Review on recent DNA-based methods for main food authentication

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Review

Review on recent DNA-based methods for main food authentication topics Karola Böhme, Pilar Calo-Mata, Jorge Barros-Velázquez, and Ignacio Ortea J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b07016 • Publication Date (Web): 22 Mar 2019 Downloaded from http://pubs.acs.org on March 24, 2019

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Journal of Agricultural and Food Chemistry

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Review

on

recent

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authentication topics

DNA-based

methods

for

main

food

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Karola Böhmea, Pilar Calo-Mataa, Jorge Barros-Velázqueza, Ignacio Orteab*

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aDepartment

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Compostela, E-27002 Lugo, Spain.

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bProteomics

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of Analytical Chemistry, Nutrition and Food Science, University of Santiago de

Unit, Maimonides Institute for Biomedical Research (IMIBIC), E-14004

Córdoba, Spain.

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* Corresponding author: [email protected]

13 14 15 16 17 18 19 20 21 22 23 24

ACS Paragon Plus Environment

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ABSTRACT

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Adulteration and mislabeling of food products, and the commercial fraud derived, either

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intentionally or not, is a global source of economic fraud to consumers, but also for all

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stakeholders involved in food production and distribution. Legislation has been enforced all

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over the world aimed at guaranteeing the authenticity of the food products all along the

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distribution chain, therefore avoiding food fraud and adulteration. Accordingly, there is a

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growing need for new analytical methods able to verify that all the ingredients included in a

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foodstuff match the qualities claimed by the manufacturer or distributor. In this sense, the

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improved performance of most recent DNA-based tools in term of sensitivity, multiplexing

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ability, high-throughput and relatively low cost, give them a game changer role in food

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authenticity-related topics. Here, we provide a thorough and updated vision on the recently

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reported approaches that are applying these DNA-based tools to assess the authenticity of

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food components and products.

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KEY WORDS

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DNA; food authentication; food fraud; foodomics; next-generation sequencing; DNA

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barcoding; PCR.

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INTRODUCTION

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Food adulteration, either intentionally or not, is a global source of economic fraud to

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consumers, but also for all stakeholders involved in food production and distribution. Since

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most counterfeiting incidents do not cause a health harm, most of them keep undetected. It is

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estimated that food fraud imply more than 40 billion dollars of yearly loss to the food

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industry.1,2 Furthermore, the possible introduction of non-declared ingredients that might

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cause allergic reactions in sensitized individuals have important safety implications.3

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Legislation has been enforced all over the world aimed at guaranteeing the authenticity of the

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food products all along the distribution chain, therefore avoiding mislabeling and food fraud

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and adulteration.4,5 To comply with these regulations, there is an increasing need for analytical

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methods that allow us to verify and assure that all the ingredients included in a foodstuff match

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the qualities and features claimed by the manufacturer or distributor.

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A wide variety of analytical methodologies have been applied to food authentication

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studies. Although pioneer techniques, such as liquid chromatography, electrophoretic

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profiling, and sensory analysis are still commonly used, the addition of new DNA-related

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techniques to the catalogue of available food assays, are surpassing limitations of those earlier

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methodologies.6 Although enzyme-linked immunosorbent assay (ELISA) is still one of the

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most frequently applied technique, the higher specificity, molecule stability and sensitivity

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due to the amplification power of polymerase-chain reaction (PCR), makes DNA a perfect

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target molecule for food authenticity purposes, allowing the detection of mislabelling and

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food fraud even at trace levels and in processed foodstuffs.7

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Current challenges associated with food authenticity were defined by Ortea et al.8 (Figure

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1). The identification, detection and quantification of a certain species in a food product or

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ingredient is the area of highest activity, but other food authentication topics such as variety

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identification, production method, undeclared additions, component proportion and


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geographical origin have also great importance since they are a source for mislabeling and

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commercial fraud.

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The substitution of an animal or plant species of high commercial value by a

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cheaper/lower-quality one is a common fraud in the food industry, including all branches from

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meat, seafood, dairy products to food of plant origin, such as oil and juices. Accordingly,

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elevated mislabeling levels have been continuously published: e.g. 57% in processed meat

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products and 42.8% in fish fillets sold in Italy,9,10 up to 35% in meat products sold in US,11

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24.4% in prawns and shrimps12 and up to 80% in dairy products.13 Meat is particularly

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susceptible for fraudulent substitution by less valuable meat or meat coming from domestic

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animals. In addition, the presence of rat, dog and cat meat in food products may represent

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substantial threats to public health besides ethical reasons and has been objective of several

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studies in the last years. Likewise, food products of plant origin, such as dietary supplements

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and spices, are common products exposed to frauds, due to the substitution of the

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corresponding plant species. In these cases, the mixed formulations in form of powder make

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authentication especially challenging. Undeclared species substitution in food products might

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also represent an important health threat to allergic consumers, related to the introduction of

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food allergens, such as different kinds of nuts and molluscs.

