation System and the Food Fraud Network BaTAnS Barcoding Table of Animal Species BVL German Federal Office for Consumer Protection and Food Safety CEN European Committee for Standardisation NGS Next Generation Sequencing PCR polymerase chain reaction SMPR standard method performance requirements The underlying technologies for monitoring adulteration methods range from infrared spectrometry (NIR, FT-IR, RAMAN) to Nuclear Magnetic Resonance and High-Resolution Accurate Mass. One of the challenges faced by these methodologies is that performance criteria that allow easy evaluation of their fitness-for-purpose are not well developed. Here, AOAC International (an independent, third party, not-for-profit association and voluntary consensus standards developing organisation) broke new ground by establishing a food fraud taskforce9, which developed standard method performance requirements (SMPR) for targeted and untargeted food chemistry methods10. These SMPRs have been approved by the stakeholders and will shortly be published in the Journal of AOAC International11. However, at this point in time, SMPRs have not been developed for untargeted DNA-based methods. This will be the next step for which a new working group has been established at the recent annual meeting of AOAC. Relevance of DNA-based methods In the past, numerous methods for species analysis have been developed and a number have become standards as a result of several EU CEN working groups (for example TC460 WG2 ‘Species analysis using DNA-based methods’ or TC275 WG 12 ‘Food allergens’) focusing on detection methods for species identification, including allergens. However, since many different types of plant and animal species12 are being used for adulterating foods, single-target polymerase chain reaction-based, and even multiplex methods, are of limited use. These methods are not capable of detecting the whole range of animal or plant species that could possibly be used for adulteration of a product, which can sometimes even include the use of murine species. Consequently, the detection of animal species has become increasingly important. The most recent annual report of The EU Food Fraud Network and the Administrative Assistance and Cooperation (AAC-FF) System of the European Commission13 shows the top categories of animal species for which administrative assistance was requested (Figure 2). Figure 2Open in figure viewerPowerPoint Number of AAC-FF requests in 2019 per product category. The sum of requests related to products of animal origin (94) exceed those of any other category, demonstrating the importance of having appropriate methods to analyse samples in this segment. Since 47% of these requests were dedicated to ‘Mislabeling’ and 20% to ‘Replacement/Dilution/Addition/Removal in Product’, it is clear that there is a need for methods to identify animal species in such foods. In order to detect adulterations, DNA-based methods have been evaluated in several actions coordinated by the EU as in the case of the illegal trade of the European eel. Development of non-targeted and semi-targeted DNA methods Next Generation Sequencing (NGS) technologies are becoming a new gold standard to investigate foods for the presence of unknown or unexpected species. NGS methods are particularly useful in identifying all species in a mixed food matrix, like seafood mixes, where seafood species for adulteration are unknown or exotic. However, these metabarcoding methods are still fairly complex, time-consuming and costly when it comes to the identification of animals or plants. Therefore, a semi-targeted approach is often chosen, saving both time and cost while still being straightforward in terms of species diagnosis. In this approach, DNA sequences common to eukaryotes, particularly animals, are used for PCR (polymerase chain reaction) amplification and subsequent analysis of the DNA sequence. Sequences of the cytochrome b (cyt b) gene or cytochrome c oxidase subunit 1 (cox1, COI) are commonly used. These both occur in the mitochondria of eukaryotes playing a key role in the respiratory chain and are therefore relatively conserved across the animal kingdom. Analysis of other sequences of the mitochondrial genome can also be valuable and sometimes highly conserved nuclear genes are also used, like sequences of the myosin heavy peptide 6 (myh6) gene. The conservation of these genes makes it possible to amplify DNA sequences of a large range of animal species using only a limited set of primers. Highly variable regions in these genes that are often specific to a certain animal species are used for differentiation of samples at the species level. This approach is described as DNA barcoding and many methods with different sets of primers have been described in the literature. The challenge with these methods is often that the validation of the primers may not be sufficiently comprehensive, since in some cases certain animal species are not recognised by a certain primer set, and in others, unrelated species are recognised. Additionally, it is not economical to validate all primer sets that are used or may be developed in the future in competent laboratories dealing with DNA barcoding for species