Improving DNA isolation from honey for the botanical origin identification

Establishment of rapid extraction and sensitive detection system of trace corn syrup DNA in honey

Honey adulteration with exogenous syrup has become a common phenomenon, and current detection techniques that require large instruments are cumbersome and time-consuming. In this study, a simple and efficient method was developed by integrating the rapid extraction of nucleic acids (REMD) and recombinase polymerase amplification (RPA), known as REMD-RPA, for the rapid screening of syrup adulteration in honey. First, a rapid extraction method was developed to rapidly extract corn syrup DNA in five minutes to meet the requirements of PCR and RPA assays. Then, the RPA method for detecting endogenous maize genes (ZssIIb) was established, which could detect 12 copies/μL of the endogenous maize gene within 30 min without cross-reacting with other plant-derived genes. This indicated that the RPA technique exhibited high sensitivity and specificity. Finally, the REMD-RPA detection platform was used to detect different concentrations of corn syrup adulteration, and 1 % adulteration could be detected within 30 min. The 22 commercially available samples were tested to validate the efficacy of this method, and the established RPA was able to detect seven adulterated samples in less than 30 min. Overall, the developed method is rapid, sensitive, and specific, providing technical support for the rapid field detection of honey adulteration and can serve as a reference for developing other field test methods.

Using pollen DNA metabarcoding to trace the geographical and botanical origin of honey from Karangasem, Indonesia

The unique floral fingerprint embedded within honey holds valuable clues to its geographical and botanical origin, playing a crucial role in ensuring authenticity and detecting adulteration. Honey from native Apis cerana and Heterotrigona itama bees in Karangasem, Indonesia, was examined utilizing pollen DNA metabarcoding for honey source identification. In this study, we used ITS2 amplicon sequencing to identify floral DNA in honey samples. The finding reveals distinct pollen signatures for each bee species. Results analysis showed A. cerana honey generated 179,267 sequence reads, assembled into Amplicon Sequence Variants (ASVs) with a total size of 485,932 bp and an average GC content of 59 %. H. itama honey generated 177,864 sequence reads, assembled into ASVs with a total size of 350,604 bp and an average GC content of 57 %. A. cerana honey exhibited a rich tapestry of pollen from eleven diverse genera, with Schleichera genus dominating at an impressive relative read abundance of 72.8 %. In contrast, H. itama honey displayed a remarkable mono-dominance of the Syzygium genus, accounting for a staggering 99.95 % of its pollen composition or relative read abundance, highlighting their distinct foraging preferences and floral resource utilization. Notably, all identified pollen taxa were indigenous to Karangasem, solidifying the geographical link between honey and its origin. This study demonstrates pollen DNA metabarcoding may identify honey floral sources. By using pollen profiles from different bee species and their foraging patterns, we may protect consumers against honey adulteration and promote sustainable beekeeping in Karangasem district. Future research could explore expanding the database of reference pollen sequences and investigating the influence of environmental factors on pollen composition in honey. Investigating this technology's economic and social effects on beekeepers and consumers may help promote fair trade and sustainable beekeeping worldwide.

An innovative molecular approach towards the cost-effective entomological authentication of honey

Honey authentication and traceability are crucial not only for economic purposes but also for ensuring safety. However, the widespread adoption of cutting-edge technologies in practical applications has been hampered by complex, time-consuming sample pre-treatment processes, the need for skilled personnel, and substantial associated expenses. This study aimed to develop a simple and cost-effective molecular technique to verify the entomological source of honey. By utilizing newly designed primers, we successfully amplified the mitochondrial 16S ribosomal RNA gene of honey bees from honey, confirming the high quality of the extracted DNA. Employing RFLP analysis with AseI endonuclease, species-specific restriction patterns were generated for honey derived from six closely related honey bees of the Apis genus. Remarkably, this method was proven equally effective in identifying heat-treated and aged honey by presenting the same RFLP profiles as raw honey. As far as we know, this is the initial research of the simultaneous differentiation of honey from closely related honey bee species using the restriction endonuclease AseI and mitochondrial 16S rRNA gene fragments. As a result, it holds tremendous potential as a standardized guideline for regulatory agencies to ascertain the insect origins of honey and achieve comprehensive traceability.