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Consequently, many of the studies published in the food authentication field are related to

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species identification and discrimination. In this regards, developed DNA-based methods

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have included DNA sequencing, restriction fragment length polymorphism (RFLP),

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Randomly Amplified Polymorphic DNA (RAPD), multiplex-PCR, quantitative PCR (qPCR)

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and Simple Sequence Repeats (SSR) or microsatellites.7,14 In the last years, new techniques

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have started to be assessed for food authenticity purposes. New tools such as high resolution

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melting (HRM) PCR, droplet digital PCR (ddPCR), isothermal amplification (e.g. loop-

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mediated isothermal amplification (LAMP), recombinase polymerase amplification, strand


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displacement amplification, helicase-dependent amplification, rolling circle amplification)

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and next-generation sequencing (NGS) are starting to show they are able to overcome the

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performance of those prior methods in terms of specificity, sensitivity, speed and

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multiplexing.

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Besides species discrimination, food authenticity also requires the identification of a

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certain animal breed or plant variety or cultivar, and the assessment of the origin of a food

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component. Quality standards such as the Protected Designation of Origin (PDO) label

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created by the EU, could greatly benefit from methodologies that can trace the food ingredient

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or product to a specific geographical region. In this sense, DNA-based methods can only be

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used when the geographic difference is related to genetic diversity, which must be studied at

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the intra-species level, targeting many loci to achieve sufficient diversity and allowing

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classification of the studied populations.

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In a recent review, we compiled a broad but brief report of the proteomics, metabolomics

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and genomics approaches used for food authentication purposes.15 Here, we offer a much

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thorough vision focusing on the recently reported DNA-based approaches –the area of highest

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scientific activity within the field of food authentication, including techniques recently

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incorporated to the catalogue, but also those more classical techniques that are still used–

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providing an updated and comprehensive overview of the recent (2014-2019) applications to

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assess the authenticity of food components and products.

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PCR AND qPCR

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PCR has been proposed as a useful technique for the detection and identification of animal

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and plant species in foods, because of the high sensitivity and specificity, in addition of being

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relatively fast and not costly. Multiplexed PCR assays allow the simultaneous identification

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of several species by using species-specific primers, and are being extensively applied to the


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detection and differentiation of the species present in food products. The exponentially

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amplification of a target DNA molecule by use of a thermal cycler, generates up to millions

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of copies and allows the detection of a target in a complex matrix at very low concentrations.16

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Even though, the usefulness of the PCR assay depends to a great extent on the quality and

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quantity of the targeted DNA. Mitochondrial DNA is often selected for sensitive qualitative

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assays, due to its high cell copy number. In this sense, multiplex PCR assays, targeting

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mitochondrial regions, have been developed to simultaneously detect different animal species

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in meat, showing detection sensitivities down to 1pg DNA.17–20

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Likewise, meat from dog, rat, rabbit and squirrel could be identified in meatballs down to

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0,1% of adulteration.21,22 Nevertheless, since copy number per cell changes between species,

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individuals and even tissues within the same individual, makes mitochondrial genes

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unsuitable for quantification. Accordingly, in the cases where quantification is required to

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assure food authenticity, nuclear genes are more appropriate.23

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Quantitation of a certain species in a food product (e.g. animal species used in a meat

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product) is a critical issue and common concern, since it is necessary to verify an intentional

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or unintentional mixing, as the horse meat scandal proved.6 Accordingly, qPCR has turned

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out to be especially convenient, being the method of choice for the quantitative assessment of

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adulteration in mixed food products. In qPCR, nucleic acids are amplified, real-time

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monitored and quantified by measuring the fluorescence coming from the release of a double-

144

strand DNA binding dye, measured in each PCR cycle.24 qPCR performance surpasses

145

traditional techniques in sensitivity, multiplexing, speed and cost. Since it is based on real-

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time monitoring of the increasing number of target DNA molecules, the post-PCR processing

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steps of conventional PCR are avoided.

