Elsevier

Food Research International

Volume 113, November 2018, Pages 407-413
Food Research International

Untargeted metabolomics reveals differences in chemical fingerprints between PDO and non-PDO Grana Padano cheeses

https://doi.org/10.1016/j.foodres.2018.07.029Get rights and content

Highlights

  • The untargeted profile of PDO and non-PDO Grana Padano cheeses was investigated.

  • Multivariate statistics discriminated samples from both productions.

  • Lipids, oligopeptides and plant-derived compounds were the best discriminants.

  • Untargeted metabolomics could be a valuable tool for PDO cheeses authenticity.

Abstract

The purpose of this preliminary study was to discriminate the chemical fingerprints of Protected Designation of Origin (PDO) Grana Padano cheeses from non-PDO “Grana-type” cheeses by means of an untargeted metabolomic approach based on ultra-high-pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometer (UHPLC/QTOF-MS). Hierarchical cluster analysis and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) allowed discriminating PDO vs. non-PDO cheeses. Lipids (fatty acids and their derivatives, phospholipids and monoacylglycerols), amino acids and oligopeptides, together with plant-derived compounds were the markers having the highest discrimination potential.

It can be postulated that Grana Padano value chain, as strictly defined in the PDO production specification rules, can drive the biochemical processes involved in cheese making and ripening in a distinct manner, thus leaving a defined chemical signature on the final product.

These preliminary findings provide the basis for further authenticity studies, aiming to protect the designation of origin of PDO Grana Padano cheese by applying a comprehensive foodomics-based approach.

Introduction

Grana Padano (GP) is a famous and highly exported hard-textured, cooked and long-ripened traditional Italian cheese exhibiting typical sensorial and physico-chemical characteristics. From a dietary perspective, GP cheese is considered a highly nutritional food, since 100 g of GP contain on average 390 kcal, 33 g of protein and 28 g of fat. Further, it is also a natural source of minerals (e.g., calcium, zinc and phosphorus) and vitamins (e.g., vitamin A and vitamin B12) (www.granapadano.it, 2017). With a production of >4.8 million cheeses wheels in 2016 (about 184,000 tons), GP is one of the most popular Italian cheese (www.granapadano.it, 2017).

The Protected Designation of Origin (PDO) trademark is assigned to agro-food products that are strictly related to a defined geographical area where both raw materials originate, and their transformation take place (Mazzei & Piccolo, 2012). In particular, according to the Disciplinary of Production (Council Regulation, 2012), GP cheese can be exclusively produced using raw Italian dairy cow milk, partially skimmed by natural surface skimming (Neviani, Bottari, Lazzi, & Gatti, 2013). Accordingly, the area of production of GP cheese is widely extended Northern Italy, including several provinces in Piedmont, Lombardy, Veneto, Emilia Romagna and Trentino-Alto Adige (Mulas, Anedda, Longo, Roggio, & Uzzau, 2016).

However, GP cheese intrinsic values, along with consumers demand and its high market price, make it a remunerative target for either misappropriate and unlawfully PDO sales. Consequently, there is the need to develop robust and accurate methods to verify PDO GP cheese authenticity, aiming to protect both product values and consumers (Granato et al., 2018). Foods and ingredients presenting high quality and nutritional values, such as PDO GP cheeses, are the most vulnerable for adulteration. In particular, the most common strategies adopted by defrauders are the addition of additives, such as aromas, to improve the value of counterfeit products or the utilization of cheaper ingredients/substances (Kamal and Karoui, 2015). For what concerns certified dairy products, the adulteration phenomena could include the mixing of different types of milk during the production, the utilization of toxic and harmful compounds or the illegal labelling of determined foods. Furthermore, other factors such as animal feeding, processing conditions or packaging should be also considered.

