Stone Pine (Pinus pinea L.) High-Added-Value Genetics: An Overview.

Stone pine (Pinus pinea L.) has received limited attention in terms of genetic research. However, genomic techniques hold promise for decoding the stone pine genome and contributing to developing a more resilient bioeconomy. Retrotransposon and specific genetic markers are effective tools for determining population-specific genomic diversity. Studies on the transcriptome and proteome have identified differentially expressed genes PAS1, CLV1, ATAF1, and ACBF involved in shoot bud formation. The stone pine proteome shows variation among populations and shows the industrial potential of the enzyme pinosylvin. Microsatellite studies have revealed low levels of polymorphism and a unique genetic diversity in stone pine, which may contribute to its environmental adaptation. Transcriptomic and proteomic analyses uncover the genetic and molecular responses of stone pine to fungal infections and nematode infestations, elucidating the defense activation, gene regulation, and the potential role of terpenes in pathogen resistance. Transcriptomics associated with carbohydrate metabolism, dehydrins, and transcription factors show promise as targets for improving stone pine's drought stress response and water retention capabilities. Stone pine presents itself as an important model tree for studying climate change adaptation due to its characteristics. While knowledge gaps exist, stone pine's genetic resources hold significant potential, and ongoing advancements in techniques offer prospects for future exploration.

Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements.

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.

Authentication of incense (Pittosporum undulatum Vent.) honey from the Azores (Mel dos Açores) by a novel real-time PCR approach.

'Mel dos Açores' is a unique nectar honey produced from the exceptional and diverse flora of the Azores archipelago, categorised as incense honey ('mel de incenso') or multifloral honey ('mel multiflora'). Incense honey should contain over 30 % of pollen grains of Pittosporum undulatum Vent. In this work, a real-time PCR method targeting the ITS region was proposed for the first time to detect P. undulatum in the honey from the Azores. The approach exhibited high analytical performance, achieving a quantification limit of 0.01 pg of incense DNA. The method was successfully applied to 22 honey samples, from which incense was detected in all 9 monofloral incense honeys and in 5 out of 10 multifloral samples from the Azores. Generally, the quantitative results for incense DNA were in good agreement with the melissopalynological data. Therefore, a simple, cost-effective and reliable tool was herein proposed to authenticate and valorise the Azores honey.

Authentication of Argan (Argania spinosa L.) Oil Using Novel DNA-Based Approaches: Detection of Olive and Soybean Oils as Potential Adulterants.

Argan oil is a traditional product obtained from the fruits of the argan tree (Argania spinosa L.), which is endemic only to Morocco. It is commercialized worldwide as cosmetic and food-grade argan oil, attaining very high prices in the international market. Therefore, argan oil is very prone to adulteration with cheaper vegetable oils. The present work aims at developing novel real-time PCR approaches to detect olive and soybean oils as potential adulterants, as well as ascertain the presence of argan oil. The ITS region, matK and lectin genes were the targeted markers, allowing to detect argan, olive and soybean DNA down to 0.01 pg, 0.1 pg and 3.2 pg, respectively, with real-time PCR. Moreover, to propose practical quantitative methods, two calibrant models were developed using the normalized ΔCq method to estimate potential adulterations of argan oil with olive or soybean oils. The results allowed for the detection and quantification of olive and soybean oils within 50-1% and 25-1%, respectively, both in argan oil. Both approaches provided acceptable performance parameters and accurate determinations, as proven by their applicability to blind mixtures. Herein, new qualitative and quantitative PCR assays are proposed for the first time as reliable and high-throughput tools to authenticate and valorize argan oil.

Single-tube nested real-time PCR versus normalised real-time PCR for the quantification of allergenic cashew nut in foods: Impact of thermal processing and matrix.