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Several works have been published, aimed at the development of qPCR assays for the

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simultaneous detection of different animal species in game meat and the quantification of four


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deer species amount.25–28 Likewise, the presence of forbidden meat species (e.g. pork) in raw

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and processed Halal products have been studied by qPCR.29,30 Regarding seafood, qPCR

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systems have been recently applied to specifically detect fraud or mislabelling in tuna

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products.31 Detection of fraud and mislabelling of dairy products has also been the aim of

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developed multiplex qPCR assays.32–34

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In this sense, it should be mentioned that qualitative detection of a certain species in a food

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products can be carried out down to very low concentrations, because of the high specificity

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of the targeted DNA regions. Nevertheless, absolute or relative quantification has some

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limitations, mainly due to the effects of tissue composition or matrix components over the

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PCR efficiency and precision.35

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In some cases, qPCR assays allow estimation rather than an exact quantification of the

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content and ratios of the different animal or plant species, as described for example in fruit

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juices containing different ratios of mandarin and orange juice in the samples.36 Due to the

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high sensitivity and specificity of qPCR-based approaches, their application to food

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authenticity where traces have to be detected has been frequently described. Special efforts

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have been made in the detection and quantification of low levels of allergens, such as

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hazelnut.37

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Recently, a new performance of PCR has been developed, named digital droplet PCR

168

(ddPCR). ddPCR consists on the massive partitioning of the amplification reaction into

169

nanoliter size samples which are encapsulated into oil droplets, in order to carry out one PCR

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on each individual droplet.38 ddPCR outperforms qPCR in sensitivity and precision,

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measuring the targeted DNA content with no need for standard curves. This technique has

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been successfully applied to the authentication and quantitation of meat species.39

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A main objective of research in the field of food control and authenticity is to dispose of a

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technology that allows point-of-care food analysis. In this sense, the combination of PCR-


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based approaches with other technologies, such as microfluidics, biosensors or

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nanotechnology gained special interest for on-site applications. Furutani et al.40 used a

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portable qPCR system to detect beef, pork, chicken, rabbit, horse and mutton in processed

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foods, achieving correct species identification in 20 min. Lin et al.41 reported an approach,

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based on species-specific probes targeting the cytochrome c oxidase subunit 1 (COI) gene

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combined with flow-through hybridisation detection, for the multiplexed identification of

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multiple meat species. Since this assay is fast and relatively cheap, it could be suitable as a

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routine test. Wang et al.42 described an optical thin-film biosensor test that can monitor and

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distinguish up to eight meat species down to 0.001% by a colour change that is perceivable

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by naked eye. An interesting methodology described by Kitpipit et al.43 allowed the detection

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of six common meat species by PCR amplification directly on the sample, avoiding the

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previous step of DNA extraction. In another study, an ultra-fast method based on convection

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Palm PCR of the cyt b gene was used for meat identification, with high potential for on-site

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applications.44 Detection of the targeted species could be carried out using either singleplex

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or multiplex procedures in 24 minutes, since this approach avoids the need for ramping

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between temperatures as for standard PCR, and limits down to 1% of meat adulteration and 1

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pg DNA were achieved.

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Taboada et al.45 developed a species-specific 4-plex PCR system coupled with detection

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by a lateral flow dipstick (LFD) assay for the in-situ screening of two cod species, pollock

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and ling, in seafood products. LFD proved to be particularly useful because its portability and

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simplicity, allowing a naked-eye monitoring of the results. A similar detection multiplex PCR

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method, in this case using gel-based detection of the amplification products, was reported to

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differentiate between five edibe or potentially edible jellyfish species.46

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Recent representative studies applying standard PCR and qPCR to food authentication are shown in Table 1.


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DNA BARCODING AND NEXT-GENERATION SEQUENCING

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DNA barcoding, consisting on sequencing and comparing orthologous DNA regions for

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taxonomic identification, has been proposed as a standardized method for species (and other

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taxa) authentication.47 DNA barcoding, either by using conventional Sanger DNA sequencers

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or NGS technologies, represents an important progress in food species identification and

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traceability.48 A challenge of DNA-barcoding is the search for the “perfect” gene that presents

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low variability within a certain taxa but also a high level of inter-species variability. Therefore,

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the detection of a region conserved in several species can allow their identification. The most

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targeted genes for species discrimination are COI and cytochrome b (cytb) for animal species

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and the maturase K (matK) and carboxylase gene (rbcL) for plant species. The advantage of

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these genes of mitochondrial and plastid DNA is the higher number of copies present in the

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cells, making them the selected genes in most qualitative approaches, such as DNA barcoding,

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where a high sensitivity is required to detect the corresponding species at low

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concentrations.23

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PCR amplification of standard-length (around 650 bp) barcodes in moderate/highly

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processed and preserved products is challenging, due to DNA degradation. In this sense, mini-

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barcoding approaches, focusing on shorter DNA fragments (100-200 bp), have been

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successfully tested for the authentication of fish products achieving a 93% success rate (vs.