Enhancing the authenticity of animal by-products: harmonization of DNA extraction methods from novel ingredients

Introduction: The increasing global pressure to explore alternative protein sources derived from animal by-products has opened-up opportunities, but it has also created the need to assess their compliance with labelling statements, to ensure consumer's trust in the composition of both feed and food products. Assessing the authenticity of highly processed animal by-products, particularly within the rapidly expanding Halal food market, presents a significant challenge due to the lack of robust and standardized methodologies. However, the success of DNA based authenticity system is highly dependent on the extracted DNA quantity, quality, and purity ratios from heterogeneous matrices. Material and methods: In this work, nine DNA extraction methods were tested on selected processed animal by-products with high-value and interest for the feed industry: meals from poultry meat, blood and feather, and hydrolysates from swine meat and bone, fish, and black soldier fly. The proposed DNA extraction methods are developed to specifically target swine-specific mitochondrial region, as a case study. Results and discussion: Both the conventional CTAB method and the commercial kits, specifically Invisorb® Spin Tissue Mini and NucleoSpin™ Food, demonstrated superior extraction efficiency and quality ratios. Nevertheless, commercial kits enabled faster detection in comparison to the conventional methods. The absence of swine DNA was successfully validated and confirmed in all animal meals and hydrolysates that did not contain swine in their composition beforehand, demonstrating their compliance with the Halal market requirements.

A preliminary metabarcoding analysis of Portuguese raw honeys

The microbial diversity in Portuguese raw honeys remains largely uncharacterized, constituting a serious knowledge gap in one of the country's most important resources. This work provides an initial investigation with amplicon metabarcoding analysis of two Lavandula spp. from different geographical regions of Portugal and one Eucalyptus spp. honey. The results obtained allowed to identify that each honey harbors diverse microbiomes with taxa that can potentially affect bee and human health, cause spoilage, and highlight bad bee-hive management practices. We verified that prokaryotes had a tendency towards a more marked core bacterial and a relative homogenous taxa distribution, and that the botanical origin of honey is likely to have a stronger impact on the fungal community. Thus, the results obtained in this work provide important information that can be helpful to improve this critical Portuguese product and industry.

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.

Towards DNA-Based Methods Analysis for Honey: An Update

Honey is a natural product widely consumed all over the world due to its relationship with healthy benefits. Additionally, environmental and ethical issues have a higher weight in the consumer's choice to buy honey as a natural product. Following the high demand of this product, several approaches have been suggested and developed aiming at the assessment of honey's quality and authenticity. Target approaches, such as pollen analysis, phenolic compounds, sugars, volatile compounds, organic acids, proteins, amino acids, minerals, and trace elements, showed an efficacy, particularly concerning the honey origin. However, a special highlight is given to DNA markers, due to their useful applicability in environmental and biodiversity studies, besides the geographical, botanical, and entomological origins. Different DNA target genes were already explored for addressing diverse sources of honey DNA, with DNA metabarcoding attaining a relevant importance. This review aims to describe the latest advances on DNA-based methods applied in honey related studies, identifying the research needs for the development of new and additional required methodologies, and to select the most adequate tools for future research projects.

Metabarcoding of eDNA for tracking the floral and geographical origins of bee honey

Authentic honey products have a high commercial value and are often falsified via adulteration. Metabarcoding of environmental DNA (eDNA) from bacterial, floral, and entomological sources has recently been proposed as a useful tool for identifying and authenticating floral and geographical origins of bee honey. In this study, eDNA metabarcoding was applied to reveal the bacterial, plant, and honey bee DNA signatures of 48 commercial honey products from six different geographical origins. Bacterial DNA composition in commercial honey showed different relative abundance of Paenibacillus and Bacillus in geographically different samples, and high abundance of Methylobacterium in chestnut honey implying potential use of bacterial DNA composition for honey authentication. Using the chloroplast trnL (UAA) as a DNA marker, floral origins of commercial honey were investigated. Based on floral DNA signatures, 12 monofloral honey samples were identified among the 45 samples tested. Targeted amplicon sequencing of cytochrome oxidase I (COI) gene from entomological DNA identified three different Apis mellifera sequence variants, specific to geographic origin of honey, suggesting that COI can be implemented as a DNA marker to trace the origin of honey. Therefore, the current study demonstrated the potential of eDNA based metabarcoding as a robust tool for evaluating commercial bee honey by exploring their floral and geographical origins.