In this work, three allergen-encoding genes (Ana o 1, Ana o 2, Ana o 3) were investigated for the detection of cashew nut as an allergenic food. Normalised and single-tube nested real-time PCR approaches targeting the Ana o 2 or Ana o 3 genes are proposed and compared. Normalised real-time PCR detected 10 pg, while single-tube nested real-time PCR achieved 1 pg of cashew nut DNA. Single-tube nested real-time PCR targeting Ana o 3 allowed the best relative sensitivities (10 mg/kg cashew nut in dough/biscuit), being successfully validated regarding precision/accuracy. The normalised real-time PCR did not show acceptable accuracy for both targets. Sensitivity of single-tube nested real-time PCR was affected by the matrix (pasta), but not by thermal processing (dough/biscuit). Herein, two highly sensitive and specific single-tube nested real-time PCR targeting allergen-encoding genes are proposed for the first time as quantitative/validated tools for cashew nut analysis as an allergenic food.

Botanical authentication of globe artichoke-containing foods: Differentiation of Cynara scolymus by a novel HRM approach.

Cynara scolymus L., known as globe artichoke, is a medicinal plant widely used in plant food supplements (PFS) and herbal infusions due to its beneficial health properties. The high demand for artichoke-containing products can lead to adulteration practices. In this work, a real-time polymerase chain reaction (PCR) system coupled to high-resolution melting (HRM) analysis was proposed to differentiate C. scolymus from other Cynara species. Hence, a Cynara-specific real-time PCR assay was successfully developed with high analytical performance, achieving a sensitivity of 0.4 pg of globe artichoke DNA. HRM analysis enabled the discrimination of C. scolymus, with a high level of confidence (>98%), corroborating sequencing data. Application results to artichoke-containing PFS and mixed herbal infusions allowed confirming the presence of C. scolymus in 38% of the samples, suggesting the substitution/mislabelling of globe artichoke in 2 samples and the need for further efforts to increase DNA amplifiability of PFS.

High-Resolution Melting Analysis as a Tool for Plant Species Authentication.

High-resolution melting (HRM) analysis is a cost-effective, specific, and rapid tool that allows distinguishing genetically related plants and other organisms based on the detection of small nucleotide variations, which are recognized from melting properties of the double-stranded DNA. It has been widely applied in several areas of research and diagnostics, including botanical authentication of several food commodities and herbal products. Generally, it consists of the main steps: (1) in silico sequence analysis and primer design; (2) DNA extraction from plant material; (3) amplification by real-time PCR with an enhanced fluorescent dye targeting a specific DNA barcode or other regions of taxonomic interest (100-200 bp); (4) melting curve analysis; and (5) statistical data analysis using a specific HRM software. This chapter presents an overview of HRM analysis and application, followed by the detailed description of all the required reagents, instruments, and protocols for the successful and easy implementation of a HRM method to differentiate closely related plant species.

Botanical origin authentication of dietary supplements by DNA-based approaches.

Herbal products, such as dietary supplements, have become a subject of increasing global importance for their health benefits and economic considerations. However, they have also been targets of adulteration practices, being the accurate identification of botanicals in herbal products of utmost importance to protect the health and expectations of consumers. Particularly, in the case of dietary supplements, which can have different types of formulations, the identification of plant material used in their production is often a research challenge. DNA-based techniques have played a crucial role on the development of a wide range of tools for the authentication of herbal products. Therefore, this review intends to describe their main progresses, critically discussing their advantages and drawbacks when applied to authenticate herbal products, focusing on dietary supplements. DNA barcoding is particularly emphasized because it has provided the highest number of applications, followed by the advances on high-resolution melting analysis combined with DNA barcodes. A special emphasis is also given to the promising approaches relying on DNA metabarcoding and isothermal amplification.

Machine Learning Approaches Applied to GC-FID Fatty Acid Profiles to Discriminate Wild from Farmed Salmon.