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20.5% when a standard-length barcode was used).49

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In the last years, the global project Barcode of Life Data System (BOLD) put much effort

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to create public databases of barcodes for all species of life. Special attention is given to plant

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species and fish and seafood, due to the high similarity in DNA sequences of closely related

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species. In comparison to meat, diversity of edible seafood and plant species is very high and

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discrimination between similar individuals results challenging, especially in processed food


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products. In many cases, a high percentage of mislabelling could be detected by barcode

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analysis, being unclear if the fraud has been either intentionally or accidently, due to the high

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similarity of the species. The Fish Barcode of Life Initiative (FISH-BOL), is a public library

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of standardised reference sequences for all fish species, aimed at the unequivocal

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discrimination and identification. In this sense, DNA barcoding has been successfully applied

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to detect frauds and mislabelling in the seafood sector, including fresh, frozen and processed

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products.50–56

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The authenticity of food additives and supplements of plant origin is another field of raising

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concern for consumers, highlighting the need for accurate methods to assure the quality.

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Nevertheless, the efforts to create reference sequence libraries for plant species discrimination

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result more challenging due to the absence of a unique barcode candidate. Recently, a number

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of different genes have been studied as possible markers for the discrimination of plant species

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by barcoding.57,5858 DNA barcoding has been applied to authenticity purposes in plant-related

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food additives,59 poisonous plants,60 herbal infusions61 and spices such as tumeric.62 In a

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similar study, small quantities of up to ten different plant oils could be detected in olive oil by

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a DNA barcode assay together with PCR-capillary electrophoresis.63 In another study, DNA

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barcoding succeed in detecting as low as 1% of berry fruits added to fruit juices.64

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Plant and entomological origin of honey greatly affects its properties and quality. DNA

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barcoding showed to be able to identify the plant origin in honey by targeting different plastid

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regions. Up to 39 different plant species could be identified in honey samples.65 In a similar

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study, DNA barcoding, using three different genes, provided information not only on the

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botanical origin of honey, but also on the honeybee species producing a specific honey

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(entomological origin).66 The authors also discussed the difficulties found when analysing

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honeys with high content of polyphenolic compounds or subjected to crystallization.


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Recently, DNA barcoding approaches have been integrated into high-throughput

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sequencing formats (formerly next-generation sequencing, NGS), demonstrating high

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potential for the simultaneous identification of species of animal and plant origin in food

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products. NGS, which has revolutionised genomic research, is able to sequence millions of

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small DNA fragments in parallel.67 In this sense, NGS is much faster and higher throughput

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than Sanger sequencing, since it does not require post-reaction steps and the detection is real-

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time. The combination of DNA barcoding and pyrosequencing technologies have been

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successfully used for the authentication of fish and seafood species68–70 and meat species71 in

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processed food products. Likewise, the animal species of milk origin could be detected in

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dairy products, including the detection of undeclared species and human DNA, being the latter

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one an indicator for the hygienic level of the food products.72 Qualitative detection of the milk

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producing species could be carried out down to very low concentrations.

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HRM

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HRM is a rapid high-throughput technique that allows genotyping and sequence matching

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(and therefore differentiation of taxa) according to the Tm of specific DNA amplicons which

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reflects genetic variations.73 This post-PCR method uses a fluorescence intercalating DNA

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dye that allows monitoring dsDNA denaturing as temperature increases. Resolving power of

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HRM relies on sequence divergence, and therefore, even a few base-pair differences alter the

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melting curve, discrimination of species is challenging when the analysed DNA sequences

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are very similar. HRM has succeed in the simultaneous detection of up to eight different

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animal species in meat with 0.1 ng DNA detection limit.74 In a similar study, this time related

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to entomological authentication of honey, honeybee species were identified by analysing

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honey samples.75


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Another recently developed methodology is the combination of HRM with DNA

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barcoding, termed Bar-HRM, which has proved a great potential when used for species and

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subspecies differentiation.76 The method consists on designing HRM specific primers based

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on the sequences derived for the barcoding markers. Bar-HRM has the advantage over DNA

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barcoding that it allows quantitative measurements and at the same time it surpass the

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resolving power of conventional melting curve analysis.77 Bar-HRM was reported to

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differentiate the five most commercially-relevant shrimp species, achieving an identification

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accuracy above 99%.78 The same methodology was applied for discriminatiing five hake