Accurate and Rapid Genetic Tracing the Authenticity of Floral Originated Honey with the Molecular Lateral Flow Strip

Honey is a natural product and is heavily consumed for its well-known nutritional functions. Honeys with different floral origins possess distinctive flavors, tastes, functions and economic values. It is vital to establish an effective strategy for identifying the authenticity of honey. The intrinsic genetic materials of pollen were adopted as target analytes for the effective identification of honey with floral origins. With an optimized protocol for the rapid gene extraction from honey, target genetic templates were amplified on-site with a portable device. Conveniently, all on-site amplified functional products were easily judged by the designed lateral flow strip (LFS), which was defined as the molecular LFS in this research. Additionally, the entire on-site genetic authentication of honey was completed in less than 2 h by visual observation. Commercial honey products have been successfully identified with excellent accuracy. This low-cost, high-efficiency and easy-operational strategy will greatly benefit the quality guarantee of foods with specific functions and geographical markers.

Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey

Adulteration and mislabeling of honey to mask its true origin have become a global concern. Pollen microscopy, the current gold standard for identifying honey's geographical and plant origins, is laborious, requires extensive training, and fails to identify filtered honey and honey spiked with pollen from a more favorable plant to disguise its origins. We successfully isolated pollen-free DNA from filtered honey using three types of adsorbents: (i) anti-dsDNA antibodies coupled to magnetic microspheres; (ii) anion-exchange adsorbent; and (iii) ceramic hydroxyapatite. The internal transcribed spacer 2 region of the captured pollen-free DNA was polymerase chain reaction-amplified and subjected to next-generation sequencing. Using an in-house bioinformatics pipeline, initial experiments showed that anion exchange had the greatest capacity to capture trace pollen-free DNA, and it was successfully applied to isolate DNA from five honey samples. Enrichment of trace pollen-free DNA from filtered honey samples opens a new approach for identifying the true origins of honey.

Identification of Seasonal Honey Based on Quantitative Detection of Typical Pollen DNA

Monofloral honey is produced from the nectar of a single predominant botanical species in a particular season and has certain unique properties. Valuable monofloral honey produced in a particular season with unique properties is often targeted for adulteration. Herein, a method for the identification of monofloral honey and determination of its production season was developed. Major nectar plants, including Prunus sp., Robinia pseudoacacia, Castanea sp., and Kalopanax sp., were selected to evaluate the honey produced between April and July in South Korea. Results showed that the highest amount of DNA from each plant was detected in the corresponding flowering season. The pollens tended to accumulate in the honeycomb after the flowering season. The accumulations result in an increase in the diversity of pollen detected in honey. Additionally, DNA quantity of each plant decreased in the samples as the number of plant DNA types increased from May to July. Moreover, the authenticity of the commercial monofloral honey samples showed only cherry blossom honey was found authentic, which exhibited the expected high amount of Prunus sp. DNA. This molecular tool is expected to be useful in verifying the origin of monofloral honey and its production season.

Tracing the origin of honey products based on metagenomics and machine learning

The adulteration of honey is common. Recently, High Throughput Sequencing (HTS)-based metabarcoding method has been applied successfully to pollen/honey identification to determine floral composition that, in turn, can be used to identify the geographical origins of honeys. However, the lack of local references materials posed a serious challenge for HTS-based pollen identification methods. Here, we sampled 28 honey samples from various geographic origins without prior knowledge of local floral information and applied a machine learning method to determine geographical origins. The machine learning method uses a resilient backpropagation algorithm to train a neural network. The results showed that biological components in honey provided characteristic traits that enabled accurate geographic tracing for nearly all honey samples, confidently discriminating honeys to their geographic origin with >99% success rates, including those separated by as little as 39 km.

