Rapid identification of the botanical and entomological sources of honey using DNA metabarcoding

Uncontrolled deforestation and population growth threaten a tropical island's water and land resources in only 10 years

Rapid demographic growth in tropical islands can exacerbate conflicts and pressures on natural resources, as illustrated by the French island of Mayotte where resources are limited. In only 10 years, uncontrolled migration and population growth (+80% of population between 2002 and 2021) have led to a pronounced 3600% increase in deforestation rates (2010-2014) and an intensification of agricultural practices, escalating conflicts over limited land, water, and biodiversity resources. Implementing an original multi-proxy approach to sediment cores, our study reveals a staggering 300% acceleration in erosion during the first wave of migration (2011-2015), followed by a further 190% increase (2019-2021) under sustained migratory and demographic pressures. Sedimentary DNA analysis provided insights into increased connectivity and community changes. By 2050, the population of this region will increase by 74 and 103%, in Comoros and Madagascar islands, respectively. Urgent conservation measures are needed to avoid major socio-environmental crises and to protect resources for future generations.

Hydroxy Fatty Acid Synthesis-Related mRNA as the Biomarker for Detecting Mislabeling of Honey Entomological Origin

The authentication of the entomological origin of honey is a widespread concern, necessitating the prompt establishment of an effective approach for distinguishing between Apis cerana cerana honey (ACH) and Apis mellifera ligustica honey (AMH). Hydroxy fatty acids (HFAs) found in honey are bee-derived components synthesized by the mandibular glands of worker bees. We previously discovered significant variations in the hydroxy fatty acid composition between ACH and AMH, suggesting their potential as indicators for identifying the authenticity of the entomological origin of honey. Herein, we identified differentially expressed genes associated with HFA synthesis by conducting transcriptome sequencing of the mandibular glands of AC and AM honeybees. Subsequently, we proposed a method for the relative quantitative analysis of bee-derived RNA components using real-time fluorescence quantitative polymerase chain reaction, which was supplemented by multivariate statistical analysis to further discern differences in HFA synthesis-related mRNA between ACH and AMH. The results showed that the mRNAs of FAXDC2 (fatty acid hydroxylase domain-containing protein 2) and FAS (fatty acid synthase) may serve as indicators to discern the entomological origin of honey. This study presents two novel biomarkers for detecting mislabeling of the entomological origin in ACH and AMH based on variations in bee-derived components.

Decoding Seafood: Multi-Marker Metabarcoding for Authenticating Processed Seafood

Given the recognized nutritional value of fish and shifting consumer lifestyles, processed seafood has become increasingly prevalent, comprising a significant portion of global food production. Although current European Union labeling regulations do not require species declaration for these products, food business operators often voluntarily provide this information on ingredient lists. Next Generation Sequencing (NGS) approaches are currently the most effective methods for verifying the accuracy of species declarations on processed seafood labels. This study examined the species composition of 20 processed seafood products, each labeled as containing a single species, using two DNA metabarcoding markers targeting the mitochondrial cytochrome c oxidase I (COI) and 16S rRNA genes. The combined use of these markers revealed that the majority of the products contained multiple species. Furthermore, two products were found to be mislabeled, as the declared species were not detected. These findings underscore that NGS is a robust technique that could be adopted to support routine food industry activities and official control programs, thereby enhancing the 'From Boat to Plate' strategy and combating fraudulent practices in the complex fisheries supply chain.

Finding the perfect pairs: A matchmaking of plant markers and primers for multi-marker eDNA metabarcoding

As the scope of plant eDNA metabarcoding diversifies, so do the primers, markers and methods. A wealth of primers exists today, but their comparative evaluation is lacking behind. Similarly, multi-marker approaches are recommended but debates persist regarding barcode complementarity and optimal combinations. After a literature compilation of used primers, we compared in silico 102 primer pairs based on amplicon size, coverage and specificity, followed by an experimental evaluation of 15 primer pairs on a mock community sample covering 268 plant species and genera, and about 100 families. The analysis was done for the four most common plant metabarcoding markers, rbcL, trnL, ITS1 and ITS2 and their complementarity was assessed based on retrieved species. By focusing on existing primers, we identify common designs, promote alternatives and enhance prior-supported primers for immediate applications. The ITS2 was the best-performing marker for flowering vascular plants and was congruent to ITS1. However, the combined taxonomic breadth of ITS2 and rbcL surpassed any other combination, highlighting their high complementarity across Streptophyta. Overall, our study underscores the significance of comprehensive primer and barcode evaluations tailored to metabarcoding applications.