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species, a group of highly appreciated fish which are prone to be adulterated.79 Two out of 45

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commercial products analyzed with the developed method showed mislabeling or species

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substitution. Adulteration of Chinese commercial sea buckthorn products, an ancient crop,

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has also been studied by Bar-HRM.80 Five out of ten commercial products tested showed

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either adulteration or contamination with species different from those specified in the

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labelling. A similar mislabelling rate (e.g. 48.5%) was found when analysing commercial

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curry powders with a Bar-HRM developed for identifying seven Zingiberaceae curry

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species.81 The combination of HRM and DNA barcoding has also been applied to the

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authentication of wines.82 In this study, 13 grapevine varieties could be differentiated in musts

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and wines. This method, apart from identifying the fruit variety used, could be useful also for

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protecting PDO wines.

292 293

LAMP

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Recently, a nucleic acid amplification technique named LAMP, has started to be used with

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food authentication purposes. As PCR and qPCR, LAMP detects specific DNA sequences,

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but it can target up to eight different sequences. The LAMP method uses self-recurring strand-


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displacement DNA synthesis, replicating a target DNA at constant temperature and avoiding

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the lengthy steps of PCR amplification.83

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Regarding the introduction of food allergens in foodstuffs, it has been applied to the

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quantification of peanut.84 A LAMP assay has also been used in a method for detecting the

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addition of five vegetables not allowed in Chinese vegetarian diets (e.g. leek, several onion

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varieties and garlic) to other plant ingredients.85 LAMP has some advantages over previous

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techniques, such as the naked-eye result observation, although the use of intercalating

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fluorescence dyes allows real-time tracking. Additionally, there is no need for a thermal

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cycler, since the reaction is performed at isothermal conditions, and therefore it facilitates on-

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site detection. The sensitivity of LAMP has been found to be higher than PCR in some

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cases.84,85 However, real-time LAMP (qLAMP) has showed lower sensitivity than qPCR

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when used for monitoring and quantifying gluten in wheat and corn samples (limits of

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detection 0.0015 ng/L and 0.15 ng/L for qPCR and qLAMP, respectively).86 Regarding milk

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adulteration, as low as 5 % addition of cow milk could be detected in buffalo milk using

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LAMP.87

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Regarding the assessment of halal claims, qLAMP and the combination of LAMP and

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electrochemiluminescence (ECL) sensors, targeting pork specific DNA, have achieved

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detection limits as low as 0.01 % of pork in beef meat and 0.1 pg/µL pork DNA content,

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respectively.88,89 The LAMP-ECL sensor, apart from showing a high sensitivity, could be

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incorporated into a compact, simple and rapid (around 5 min for detection) biosensor useful

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for on-site food authentication assessment. The simultaneous detection of eight different meat

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species has also been described by a LAMP assay.90 Regarding the development of on-site

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applications, a specific LAMP reaction was combined with a LFD to develop a rapid testing

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biosensor able of detecting down to 10 pg of mammalian species DNA.91

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CLASSICAL DNA MARKERS

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Classical DNA markers widely used in population genetics studies, such as microsatellites,

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RAPD, amplified fragment length polymorphism (AFLP), RFLP, sequence-characterized

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amplified regions, and more recently, single-nucleotide polymorphisms (SNPs),

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demonstrated to be very useful also for the authentication of food products, and several

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reviews have appeared in the past focusing on their application to food authenticity

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assessment.3,7,92,93 Actually, RFLP, combined to PCR, is one of the molecular-based methods

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that are commonly available at analytical facilities for species identification in foodstuffs.

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Nevertheless, since these techniques are generally less sensitive and selective and more

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laborious, they became less interesting when DNA-barcoding arose. However, PCR-RFLP

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has been widely used for the identification of the species present in seafood products, and this

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technique is still applied. In RFLP, target DNA, after PCR amplification, is digested using

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enzymes and the resulting restriction profiles are monitored by gel electrophoresis, so the

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profiles of different samples can be compared.94 Five tuna species, nine different snapper

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species and 16 commercial sea cucumber species have been recently discriminated by PCR-

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RFLP, targeting mitochondrial regions.95–97 An RFLP approach was also used for detecting

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as low as 0.01% cat meat content in mixtures and meatballs.98 In spite of being one of the

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techniques most frequently used, RFLP analyses, and the other classical DNA markers, suffer

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from an unsuitability for obtaining reliable quantitative information. Moreover, since the

341

analysis is based on fingerprint-like amplification patterns that may be compared to reference

342

samples, they are difficult to standardize.