Determination of honey adulterated with corn syrup by quantitative amplification of maize residual DNA using ultra-rapid real-time PCR

BACKGROUND

Honey is a naturally sweet syrup made by honeybees from floral nectar. However, high-fructose corn syrup has been prevalently used for the adulteration of honey. A novel molecular method was developed for the characterization of corn syrup-adulterated honey by specific amplification and quantification of maize residual DNA in honey. An ultra-rapid real-time polymerase chain reaction (UR-qPCR) system for rapid amplification and protocol for direct purification of residual DNA from honey were described.

RESULTS

Rapidity of maize DNA amplification was acquired within 20 min for a limit of detection of around three copies of targeted DNAs. The amplification of maize residual DNA in honeys adulterated with corn syrup from 5% to 80% (v/v) showed that a minimum rate of 10% adulteration can be identified, and Maize genomic DNA in 5 mL of adulterated honeys was from 13 ± 9 copies to 2478 ± 827 copies, respectively. However, the residual DNA of maize was also detected in natural honey produced in the region where pollen and nectar of maize were collected, and the quantity of maize genomic DNA in these natural honeys was in the range of 10% adulteration with corn syrup. Therefore, detection of both pollen and residual DNA of maize in honey is important in identifying the source of maize residual DNA present in honey.

CONCLUSION

A rapid PCR assay was first developed for the accurate detection and quantification of maize residual DNA in honey. It is a useful tool for specific identification of the corn syrup used for honey adulteration. Further studies on residual DNA in various types of corn syrup and specificity of primer are recommended. © 2021 Society of Chemical Industry.

Molecular Detection of Nosema spp. in Honey in Bulgaria

Environmental DNA (eDNA) analysis is related to screening genetic material of various organisms in environmental samples. Honey represents a natural source of exogenous DNA, which allows for the detection of different honey bee pathogens and parasites. In the present study, we extracted DNA from 20 honey samples from different regions in Bulgaria and tested for the presence of DNA of the ectoparasitic mite Varroa destructor, as well as Nosema apis and Nosema ceranae. Only Nosema ceranae was detected, showing up in 30% of all samples, which confirms the widespread prevalence of this pathogen. All positive samples were found in plain regions of the country, while this pathogen was not detected in mountainous parts. None of the samples gave positive amplifications for the Nosema apis and Varroa mite. The obtained results from this study confirm previous observations that eDNA contained in honey is a potent source for effective biomonitoring of actual diseases in the honey bee.

Integration of DNA extraction, metabarcoding and an informatics pipeline to underpin a national citizen science honey monitoring scheme

Worldwide honeybees (Apis mellifera L.) are one of the most widely kept domesticated animals, supporting domestic and commercial livelihoods through the production of honey and wax, as well as in the delivery of pollination services to crops. Quantifying which plant species are foraged upon by honeybees provides insights into their nutritional status as well as patterns of landscape scale habitat utilization. Here we outline a rapid and reproducible methodology for identifying environmental DNA (eDNA) originating principally from pollen grains suspended within honey. The process is based on a DNA extraction incorporating vacuum filtration prior to universal eukaryotic internal transcribed spacer 2 region (ITS2) amplicon generation, sequencing and identification. To provide a pre-cursor to sequence phylotyping, we outline systems for error-corrected processing amplicon sequence variant abundance tables that removes chimeras. This methodology underpins the new UK National Honey Monitoring Scheme.•

We compare the efficacy and speed of centrifugation and filtration systems for removing pollen from honey samples as a precursor to plant DNA barcoding.

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We introduce the ‘HONEYPI’ informatics pipeline, an open access resource implemented in python 2.7, to ensure long-term reproducibility during the process of amplicon sequence variant classification.

[Analysis of differences between unifloral honeys from different botanical origins based on non-targeted metabolomics by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry]