In the last years, some analytical approaches have been carried out to distinguish genuine PDO from other similar “Grana-type” cheeses, by focusing on few aspects of the traditional cheese-making process (Cattaneo et al., 2008; Gori, Maggio, Cerretani, Nocetti, & Caboni, 2012). Among these different approaches, the metabolomics-based approach represents a powerful method to discriminate different or fraudulent varieties of a given food product, being capable to identify a “molecular fingerprint” that accurately represents the food of interest (Castro-Puyana, Pérez-Míguez, Montero, & Herrero, 2017). Metabolomics includes the exhaustive study of the whole small metabolite (<1500 Da) composition of a particular system or organism, by means of fingerprinting or profiling (Wishart, 2008). In this regard, chromatography coupled to mass spectrometry-based metabolomics approaches (both LC-MS and GC-MS) followed by multivariate statistics are promising, since they are able to provide the level of accuracy needed for food traceability purposes, considering both geographical origin assessments and changes in the food metabolic profiles after a particular food process (Esslinger, Riedl, & Fauhl-Hassek, 2014; Rocchetti et al., 2018; Rocchetti, Giuberti, & Lucini, 2018). These analytical platforms have been employed above all to highlight differences in cheese metabolome during ripening (Le Boucher et al., 2015), or to identify new markers of silage feedings for cheeses (such as PDO GP) (Caligiani, Nocetti, Lolli, Marseglia, & Palla, 2016). In other works, Mazzei and Piccolo (2012) and Pisano, Scano, Murgia, Cosentino, and Caboni (2016) applied a metabolomics-based approach to assess the quality and traceability of “mozzarella cheese”, another typical Italian dairy product.

However, scarce information exists regarding the untargeted and comprehensive screening of markers able to discriminate PDO GP cheese from counterfeits or adulterations available on the market. This may be of concern since, during 2014, unfair trade practices, counterfeiting, improper use of the PDO or other illegal practices in the production, transformation or marketing of GP cheese were estimated to account for about 1 billion euro (www.granapadano.it, 2014).

Therefore, an untargeted metabolomics approach has been applied in this preliminary work with the aim of characterizing low-molecular weight metabolites able to reveal differences between genuine PDO GP cheeses from similar non-PDO “Grana-type” cheeses. In particular, the use of a metabolomics approach is expected to provide a much deeper investigation of the actual composition of these food products, as compared to classical targeted approaches.

Section snippets

Cheese samples

Ten commercial samples of genuine PDO GP cheeses (16 months of ripening) were gratefully donated by the Grana Padano Protection Consortium (Desenzano Del Garda, BS, Italy), whose PDO production is officially recognized by the Italian Ministry of Agricultural and Forestry Policies (MIPAF). Additionally, 10 similar portioned non-PDO grated “Grana-type” cheeses, all within the expiration date, were purchased from local or abroad retailers located in Europe. Each sample was contained inside an

Untargeted screening and evaluation of discriminant metabolites in cheese samples

An untargeted metabolomics-based approach was used to comprehensively screen and profile low-molecular-weight compounds in different cheese samples, through UHPLC-ESI/QTOF-MS analysis. In particular, a wide variety of chemical classes was annotated using the database Metlin. Overall, a total of 1902 compounds could be annotated across samples; however, recursive analysis and subsequent filtering in Mass Profiler Professional dramatically reduced the number of compounds in the dataset (775

Conclusions

An untargeted metabolomic approach based on ultra-high-pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometer (UHPLC/QTOF-MS), followed by multivariate statistics, was carried out to discriminate PDO Grana Padano from non-PDO “Grana-type” cheeses according to their chemical fingerprints. Both the unsupervised hierarchical cluster analysis (HCA) and the supervised Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) allowed discriminating PDO

Conflict of interest

The authors declare no conflict of interest.

The following are the supplementary data related to this article.

. Whole dataset of identified compounds being in 66% of samples within at least one treatment (either PDO and non PDO cheeses), with individual abundances and composite spectra (mass-abundance combinations).

Acknowledgements

GR was the recipient of a Ph.D. fellowship from the Università Cattolica del Sacro Cuore (UCSC, Piacenza, Italy). The authors wish to thank the Grana Padano Consortium for kindly providing cheese specimens and the “Romeo ed Enrica Invernizzi” foundation for supporting the metabolomic platform.

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