have

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Besides species identification, discrimination between different cultivars and varieties is

344

important in some foods of plant origin. In that sense, different cocoa and sugarcane cultivars

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have been assessed through microsatellite markers, with the aim to differentiate varieties or

346

cultivars.99,100 Microsatellites or SSR consist on simple repeat sequences along the genome,


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characterized by a short (2-8 basepairs) DNA sequence that is repeated up to 100 times.101

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Microsatellite markers have been used to identify local varieties of barley orzo Agordino.102

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Microsatellites are highly polymorphic markers that have revealed useful for detecting intra-

350

population difference, such as the one produced by geographical divergence. In this regard,

351

different geographical origins of sesame seeds and oil could be discriminated using DNA

352

microsatellite markers.103

353

A SNP is a DNA sequence variation at a single position, and therefore SNP analysis allows

354

the differentiation of phylogenetically closely related specimens, having proved very useful

355

for diagnosis of human diseases.104 Since the analysis focuses on single nucleotide changes

356

instead of the whole sequences, this methodology is especially indicated for the identification

357

of very similar cultivars or breeds. In this regard, SNP genotyping on a suspension of

358

fluorescence-encoded microspheres has been used for the identification of five Greek olive

359

oil cultivars.105 Table 2 compiles recent studies that have used these classical DNA markers

360

for food authentication.

361 362

CONCLUDING REMARKS AND FUTURE TRENDS

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Consumers, governments and the food industry demand a strict control and monitoring of

364

food labeling and authenticity, assuring food quality and safety. The analytical methods used

365

for assessing food authenticity may fulfill several requirements, apart from being accurate and

366

reliable: sensitive, due to the often low amount of target DNA, which is frequently highly

367

fragmented; highly specific, able to differentiate between DNA molecules presenting

368

minimum differences; multiplexing capability, in order to perform the identification of several

369

features in parallel in the same analysis; high-throughput and low analysis time, so many

370

samples can be analyzed in less time. In this sense, recently-developed technologies such as

371

NGS, DNA-metabarcoding, Bar-HRM, LAMP and ddPCR are surpassing classical methods.


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We anticipate that the combination of techniques such as digital PCR and LAMP with micro-

373

and nano-fluidic systems and novel nanobiosensor systems will significantly improve the

374

performance of DNA-based methodologies.106–108 Biosensors based on nanoparticles are

375

attracting great interest in the last years. Since they allow analytical platforms massively

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parallel, portable and avoiding sample preparation (or highly reducing it), nanoparticles are

377

already being incorporated to food applications, such as the detection of allergenic and

378

toxicant compounds,109,110 and even food authentication.111 Since food samples frequently

379

contain fragmented DNA and minute concentrations, new sample preparation protocols, able

380

to deal with these trace-level DNA amount, will also be needed. In this sense, the use of

381

microfluidic devices and nanoparticles is already improving DNA recovery and extraction

382

process from complex food matrices.112,113

383

Besides advances in technologies and instrumentation, method development, validation

384

and harmonization issues have to be addressed in terms of assuring the validity of the future

385

studies, previously to the implementation of the developed methods in the industry: (i) all the

386

possible sources of variability, such as changes caused by intra-species differences or food

387

processing, should have to be controlled; (ii) power analysis should be performed to check

388

statistical validity of the results; (iii) inter-laboratory comparisons should be addressed in

389

order to guarantee that comparable analytical results are provided; (iv) certified reference

390

materials and operation procedures should be developed and made available for method

391

standardization.

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743 744 745 746


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747

FIGURE CAPTIONS

748

Figure 1. Current challenges associated with food authenticity and main DNA-based

749

technologies that are being used to study them. Adapted from Ortea et al. (2016),

750

doi:10.1016/j.jprot.2016.06.033, available under the Creative Commons Attribution License

751

(CC BY) (https://creativecommons.org/licenses/by/4.0/). Bar-HRM, DNA barcoding high-

752

resolution melting; ddPCR, droplet digital PCR; HRM, high resolution melting; LAMP, loop-

753

mediated isothermal amplification; NGS, next-generation sequencing; PCR, polymerase

754

chain reaction; PDO, protected designation of origin; qPCR, real-time PCR; RFLP, restriction

755

fragment length polymorphism.

756


31


757

Page 32 of 37

TABLES

758 759

Table 1. Recent representative studies applying standard PCR and qPCR to food authentication Food group Meat

Purpose of analysis

Main Technique

Ref.