不同的蜜源植物具有结构多样的次生代谢产物。该研究以8种不同蜜源单花蜜(洋槐蜜、枣花蜜、荆条蜜、椴树蜜、荞麦蜜、麦卢卡蜜、枸杞蜜、益母草蜜)为研究对象,建立了基于超高效液相色谱-四极杆飞行时间质谱技术(UPLC-Q-TOF-MS^E)的非靶向代谢组学方法,考察了不同蜜源中次生代谢产物的差异。该研究采用固相萃取前处理方法和UPLC-Q-TOF-MS^E方法,获得不同蜜源单花蜜的植物代谢组信息,并构建了多变量统计分析模型,对不同来源的单花蜜进行模式识别和差异分析,发现洋槐蜜、枣花蜜、荆条蜜、椴树蜜、荞麦蜜、麦卢卡蜜相互间存在不同程度的显著差异。结合模型的变量重要性投影、方差分析与最大差异倍数值,根据精确前体离子和碎片离子质量信息检索Chemspider、HMDB数据库,该研究筛选并鉴定出32个代谢差异化合物,其中黄酮类化合物18个、酚酸类化合物7个、苯苷与萜苷类化合物6个、甾体类化合物1个;研究发现麦卢卡蜜和荞麦蜜以黄酮类化合物为主要差异代谢物,荆条蜜中酚酸类化合物为特征性表达,苯苷与萜苷类化合物主要为椴树蜜的特征代谢物。该研究从植物代谢组学角度初步揭示了不同单花蜜的代谢产物差异性以及特征化合物,为基于化学分析技术的蜂蜜溯源识别与质量评价提供了有效的研究策略。

Molecular Approaches to Agri-Food Traceability and Authentication: An Updated Review

In the last decades, the demand for molecular tools for authenticating and tracing agri-food products has significantly increased. Food safety and quality have gained an increased interest for consumers, producers, and retailers, therefore, the availability of analytical methods for the determination of food authenticity and the detection of major adulterations takes on a fundamental role. Among the different molecular approaches, some techniques such as the molecular markers-based methods are well established, while some innovative approaches such as isothermal amplification-based methods and DNA metabarcoding have only recently found application in the agri-food sector. In this review, we provide an overview of the most widely used molecular techniques for fresh and processed agri-food authentication and traceability, showing their recent advances and applications and discussing their main advantages and limitations. The application of these techniques to agri-food traceability and authentication can contribute a great deal to the reassurance of consumers in terms of transparency and food safety and may allow producers and retailers to adequately promote their products.

Honey authenticity: analytical techniques, state of the art and challenges

Honey is a high-value, globally consumed, food product featuring a high market price strictly related to its origin. Moreover, honey origin has to be clearly stated on the label, and quality schemes are prescribed based on its geographical and botanical origin. Therefore, to enhance food quality, it is of utmost importance to develop analytical methods able to accurately and precisely discriminate honey origin. In this study, an all-time scientometric evaluation of the field is provided for the first time using a structured keyword on the Scopus database. The bibliometric analysis pinpoints that the botanical origin discrimination was the most studied authenticity issue, and chromatographic methods were the most frequently used for its assessment. Based on these results, we comprehensively reviewed analytical techniques that have been used in honey authenticity studies. Analytical breakthroughs and bottlenecks on methodologies to assess honey quality parameters using separation, bioanalytical, spectroscopic, elemental and isotopic techniques are presented. Emphasis is given to authenticity markers, and the necessity to apply chemometric tools to reveal them. Altogether, honey authenticity is an ever-growing field, and more advances are expected that will further secure honey quality.

Methods for determining the botanical origin of honey

The demand for monofloral, original, and special (functional) kinds of honey, or those with geographical indication, is forecast. At the same time, there is a need to improve the methods for determining the botanical and geographical origin of honey. The purpose of the research was to select and apply a variety of techniques for identifying the botanical origin of honey for its correspondence to acacia species. Samples of honey from the Kyiv, Odesa, and Dnipro regions extracted in the spring and summer period were used in the research. Organoleptic, physicochemical, NMR spectrometry, and advanced melissopalynology methods were applied. The tests were carried out at the laboratories of the Department of Certification and Standardization of Agricultural Products, NULES, Ukraine; the Ukrainian Laboratory of Quality and Safety of Agricultural Products; and the Bruker BioSpin GmbH company (Germany). According to the research results, the requirements for acacia honey were met by the organoleptic method for samples B1 and B2; by the physicochemical method for A0 and A2; by NMR spectroscopy for not a single sample, all being assessed as polyfloral; and by pollen analysis for B1 and B2. The conducted studies confirm the need for a comprehensive approach to the identification of the botanical origin of honey for its conformity to acacia species. There is a need to review the physicochemical indicators for the compliance of honey with the acacia species obtained in Ukraine. After all, even the modern NMR spectrometry technique indicated that the specially fabricated sample that did not contain acacia pollen grains was acacia honey. Identification of the botanical origin of monofloral honey, in particular acacia, should be carried out in the following sequence: pollen analysis (by dominant pollen grains), safety (presence of antibiotics, pesticides), physicochemical parameters according to international requirements, organoleptic parameters.