identification in food and feed. This gap makes such methods difficult to use by private laboratories and certainly by the competent authorities when judging results and reporting them in a courtroom-safe manner. BaTAnS tool To address this challenge, a subgroup of the official working group for the validation and standardisation of molecular biology methods for plant and animal species differentiation of the German Federal Office for Consumer Protection and Food Safety (BVL) has developed a new tool called BaTAnS, an acronym for Barcoding Table of Animal Species. The initiative, led by Nele Matthes and supported by the secretary of the working group, Kathrin Szabo, collected validation data on current popular methods used for barcoding of animal species, predominantly from Germany. In the BaTAnS tool, the validation data are compiled together with the method parameters (primer sequences, length of the amplicon, source, available national or international standard, supplementary information etc.) as well as the specificity of the primers. The latter is a key parameter since it determines which species the method is capable of detecting. For a method to qualify, it needs to be successfully validated in at least two competent laboratories. After that, it can be added to the BaTAnS library of methods. Already validated specificity data are categorised for the different animal taxa: Amphibia, Aves, Crustacea, Insecta, Mammalia, Mollusces, Pisces and Reptilia, and provide information about which primer set is able (or not) to identify which animal species at genus or species level. This new tool will be updated as further information becomes available for DNA barcoding of animal species. Therefore, it contains both a method submission sheet and a sheet for error reporting. To add a new method or new validation data to existing methods, the submission data sheet requests all information needed, like the method parameters and which species can or cannot be identified using the new method. Additionally, the names of at least two laboratories that have verified the data are requested. Since this tool contains a lot of different data for the identification of all animal taxa, mistakes may occur while adding data; the error reporting sheet provides an opportunity to correct these mistakes. An error will be corrected if two competent laboratories have identified it and verified the correct entry. The method submission sheet, as well as the error reporting sheet, contains a contact e-mail address, where proposals for new entries or methods can be directed. The aim is to keep BaTAnS up-to-date with the current state of DNA barcoding. The BaTAnS tool will help private and competent authority laboratories to select appropriate methods, the results of which can be defended in court. The tool can be downloaded from the BVL website14 and is also available as additional material to the peer-reviewed article.15 The BaTAnS tool will help private and competent authority laboratories to select appropriate methods, the results of which can be defended in court. Conclusions Food adulteration has come a very long way since the Code of Hammurabi16 was written into stone 3800 years ago: from the simple dilution of wine with water to the addition of melamine to milk powder. But so have detection methods for food adulteration. Scientists are constantly striving to develop better and more appropriate or sensitive detection methods and the recent development of non-targeted and semi-targeted methods represents a turning point in the detection of food adulteration. Yet, much still needs to be done to harmonise and standardise these methods. For barcoding, the BaTAnS tool has made a significant contribution to allowing scientists to identify appropriate, fit-for-purpose methods. The next step will be the AOAC initiative to develop SMPRs for DNA-based methods to provide further guidance. However, testing for food adulteration is always only one piece of a puzzle. Supply chain traceability, big data analysis (e.g. for mass balance assessment) and analytical control all need to be integrated to demonstrate the efficiency of the implemented measures. This should lead to a restoration of consumer trust in the food industry and government control authorities alike. Bert Poppinga, Nele Matthesb, Gabriele Näumannc, Klaus Pietschd, Anke Rullmanne, Kathrin Szabof Corresponding author email bert.popping@focos-food.com a FOCOS – Food Consulting Strategically, Zum Kälterhaus 6b, 63755 Alzenau, Germany b State Office for Agriculture, Food Safety and Fishery Mecklenburg-Vorpommern, Thierfelderstraße 18, 18059 Rostock, Germany c Institute for Hygiene and Environment Hamburg, Markmannstr. 129b, 20539 Hamburg, Germany d State Institute for Chemical and Veterinary Analysis Freiburg, Bissierstr. 5, 79114 Freiburg, Germany e State Institute for Chemical and Veterinary Analysis Karlsruhe, Weissenburgerstr. 3, 76187 Karlsruhe, Germany f Federal Office of Consumer Protection and Food Safety, Mauerstr. 39-42, 10117 Berlin, Germany References 1Butler, S., Smithers, R. 2014. Horsemeat scandal results in slide in sales of red meat in Britain. The Guardian. 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