COI gene

17

Cyt b, COI and 12S rRNA genes

43

Duplex PCR

mtDNA sequence

18

Multiplex PCR with optical microarray biosensor

mt DNA regions

42

ddPCR

Nuclear gene

39

0.01-50% mixtures of minced cooked beef, pork, and horsemeat.

Cyt b gene

44

Raw beef, lamb, and pork meat samples from Korean markets.

PCR + specific hybridisation

COI gene

41

Meat samples from dog, dog, mouse, horse, pork, lamb and beef.

Multiplex PCR

Cyt b and ATP6 genes

21

81 reference rabbit, squirrel and rat meat samples.

Mitochondrial genes

19,20

Reference meat samples (pork, chicken, turkey, partridge, pheasant, wild duck and quail).

Binary mixtures (0.01-20%), and 18 commercial samples

0.01% addition of each of the species.

Mitochondrial D-loop region

29

34 pork meat and blood samples from local markets.

Cooked, autoclaved, and microoven cooked pork samples. Selectivity: 23 other animal species.

10 pg pig DNA; 0.1% pork content in meat mixtures.

Cyt b gene

22

Ternary mixtures and cooked meatballs, plus 10 other animal and three plant species.

Commercial meatballs (five halal brands).

0.1% (in ternary mixtures), 0.2% (in cooked meatballs) dog meat.

Multiplex PCR

Multi-species detection

Convection PCR

Discrimination of rabbit, squirrel and rat meat Authentication traditional products

Palm

of meat

Detection/quantification of pork meat adulteration Detection of dog meat adulteration

Target species and type of samples tested Reference meats of horse, beef, mutton, pork, dog, chicken and mice.

Target

Species-specific PCR assays

F2

Reference meats of chicken, beef, pork, horse, mutton and ostrich, Meat samples from eight species (goat, sheep, deer, buffalo, cattle, yak, pig and camel). Meat samples from deer, rabbit, duck, chicken, beef, horse, sheep, and pork from local Chinese supermarkets.


Validation

Detection limits

Binary pork-mutton meat mixtures, and processed foods 115 processed foods from Thailand markets. Specificity: 13 other animal species. 170 commercial meat products. Specificity: nine other animal species.

1 pg DNA, 0.05% (pork content in mixtures).

Five retail samples for validation. Calf liver sausages and processed meat products. Specificity 14 other species and 49 different breeds. Thermally processed samples and processed food products (ham and sausage). Specificity: 10 other mammal or bird species. 72 meatball samples. Stability: boiled, autoclaved and micro-oven cooked samples.

7 fg. 6-20 pg. 0.5 pg deer/beef DNA, 0.001% (w/w) deer/beef. 0.001%. 1 pg DNA; 1% meat adulteration. 5 pg DNA. 0.01 ng DNA in pure meat samples and 0.1% in meatballs.

32

Page 33 of 37


COI gene

40

Ground meat samples of beef, pork, chicken, rabbit, horse, and mutton.

Binary mixtures (chicken meat in pork) and four commercial processed foods (hamburgers, nugget, and sausage).

0.1% chicken content in a processed food.

Determination of deer content in meat products

MC1-R gene; kappa-casein precursor gene

27,28

Game meat obtained from Austrian institutions.

Mixtures, model game sausages, and processed foods. Specificity: 19 animal and 50 plant species.

0.1% (fallow deer), 0.3% (sika deer).

Detection of pork and horse meat adulteration

12S and 16S rRNA genes

30

Specificity: six different meat and six plant species.

0.0001% horse and 0.001% pork meat in model sausages.

31 commercial fish products from local markets (22.58% mislabeling found).

50 pg DNA.

Multi-species detection

Seafood

Fruit juices

Model pasteurized sausages (with beef, chicken, soybean proteins and additives) with different proportion of horse and pork meat. Two cod species (Gadus morhua, n=15, and G. macrocephallus, n=7), Pollock (n=15) and ling (n=15), 17 specimens of other fish species.

Detection of cod, Pollock and ling in seafood products

4-plex PCR + LFD

Cyt b gene

45

Identification jellyfish species fishery products

Pentaplex PCR

COI gene

46

57 jellyfish reference samples.

78 market samples.

-

qPCR

16S rRNA gene and mitochondrial control region

31

Reference samples from five appreciated tuna species (Thunnus maccoyii, T. obesus, T. albacares, T. alalunga, and Katsuwonus pelamis), and other five tuna or tuna-like species.

Mislabeling was found in 5 out of 9 commercial samples assessed.

-

32

Cow, buffalo, goat, and sheep milk and meat were used.

33

Reference cow, buffalo, sheep, and goat milks from farms.