Interactions of Designed Trp-Containing Antimicrobial Peptides with DNA of Multidrug-Resistant Pseudomonas aeruginosa

To investigate the intracellular mechanisms of seven Trp-containing peptides in clinically isolated multidrug-resistant Pseudomonas aeruginosa (MRPA0108). The results showed that the Trp-containing peptides had high antibacterial activity against the MRPA0108 strain, with minimal inhibitory concentration (MIC) values ranging from 6.25 to 25 μM. The peptides rapidly and completely killed the MRPA0108 at a concentration of 16 × MIC at 60-90 min. The Trp-containing peptides were found to penetrate the bacterial cell membrane and accumulate in the cells. A DNA gel retardation assay indicated that the peptides were able to bind with the genomic DNA of MRPA0108 cells; L5W exhibited a stronger DNA binding ability than that of the other peptides, and the ratio of peptide to DNA was 0.62/1. Next, the UV absorption spectrum of the DNA indicated that L5W interacted with the MRPA0108 genomic DNA and intercalated into the groove of the DNA molecule, resulting in loosening of the double-helical structure of the originally contracted DNA and leading to the occurrence of a hyperchromic effect. The circular dichroism spectrum suggested that I1W and L5W associated with the DNA via a trench combination mode resulting from the compact structure of the DNA double helix and reduction in ππ accumulation between base pairs. Furthermore, real-time quantitative PCR demonstrated that the Trp-containing peptides could downregulate the expression of DNA replication-initiating genes in MRPA0108 cells. MRPA0108 DNA may be a potential active target for the antimicrobial activity of Trp-containing peptides.

Descriptive Bacterial and Fungal Characterization of Propolis Using Ultra-High-Throughput Marker Gene Sequencing

Bees harbor microorganisms that are important for host health, physiology, and survival. Propolis helps modulate the immune system and health of the colony, but little information is available about its microbial constituents. Total genomic DNA from samples of natural propolis from Apis mellifera production hives from four locations in Mexico were used to amplify a region of the 16S rRNA gene (bacteria) and the internal transcriber spacer (fungi), using PCR. The Illumina MiSeq platform was used to sequence PCR amplicons. Extensive variation in microbial composition was observed between the propolis samples. The most abundant bacterial group was Rhodopila spp. (median: 14%; range: 0.1%–27%), a group with one of the highest redox potential in the microbial world. Other high abundant groups include Corynebacterium spp. (median: 8.4%; 1.6%–19.5%) and Sphingomonas spp. (median: 5.9%; 0.03%–14.3%), a group that has been used for numerous biotechnological applications because of its biodegradative capabilities. Bacillus and Prevotella spp. alone comprised as much as 88% (53% and 35%, respectively) of all bacterial microbiota in one sample. Candida (2%–43%), Acremonium (0.03%–25.2%), and Aspergillus (0.1%–43%) were among the most abundant fungi. The results contribute to a better understanding of the factors associated with the health of Apis mellifera production hives.

Genome-skimming provides accurate quantification for pollen mixtures

Studies on foraging partitioning in pollinators can provide critical information to the understanding of food-web niche and pollination functions, thus aiding conservation. Metabarcoding based on PCR amplification and high-throughput sequencing has seen increasing applications in characterizing pollen loads carried by pollinators. However, amplification bias across taxa could lead to unpredictable artefacts in estimation of pollen compositions. We examined the efficacy of a genome-skimming method based on direct shotgun sequencing in quantifying mixed pollen, using mock samples (five and 14 mocks of flower and bee pollen, respectively). The results demonstrated a high level of repeatability and accuracy in identifying pollen from mixtures of varied species ratios. All pollen species were detected in all mocks, and pollen frequencies estimated from the number of sequence reads of each species were significantly correlated with pollen count proportions (linear model, R²  = 86.7%, p = 2.2e-16). For >97% of the mixed taxa, pollen proportion could be quantified by sequencing to the correct order of magnitude, even for species which constituted only 0.2% of the total pollen. In addition, DNA extracted from pollen grains equivalent to those collected from a single honeybee corbicula was sufficient for genome-skimming. We conclude that genome-skimming is a feasible approach to identifying and quantifying mixed pollen samples. By providing reliable and sensitive taxon identification and relative abundance, this method is expected to improve our understanding in studies that involve plant-pollinator interactions, such as pollen preference in corbiculate bees, pollen diet analyses and identification of landscape pollen resource use from beehives.