Fecal DNA metabarcoding helps characterize the Canada jay's diet and confirms its reliance on stored food for winter survival and breeding

Accurately determining the diet of wild animals can be challenging if food items are small, visible only briefly, or rendered visually unidentifiable in the digestive system. In some food caching species, an additional challenge is determining whether consumed diet items have been previously stored or are fresh. The Canada jay (Perisoreus canadensis) is a generalist resident of North American boreal and subalpine forests with anatomical and behavioural adaptations allowing it to make thousands of arboreal food caches in summer and fall that are presumably responsible for its high winter survival and late winter/early spring breeding. We used DNA fecal metabarcoding to obtain novel information on nestling diets and compiled a dataset of 662 published and unpublished direct observations or stomach contents identifications of natural foods consumed by Canada jays throughout the year. We then used detailed natural history information to make informed decisions on whether each item identified to species in the diets of winter adults and nestlings was best characterized as 'likely cached', 'likely fresh' (i.e., was available as a non-cached item when it appeared in a jay's feces or stomach), or 'either possible'. Of the 87 food items consumed by adults in the winter, 39% were classified as 'likely cached' and 6% were deemed to be 'likely fresh'. For nestlings, 29% of 125 food items identified to species were 'likely cached' and 38% were 'likely fresh'. Our results support both the indispensability of cached food for Canada jay winter survival and previous suggestions that cached food is important for late winter/early spring breeding. Our work highlights the value of combining metabarcoding, stomach contents analysis, and direct observations to determine the cached vs. non-cached origins of consumed food items and the identity of food caches, some of which could be especially vulnerable to degradation through climate change.

Analysis of Free Amino Acid Composition and Honey Plant Species in Seven Honey Species in China

Honey is well-known as a food product that is rich in active ingredients and is very popular among consumers. Free amino acids (FAAs) are one of the important nutritional components of honey, which can be used not only as a nutritional indicator of honey but also as an indicator of plant source identification. In this study, the contents of 20 FAAs in seven types of honey from 11 provinces in China were examined for the first time. The 20 FAAs were analyzed by ultra-performance liquid chromatography-mass spectrometry/mass spectrometry (UPLC-MS/MS). By analyzing 93 honey samples from seven types of honey, the FAAs were found to range from 394.4 mg/kg (linden honey) to 1771.7 mg/kg (chaste honey). Proline ranged from 274.55 to 572.48 mg/kg, and methionine was only present in some of the linden honey, chaste honey, acacia honey, and rape honey. Evaluated by amino acid principal component analysis, multifloral grassland honey had the highest overall evaluation score, acacia and jujube honey were the most similar, while chaste honey was the least similar to the other types of honey. In addition, DNA was extracted from 174 Xinjiang grassland honey samples and different plant leaves for PCR and sequencing to identify the species of nectar plants. As a result, 12 families and 25 species of honey plants were identified. The results confirmed the diversity of FAAs in dissimilar types and sources of honey. This study provides a reference for expanding honey quality standards and verifying the authenticity of honey.

Accuracy and stability enhanced honey authenticity visual tracing method via false positive-eradicating PCR assisted nucleic acid-capturing lateral flow strip

Honey authenticity guarantee is crucial for consumer health and fair-trading commerce. New visual false-positive-free molecular lateral flow strip (LFS), termed 5'-3' exonuclease activity -directed false positive-eradicating PCR assisted lateral flow strip (FPE-PCR-LFS) was developed. This FPE-PCR-LFS explored the availability of using a signal-probe as the mediator to integrate the efficient amplification module with visual LFS module. With the genomic DNA extracted from target honey, the designed signal probe would be hydrolyzed and exhausted by the 5'-3' exonuclease activity of Taq DNA polymerase in the amplification process. The hydrolyzed signal probe would not be recognized and capture on the T line with only C line of LFS, reflecting the authenticity of the tested honey. And as low as 0.5% authenticity can be accurately identified in commercial honey samples. Significantly, the false-positive-interference was successfully eradicated for the final visual results judgement, which would greatly widen the application of molecular PCR-LFS in various fields.

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.