Identification tuna species Milk and dairy products

Portable qPCR

of

of in

five

Detection of cow, buffalo, sheep, and goat milk in dairy products Detection of cow, buffalo, sheep, and goat milk in dairy products Detection of cow and horse milk in dairy products Detection of mandarine in orange juice

4-plex qPCR Cyt b and 12S rRNA genes Multiplex qPCR 3-plex qPCR

12S gene

rRNA

qPCR

trnL-trnF intergenic region

34

36

Cow milk, mare milk, yogurt, koumiss, and sour soup (n=5 each) from Mongolia. Leaves from nine orange and 13 mandarin commercial varieties, model juices from one orange and one mandarin variety.

28 commercial samples (cheeses, yogurts, creams). Sensitivity and accuracy: binary mixture cheeses. Binary mixtures and 18 commercial dairy samples (milks and cheeses). Meat samples (beef, horse, mutton, pork, chicken, duck, goose, dog, rabbit, cat, and carp). Two commercial juices.

multi-fruit

1% cow DNA in milk mixes and cheeses. 1%. 1 pg (cow milk, yogurt, mare milk); 5 pg (sour soup, koumiss). 5% mandarine in orange juice.

760

ddPCR, droplet digital polymerase chain reaction; EGF, epidermal growth factor; LFD, lateral flow dipstick; mtDNA, mitochondrial DNA; PCR,

761

polymerase chain reaction ; qPCR, real-time polymerase chain reaction.


33


762

Page 34 of 37

Table 2. Summary of the application of recent classical DNA markers to food authentication. Food group Meat

Seafood

Main Technique

Purpose of analysis Detection of adulteration

cat

meat

Differentiation snapper species

of

nine

Lab-on-a-Chip RFLP assay

RFLP assay

Differentiation of 16 sea cucumber species Differentiation of five tuna species Plant origin

Differentiation varieties

of

cocoa

Validation

Other details

Cyt b gene

98

Cat meat samples (three specimens).

Binary and ternary mixtures and meatballs. Specificity: nine other animal and seven plant species.

Detection limit: 0.01% feline meat

Mitochondrial D-loop region

95

24 specimens from each nine snapper species in several processing forms.

20 commercial samples.

16S rRNA gene

96

Parvalbumin and cyt b genes

97

Ref.

10 nuclear SSRs

99

12 SSRs

100

Identification of local varieties of Agordino barley

Seven SSR loci

102

Differentiation among different geographical origins of sesame oils

Nine nuclear and one chloroplast SSR

103

Three SNPs

105

Differentiation of Brazilian sugarcane cultivars

Oils

RFLP and SSCP assays

Target species and type of samples tested

Target

Identification of Greek olive oil cultivars

Microsatellite marker analysis

SNP genotyping by fluorescent microspheres

16 sea cucumber species (6 fresh specimens each). 27 fish samples from five Thunnus and other scombrids from Indian and Pacific Oceans. Eight CCN-51 cocoa leaf (n=8) and bean (n=2) samples, together with Arriba cocoa (n=2) and Criollo cocoa (n=2) leaf samples. 137 genotypes from 81 Brazilian commercial sugarcane cultivars and 56 germplasm accessions, leaves or leaf roll tissue. 60 samples of the Italian barley landrace Agordino, together with 35 samples from 21 other commercial varieties from the Veneto region. 38 sesame seed samples from different countries (from Europe, Africa, Asia, and America) and the oil derived from them. Monovarietal olive oil samples, leaves and fruits from five common Greek olive cultivars.

19 frozen and commercial products.

dried

Tuna fillets from Germany.

-

-

Two out of the nine species could not be distinguished. 48% mislabeling found. Differences were found between the three varieties, and even within CCN-51 samples. 285 allele markers found could distinguish the genetic cultivar and germplasm accessions.

-

-

-

-

-

-

763

cyt b, cytochrome b; DL, detection limits; RFLP, restriction fragment length polymorphism; rRNA, ribosomal RNA.; SNP, single-nucleotide

764

polymorphism; SSCP, single-strand conformation polymorphism; SSR, simple sequence repeats.


34

Page 35 of 37

765


FIGURE GRAPHICS

766 767

Figure 1.

768

769 770 771 772 773 774 775 776 777 778


35


779

Page 36 of 37

Graphic for table of contents

780 781 782 783 784


36

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qPCR Species authentication

FOOD AUTHENTICITY

Variety/cultivar identification

DNA barcoding ACS Paragon Plus Environment

Review on recent DNA-based methods for main food authentication

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