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).

Microsatellite High-Resolution Melting (SSR-HRM) to Track Olive Genotypes: From Field to Olive Oil

The need to support food labelling has driven to the development of PCR-based techniques suitable for food analysis. DNA-based markers have been successfully employed for varietal tracing in Protected Designation of Origin (PDO) olive oils. In this study, we report a fast, sensitive, and easy-to-use strategy for PDO olive varietal identification. To achieve this aim four different DNA extraction methods were tested and compared, based on initial volume, extraction time, the gDNA concentration, and quality ratios. The optimized DNA extraction protocol from extra virgin olive oils, based on CTAB-hexane-chloroform extraction, proved to be the most effective. High-resolution melting (HRM) DNA assay was developed based on nuclear microsatellites (gSSR) and plastid DNA (cpDNA) aiming an accurate identification of the olive varieties present in the olive oil samples. After PCR reproducibility evaluation, six molecular markers: three SSRs and three cpDNA loci were chosen based on their discrimination power. The SSR-HRM strategy assays were designed to target UDO99-011, UDO99-039, UDO99-024, and ssrOeUA-DCA16 loci. All SSR-PCR products generated from these primers were analyzed by capillary electrophoresis (CE) for HRM data validation. The SSR coupled with HRM melting curve analysis generated 14 HRM profiles sufficient to genotype all varieties, highlighting their potential use for varietal discrimination. The locus ssrOeUA-DCA16 generated a specific melting curve that allow a high-throughput discrimination of the Picual and Cobrançosa varieties in olive oil samples. Further, the UDO99-024 was also tested by SSR-HRM assay in commercial olive oil samples with promising results. Considering time, cost, and performance SSR-HRM proved to be a reliable method suitable for varietal tracing of olive oils. PRACTICAL APPLICATION: Olive oil authenticity is a form of protecting producers and consumers against fraudulent practices. Herein, we present a DNA barcode suitable for the identification of olive varieties, allowing an accurate identification of the olive varieties in olive oil samples using SSR-HRM assay. Its applicability in commercial olive oil samples is viable. This methodology can be used as a tool for Extra Virgin Olive Oil (EVOO) adulterations detection.

Entomological signatures in honey: an environmental DNA metabarcoding approach can disclose information on plant-sucking insects in agricultural and forest landscapes

Honeydew produced from the excretion of plant-sucking insects (order Hemiptera) is a carbohydrate-rich material that is foraged by honey bees to integrate their diets. In this study, we used DNA extracted from honey as a source of environmental DNA to disclose its entomological signature determined by honeydew producing Hemiptera that was recovered not only from honeydew honey but also from blossom honey. We designed PCR primers that amplified a fragment of mitochondrial cytochrome c oxidase subunit 1 (COI) gene of Hemiptera species using DNA isolated from unifloral, polyfloral and honeydew honeys. Ion Torrent next generation sequencing metabarcoding data analysis assigned Hemiptera species using a customized bioinformatic pipeline. The forest honeydew honeys reported the presence of high abundance of Cinara pectinatae DNA, confirming their silver fir forest origin. In all other honeys, most of the sequenced reads were from the planthopper Metcalfa pruinosa for which it was possible to evaluate the frequency of different mitotypes. Aphids of other species were identified from honeys of different geographical and botanical origins. This unique entomological signature derived by environmental DNA contained in honey opens new applications for honey authentication and to disclose and monitor the ecology of plant-sucking insects in agricultural and forest landscapes.