Honey Quality Control: Review of Methodologies for Determining Entomological Origin

Honey is a widely consumed natural product, and its entomological origin can significantly influence its market value. Therefore, traceability of the entomological origin of honey should also be considered in honey quality control protocols. Although several methods exist, such as physicochemical characterization and bioactivity profiling of honey of different entomological origins, the most promising three methods for entomological authentication of honey include protein-based identification, chemical profiling, and a DNA-based method. All of these methods can be applied for reliable identification of the entomological origin of honey. However, as the honey is a complex matrix, the inconsistency of the results obtained by these methods is a pragmatic challenge, and therefore, the use of each method in all the cases is questionable. Most of these methodologies can be used for authentication of newly harvested honey and it is worth understanding the possibility of using these methods for authentication of relatively old samples. Most probably, using DNA-based methods targeting small fragments of DNA can provide the best result in old samples, however, the species-specific primers targeting short fragments are limited and not available for all species. Therefore, using universal primers in combination with a DNA metabarcoding approach can be a good solution that requires further investigation. This present article describes the applications of different methods, their pros, and their cons to identify honey based on entomological origin.

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.

Honey DNA metabarcoding revealed foraging resource partitioning between Korean native and introduced honey bees (Hymenoptera: Apidae)

Honey DNA metabarcoding provides information of floral sources of honey and foraging plant preferences of honey bees. We evaluated the floral composition of honey from two different species of honey bees, Apis cerana honey (ACH) and A. mellifera honey (AMH) in a mixed apiary located in a semi-forest environment to understand the floral preference and level of interspecific competition on floral resource. Three honey samples were collected from different hives of each species in mid-August. In total, 56 plant taxa were identified across the honey samples and among them, 38 taxonomic units were found in ACH compared with a total of 33 in AMH. The number of major plants (> 1% of reads) in honey samples was 9 and 11 in ACH and AMH respectively indicating the higher diversity of plant taxa in AMH. 23 taxonomic units were found exclusively in ACH, 18 taxonomic units were found only in AMH and 15 taxonomic units were shared between ACH and AMH indicating that 73% of the taxonomic units were present only in honey originated from one of the honeybee species. Qualitative and quantitative analyses of the shared major plants revealed the division of floral resource between these co-existing honey bee species pointing to a low level of interspecific competition between these two important pollinators.

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.

Honey Environmental DNA Can Be Used to Detect and Monitor Honey Bee Pests: Development of Methods Useful to Identify Aethina tumida and Galleria mellonella Infestations

Environmental DNA (eDNA) contained in honey derives from the organisms that directly and indirectly have been involved in the production process of this matrix and that have played a role in the hive ecosystems where the honey has been produced. In this study we set up PCR-based assays to detect the presence of DNA traces left in the honey by two damaging honey bee pests: the small hive beetle (Aethina tumida) and the greater wax moth (Galleria mellonella). DNA was extracted from 82 honey samples produced in Italy and amplified using two specific primer pairs that target the mitochondrial gene cytochrome oxidase I (COI) of A. tumida and two specific primer pairs that target the same gene in G. mellonella. The limit of detection was tested using sequential dilutions of the pest DNA. Only one honey sample produced in Calabria was positive for A. tumida whereas about 66% of all samples were positively amplified for G. mellonella. The use of honey eDNA could be important to establish early and effective measures to contain at the local (e.g., apiary) or regional scales these two damaging pests and, particularly for the small hive beetle, to prevent its widespread diffusion.

Windborne migration amplifies insect-mediated pollination services

Worldwide, hoverflies (Syrphidae: Diptera) provide crucial ecosystem services such as pollination and biological pest control. Although many hoverfly species exhibit migratory behavior, the spatiotemporal facets of these movement dynamics, and their ecosystem services implications are poorly understood. In this study, we use long-term (16-year) trapping records, trajectory analysis, and intrinsic (i.e., isotope, genetic, pollen) markers to describe migration patterns of the hoverfly Episyrphus balteatus in northern China. Our work reveals how E. balteatus migrate northward during spring–summer and exhibits return (long-range) migration during autumn. The extensive genetic mixing and high genetic diversity of E. balteatus populations underscore its adaptive capacity to environmental disturbances, for example, climate change. Pollen markers and molecular gut analysis further illuminate how E. balteatus visits min. 1012 flowering plant species (39 orders) over space and time. By thus delineating E. balteatus transregional movements and pollination networks, we advance our understanding of its migration ecology and facilitate the design of targeted strategies to conserve and enhance its ecosystem services.

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.