In the last decade, there has been an increasing demand for wild-captured fish, which attains higher prices compared to farmed species, thus being prone to mislabeling practices. In this work, fatty acid composition coupled to advanced chemometrics was used to discriminate wild from farmed salmon. The lipids extracted from salmon muscles of different production methods and origins (26 wild from Canada, 25 farmed from Canada, 24 farmed from Chile and 25 farmed from Norway) were analyzed by gas chromatography with flame ionization detector (GC-FID). All the tested chemometric approaches, namely principal components analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and seven machine learning classifiers, namely k-nearest neighbors (kNN), decision tree, support vector machine (SVM), random forest, artificial neural networks (ANN), naïve Bayes and AdaBoost, allowed for differentiation between farmed and wild salmons using the 17 features obtained from chemical analysis. PCA did not allow clear distinguishing between salmon geographical origin since farmed samples from Canada and Chile overlapped. Nevertheless, using the 17 features in the models, six out of the seven tested machine learning classifiers allowed a classification accuracy of ≥99%, with ANN, naïve Bayes, random forest, SVM and kNN presenting 100% accuracy on the test dataset. The classification models were also assayed using only the best features selected by a reduction algorithm and the best input features mapped by t-SNE. The classifier kNN provided the best discrimination results because it correctly classified all samples according to production method and origin, ultimately using only the three most important features (16:0, 18:2n6c and 20:3n3 + 20:4n6). In general, the classifiers presented good generalization with the herein proposed approach being simple and presenting the advantage of requiring only common equipment existing in most labs.

Authentication of Ginkgo biloba Herbal Products by a Novel Quantitative Real-Time PCR Approach.

Ginkgo biloba is a widely used medicinal plant. Due to its potential therapeutic effects, it is an ingredient in several herbal products, such as plant infusions and plant food supplements (PFS). Currently, ginkgo is one of the most popular botanicals used in PFS. Due to their popularity and high cost, ginkgo-containing products are prone to be fraudulently substituted by other plant species. Therefore, this work aimed at developing a method for G. biloba detection and quantification. A new internal transcribe spacer (ITS) marker was identified, allowing the development of a ginkgo-specific real-time polymerase chain reaction (PCR) assay targeting the ITS region, with high specificity and sensitivity, down to 0.02 pg of DNA. Additionally, a normalized real-time PCR approach using the delta cycle quantification (ΔCq) method was proposed for the effective quantification of ginkgo in plant mixtures. The method exhibited high performance parameters, namely PCR efficiency, coefficient of correlation and covered dynamic range (50-0.01%), achieving limits of detection and quantification of 0.01% (w/w) of ginkgo in tea plant (Camellia sinensis). The quantitative approach was successfully validated with blind mixtures and further applied to commercial ginkgo-containing herbal infusions. The estimated ginkgo contents of plant mixture samples suggest adulterations due to reduction or almost elimination of ginkgo. In this work, useful and robust tools were proposed to detect/quantify ginkgo in herbal products, which suggests the need for a more effective and stricter control of such products.

Towards honey authentication: Differentiation of Apis mellifera subspecies in European honeys based on mitochondrial DNA markers.

Honey is the natural sweet substance produced by Apis mellifera honeybees in Europe. Depending on the country/region, the A. mellifera subspecies native to Europe belong to three different lineages: A (A. m. iberiensis), M (A. m. iberiensis and A. m. mellifera) and C (A. m. ligustica and A. m. carnica). In this work, two DNA-based approaches were developed with the aim of entomological authentication of European honeys. A cytb specific PCR assay was proposed to identify A-lineage honeybees, while a second method based on real-time PCR coupled to high resolution melting analysis targeting the COI gene was developed to differentiate C- and M-lineages honeybees. The proposed methodologies were validated successfully with honeys of known origin and applied to the entomological authentication of 20 commercial samples from different European countries. The results highlight the predominance of honeys from C-lineage honeybees in Europe, except in Iberian Peninsula countries (honey from A-lineage honeybees).

Novel diagnostic tools for Asian (Apis cerana) and European (Apis mellifera) honey authentication.