Quality evaluation of Omani honey

This study was intended to evaluate the quality parameters of 58 Apis mellifera honey samples, from different regions in the Sultanate of Oman. Physicochemical analyses were carried out and examined according to the Gulf Standardization Organization (GSO). The results revealed that 64.4% of the samples were failing to meet the GSO standards due to acidity, hydroxyl methyl furfural (HMF), diastase, sucrose, and glucose & fructose. Acidity and HMF were above the limits in 30% and 29% of the failed samples respectively, where diastase and total glucose & fructose were below the limits in 25% and 5% respectively. Sucrose was above the limits in 11% of the failed samples. The unconformity of the analyzed honey samples to GSO standards could be due to stage of harvesting, process and storage conditions. Therefore, it's important to reconsider the whole process of honey production in Oman in order to improve the technology and honey quality.

Portuguese Honeys from Different Geographical and Botanical Origins: A 4-Year Stability Study Regarding Quality Parameters and Antioxidant Activity

Portuguese honeys (n = 15) from different botanical and geographical origins were analysed regarding their quality parameters (diastase activity, hydroxymethylfurfural content, moisture and pH), colour (L*, a*, b*) and antioxidant profile (total phenolics content, total flavonoids content, DPPH^• scavenging activity, and ferric reducing power). The samples were analysed fresh and after 4-years of storage (at 25 °C and protected from light). The hydroxymethylfurfural content and diastase activity of the fresh samples were in accordance with the recommended values described in the legislation. In general, the antioxidant activity of the samples correlated more with the bioactive compounds content than with colour. The storage affected differently each individual sample, especially regarding the antioxidant profile. Nevertheless, although in general the lightness of the samples decreased (and the redness increased), after 4 years, 11 samples still presented acceptable diastase activity and hydroxymethylfurfural values.

Deeper Insight in Beehives: Metagenomes of Royal Jelly, Pollen, and Honey from Lavender, Chestnut, and Fir Honeydew and Epiphytic and Endophytic Microbiota of Lavender and Rose Flowers

Microbiota of beehive products are very little known. We report here for the first time six metagenomes of royal jelly, pollen, and different types of honey from wild and cultivated lavender, chestnut, and fir honeydew. Four metagenomes of epiphytic and endophytic microbiota of lavender and rose flowers are also reported.

Using DNA Metabarcoding to Identify the Floral Composition of Honey: A New Tool for Investigating Honey Bee Foraging Preferences

Identifying the floral composition of honey provides a method for investigating the plants that honey bees visit. We compared melissopalynology, where pollen grains retrieved from honey are identified morphologically, with a DNA metabarcoding approach using the rbcL DNA barcode marker and 454-pyrosequencing. We compared nine honeys supplied by beekeepers in the UK. DNA metabarcoding and melissopalynology were able to detect the most abundant floral components of honey. There was 92% correspondence for the plant taxa that had an abundance of over 20%. However, the level of similarity when all taxa were compared was lower, ranging from 22-45%, and there was little correspondence between the relative abundance of taxa found using the two techniques. DNA metabarcoding provided much greater repeatability, with a 64% taxa match compared to 28% with melissopalynology. DNA metabarcoding has the advantage over melissopalynology in that it does not require a high level of taxonomic expertise, a greater sample size can be screened and it provides greater resolution for some plant families. However, it does not provide a quantitative approach and pollen present in low levels are less likely to be detected. We investigated the plants that were frequently used by honey bees by examining the results obtained from both techniques. Plants with a broad taxonomic range were detected, covering 46 families and 25 orders, but a relatively small number of plants were consistently seen across multiple honey samples. Frequently found herbaceous species were Rubus fruticosus, Filipendula ulmaria, Taraxacum officinale, Trifolium spp., Brassica spp. and the non-native, invasive, Impatiens glandulifera. Tree pollen was frequently seen belonging to Castanea sativa, Crataegus monogyna and species of Malus, Salix and Quercus. We conclude that although honey bees are considered to be supergeneralists in their foraging choices, there are certain key species or plant groups that are particularly important in the honey bees environment. The reasons for this require further investigation in order to better understand honey bee nutritional requirements. DNA metabarcoding can be easily and widely used to investigate floral visitation in honey bees and can be adapted for use with other insects. It provides a starting point for investigating how we can better provide for the insects that we rely upon for pollination.