Analytical Strategies for LC-MS-Based Untargeted and Targeted Metabolomics Approaches Reveal the Entomological Origins of Honey

A comprehensive liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach was developed to discriminate honey harvested from Apis mellifera ligustica Spinola (A. mellifera) and Apis cerana cerana Fabricius (A. cerana). Based on an untargeted strategy, ultrahigh-performance liquid chromatography electrospray ionization quadrupole orbitrap high-resolution mass spectrometry (UPLC Q-Orbitrap) was combined with chemometrics techniques to screen and identify tentative markers from A. mellifera and A. cerana honey. In targeted metabolomics analysis, a sensitive method of solid-phase extraction followed by ultrahigh-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UPLC-MS/MS) was established for quantifying three markers, and the results showed that 3-amino-2-naphthoic acid and methyl indole-3-acetate could be considered markers of A. cerana honey, as they were present in higher amounts in A. cerana honey than in A. mellifera honey, whereas kynurenic acid was determined to be a marker of A. mellifera honey. This work highlights critical information for the authentication of A. cerana and A. mellifera honey.

The Honey Bee Apis mellifera: An Insect at the Interface between Human and Ecosystem Health

Simple Summary

Apis mellifera Linnaeus (1758), a honey bee, is a eusocial insect widely known for its role in pollination, an essential ecosystem service for plant biodiversity, and quality of vegetables and fruit products. In addition, honey bees and bee products are valuable bioindicators of pollutants, such as airborne particulate matter, heavy metals, and pesticides. In this review, we explore the provisioning, regulating, and cultural services provided by the honey bee, an insect at the interface between human and ecosystem health.

Abstract

The concept of ecosystem services is widely understood as the services and benefits thatecosystems provide to humans, and they have been categorised into provisioning, regulating, supporting, and cultural services. This article aims to provide an updated overview of the benefits that the honey bee Apis mellifera provides to humans as well as ecosystems. We revised the role of honey bees as pollinators in natural ecosystems to preserve and restore the local biodiversity of wild plants; in agro-ecosystems, this species is widely used to enhance crop yield and quality, meeting the increasing food demand. Beekeeping activity provides humans not only with high-quality food but also with substances used as raw materials and in pharmaceuticals, and in polluted areas, bees convey valuable information on the environmental presence of pollutants and their impact on human and ecosystem health. Finally, the role of the honey bee in symbolic tradition, mysticism, and the cultural values of the bee habitats are also presented. Overall, we suggest that the symbolic value of the honey bee is the most important role played by this insect species, as it may help revitalise and strengthen the intimate and reciprocal relationship between humans and the natural world, avoiding the inaccuracy of considering the ecosystems as mere providers of services to humans.

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.

Do the evolutionary interactions between moths and bats promote niche partitioning between bats and birds?

Ecological theory suggests that the coexistence of species is promoted by the partitioning of available resources, as in dietary niche partitioning where predators partition prey. Yet, the mechanisms underlying dietary niche partitioning are not always clear. We used fecal DNA metabarcoding to investigate the diets of seven nocturnal insectivorous bird and bat species. Low diet overlap (2%-22%) supported resource partitioning among all species. Differences in diet corresponded with species identity, prey detection method, and foraging behavior of predators. Insects with ultrasonic hearing capabilities were consumed significantly more often by birds than bats, consistent with an evolved avoidance of echolocating strategies. In turn, bats consumed a greater proportion of noneared insects such as spruce budworms. Overall, our results suggest that evolutionary interactions among bats and moths translate to dietary niche partitioning and coexistence among bats and nocturnal birds.

Drought at a coastal wetland affects refuelling and migration strategies of shorebirds

Droughts can affect invertebrate communities in wetlands, which can have bottom-up effects on the condition and survival of top predators. Shorebirds, key predators at coastal wetlands, have experienced widespread population declines and could be negatively affected by droughts. We explored, in detail, the effects of drought on multiple aspects of shorebird stopover and migration ecology by contrasting a year with average wet/dry conditions (2016) with a year with moderate drought (2017) at a major subarctic stopover site on southbound migration. We also examined the effects of drought on shorebird body mass during stopover across 14 years (historical: 1974–1982 and present-day: 2014–2018). For the detailed comparison of two years, in the year with moderate drought we documented lower invertebrate abundance at some sites, higher prey family richness in shorebird faecal samples, lower shorebird refuelling rates, shorter stopover durations for juveniles, and, for most species, a higher probability of making a subsequent stopover in North America after departing the subarctic, compared to the year with average wet/dry conditions. In the 14-year dataset, shorebird body mass tended to be lower in drier years. We show that even short-term, moderate drought conditions can negatively affect shorebird refuelling performance at coastal wetlands, which may carry-over to affect subsequent stopover decisions. Given shorebird population declines and predicted changes in the severity and duration of droughts with climate change, researchers should prioritize a better understanding of how droughts affect shorebird refuelling performance and survival.