Honey can be produced by different species of honeybees, with two being of economic importance due to their use in apiculture, namely Apis mellifera (known as European honeybee) and Apis cerana (known as Asian honeybee). Due to the decline of the wild populations of the Asian honeybee, this honey generally attains much higher market value, being prone to adulteration. This work aims at proposing new tools, based on the use of molecular markers, for the entomological authentication of honey. To this end, new species-specific primers were designed targeting the tRNAleu-cox2 intergenic region and allowing the detection of A. cerana DNA by qualitative polymerase chain reaction (PCR). Additionally, a novel real-time PCR method with high resolution melting analysis was developed to target the 16S rRNA gene of both bee species, allowing their discrimination in different clusters. The proposed methodologies were further applied with success in the authentication of Asian and European honey samples by the identification of honeybee DNA, demonstrating the usefulness of these simple and cost-effective new approaches.

Peptide selection and antibody generation for the prospective immunorecognition of Cry1Ab16 protein of transgenic maize.

The introduction of genes isolated from different Bacillus thuringiensis strains to express Cry-type toxins in transgenic crops is a common strategy to confer insect resistance traits. This work intended to extensively in silico analyse Cry1A(b)16 protein for the identification of peptide markers for the biorecognition of transgenic crops. By combining two different strategies based on several bioinformatic tools for linear epitope prediction, a set of seven peptides was successfully selected as potential Cry1A(b)16 immunogens. For the prediction of conformational epitopes, Cry1A(b)16 models were built on the basis of three independent templates of homologue proteins of Cry1A(a) and Cry1A(c) using an integrated approach. PcH_736-746 and PcH_876-886 peptides were selected as the best candidates, being synthesised and used for the production of polyclonal antibodies. To the best of our knowledge, this is the first attempt of selecting and defining linear peptides as immunogenic markers of Cry1A(b)-type toxins in transgenic maize.

Seasonal change in main alkaloids of jaborandi (Pilocarpus microphyllus Stapf ex Wardleworth), an economically important species from the Brazilian flora.

Pilocarpus microphyllus Stapf ex Wardleworth (jaborandi, Rutaceae) is one of the most important Brazilian medicinal species owing to its content of pilocarpine (PIL), an alkaloid used for treating glaucoma and xerostomia. This species contains another alkaloid, epiisopiloturine (EPI), which has demonstrated effectiveness against schistosomiasis. The aim of this work was to assess seasonal changes of PIL and EPI in three populations of cultivated P. microphyllus from northeastern Brazil over one year, including the dry and rainy seasons. Alkaloid profiles were correlated to phenotypic and genetic patterns in the morphological and molecular characterizations. PIL was the primary alkaloid and its levels differed among populations in all months except September. The S01 population (green line) showed an especially high PIL content compared to populations S02 and S03 (traditional line), which had similar alkaloid contents. PIL content gradually decreased in the three populations in the rainy season.EPI content was significantly different between the green line (S01) and the traditional line (S02 and S03).S01 had a significantly lower EPI content in all months, demonstrating that it was not the best source for EPI extraction. Inter simple sequence repeat (ISSR) markers and morphological analyses clearly separated S01 from S02 and S03, in agreement with the alkaloid results. This study shows the first correlation between the chemical, morphological, and molecular markers of P. microphyllus and highlights the potential benefits of a multidisciplinary research approach aimed at supporting both industry and conservation of natural resources.

Matrix-normalised real-time PCR approach to quantify soybean as a potential food allergen as affected by thermal processing.

The addition of soybean protein materials to meat products is a common practice in the food industry, being a potential hidden allergenic commodity. This study aimed at proposing a novel specific and highly sensitive real-time PCR system for the detection/quantification of soybean as an allergenic ingredient in processed meat products. The method achieved a limit of detection of 9.8pg of soybean DNA (8.6 copies), with adequate real-time PCR performance parameters, regardless of the soybean material (concentrate or isolate) and after thermal treatments. A normalised approach was also proposed in the range of 0.001-10% (w/w) of soybean material in pork meat, which was successfully validated and applied to processed meat products. Soybean was identified in more than 40% of tested samples of cooked ham and mortadella in the range of 0.1-4% (w/w), 3 samples not complying with labelling regulations as a result of undeclared soybean.