Identification of pollen taxa by different microscopy techniques

Melissopalynology is an important analytical method to identify botanical origin of honey. Pollen grain recognition is commonly performed by visual inspection by a trained person. An alternative method for visual inspection is automated pollen analysis based on the image analysis technique. Image analysis transfers visual information to mathematical descriptions. In this work, the suitability of three microscopic techniques for automatic analysis of pollen grains was studied. 2D and 3D morphological characteristics, textural and colour features, and extended depth of focus characteristics were used for the pollen discrimination. In this study, 7 botanical taxa and a total of 2482 pollen grains were evaluated. The highest correct classification rate of 93.05% was achieved using the phase contrast microscopy, followed by the dark field microscopy reaching 91.02%, and finally by the light field microscopy reaching 88.88%. The most significant discriminant characteristics were morphological (2D and 3D) and colour characteristics. Our results confirm the potential of using automatic pollen analysis to discriminate pollen taxa in honey. This work provides the basis for further research where the taxa dataset will be increased, and new descriptors will be studied.

Geographic source estimation using airborne plant environmental DNA in dust

Information obtained from the analysis of dust, particularly biological particles such as pollen, plant parts, and fungal spores, has great utility in forensic geolocation. As an alternative to manual microscopic analysis of dust components, we developed a pipeline that utilizes the airborne plant environmental DNA (eDNA) in settled dust to estimate geographic origin. Metabarcoding of settled airborne eDNA was used to identify plant species whose geographic distributions were then derived from occurrence records in the USGS Biodiversity in Service of Our Nation (BISON) database. The distributions for all plant species identified in a sample were used to generate a probabilistic estimate of the sample source. With settled dust collected at four U.S. sites over a 15-month period, we demonstrated positive regional geolocation (within 600 km² of the collection point) with 47.6% (20 of 42) of the samples analyzed. Attribution accuracy and resolution was dependent on the number of plant species identified in a dust sample, which was greatly affected by the season of collection. In dust samples that yielded a minimum of 20 identified plant species, positive regional attribution was achieved with 66.7% (16 of 24 samples). For broader demonstration, citizen-collected dust samples collected from 31 diverse U.S. sites were analyzed, and trace plant eDNA provided relevant regional attribution information on provenance in 32.2% of samples. This showed that analysis of airborne plant eDNA in settled dust can provide an accurate estimate regional provenance within the U.S., and relevant forensic information, for a substantial fraction of samples analyzed.

Cataloguing the small RNA content of honey using next generation sequencing

•

Plant miRNAs are present in Australian polyfloral and Leptospermum scoparium honey.

•

Sequencing shows that honey contains a diverse range of small, non-coding RNAs.

•

Honey RNA comes from different phylogenies including invertebrates and prokaryotes.

•

Unique small RNA profiles can provide insight into honey production conditions.

Honey adulteration is a problem that effects the global honey industry and specifically, has been discovered in the Australian market. Common methods of adulteration include dilution with sugar syrup substitutes and the mislabelling of the floral and geographic origin(s) of honey. Current authentication tools rely on the molecular variability between different honeys, identifying unique chemical profiles and/or DNA signatures characteristic of a particular honey.

Honey is known to contain plant miRNAs derived from its floral source. To explore the composition and variability of honey RNA molecules, this is the first study to catalogue the small RNA content of Australian polyfloral table honey and New Zealand Leptospermum scoparium honey using next generation sequencing. The data shows that in addition to miRNAs, honey contains a variety of small non-coding RNAs including tRNA-derived fragments. Moreover, the honey small RNAs are derived from a range of phylogenetic sources, including from plant, invertebrate, and prokaryotic species. The data indicates that different honeys contain unique small RNA profiles, which suggests a novel avenue in developing molecular-based honey authentication tools.

Pollen DNA metabarcoding identifies regional provenance and high plant diversity in Australian honey

Accurate identification of the botanical components of honey can be used to establish its geographical provenance, while also providing insights into honeybee (Apis mellifera L.) diet and foraging preferences. DNA metabarcoding has been demonstrated as a robust method to identify plant species from pollen and pollen-based products, including honey. We investigated the use of pollen metabarcoding to identify the floral sources and local foraging preferences of honeybees using 15 honey samples from six bioregions from eastern and western Australia. We used two plant metabarcoding markers, ITS2 and the trnL P6 loop. Both markers combined identified a total of 55 plant families, 67 genera, and 43 species. The trnL P6 loop marker provided significantly higher detection of taxa, detecting an average of 15.6 taxa per sample, compared to 4.6 with ITS2. Most honeys were dominated by Eucalyptus and other Myrtaceae species, with a few honeys dominated by Macadamia (Proteaceae) and Fabaceae. Metabarcoding detected the nominal primary source provided by beekeepers among the top five most abundant taxa for 85% of samples. We found that eastern and western honeys could be clearly differentiated by their floral composition, and clustered into bioregions with the trnL marker. Comparison with previous results obtained from melissopalynology shows that metabarcoding can detect similar numbers of plant families and genera, but provides significantly higher resolution at species level. Our results show that pollen DNA metabarcoding is a powerful and robust method for detecting honey provenance and examining the diet of honeybees. This is particularly relevant for hives foraging on the unique and diverse flora of the Australian continent, with the potential to be used as a novel monitoring tool for honeybee floral resources.

Forensic botany: time to embrace natural history collections, large scale environmental data and environmental DNA

Forensic botany is a diverse discipline that spans many aspects of plant sciences, particularly taxonomy, field botany, anatomy, and ecology. Internationally, there is a significant opportunity to expand the application of forensic botany in criminal investigations, especially war crimes, genocide, homicide, sexual violence, serious physical assault, illegal trade in endangered species and wildlife crime. In civil proceedings, forensic botany may, for example, be called upon in trade disputes such as accidental contamination of commodities. Despite the potential, there are barriers to the wider application of forensic botany in criminal cases; there is a widespread need to improve the efficiency of botanical trace evidence identification. This could partly be addressed by embracing innovations in image recognition and by accessing the huge quantity of specimens and images housed in natural history collections worldwide. Additionally, the recent advances in DNA sequencing technologies and the expansion of environmental DNA (eDNA) and forensic ecogenomics, offers opportunities to more rapidly provide species-level identifications. The impact of taphonomic processes upon vegetation, and vice versa, remains poorly understood; improved understanding of these interactions and their ecological impacts may be invaluable in improving clandestine burial search protocols.

Barcode UK: A complete DNA barcoding resource for the flowering plants and conifers of the United Kingdom

DNA barcoding and metabarcoding provide new avenues for investigating biological systems. These techniques require well-curated reference libraries with extensive coverage. Generating an exhaustive national DNA barcode reference library can open up new avenues of research in ecology, evolution and conservation, yet few studies to date have created such a resource. In plant DNA barcoding, herbarium collections provide taxonomically robust material but also pose challenges in lab processing. Here, we present a national DNA barcoding resource covering all of the native flowering plants and conifers of the United Kingdom. This represents 1,482 plant species, with the majority of specimens (81%) sourced from herbaria. Using Sanger sequencing of the plant DNA barcode markers, rbcL, matK, and ITS2, at least one DNA barcode was retrieved from 98% of the UK flora. We sampled from multiple individuals, resulting in a species coverage for rbcL of 96% (4,477 sequences), 90% for matK (3,259 sequences) and 75% for ITS2 (2,585 sequences). Sequence recovery was lower for herbarium material compared to fresh collections, with the age of the specimen having a significant effect on the success of sequence recovery. Species level discrimination was highest with ITS2, however, the ability to successfully retrieve a sequence was lowest for this region. Analyses of the genetic distinctiveness of species across a complete flora showed DNA barcoding to be informative for all but the most taxonomically complex groups. The UK flora DNA barcode reference library provides an important resource for many applications that require plant identification from DNA.

Temporal Detection Limits of Remnant Larval Bloodmeals in Nymphal Ixodes scapularis (Say, Ixodida: Ixodidae) Using Two Next-Generation Sequencing DNA Barcoding Assays

Using next-generation sequencing DNA barcoding, we aimed to determine: 1) if the larval bloodmeal can be detected in Ixodes scapularis nymphs and 2) the post-moult temporal window for detection of the larval bloodmeal. Subsets of 30 nymphs fed on a domestic rabbit (Oryctolagus cuniculus Linnaeus, Lagomorphia: Leporidae) as larvae were reared and frozen at 11 time points post-moult, up to 150 d. Vertebrate DNA was amplified using novel universal (UP) and species-specific primers (SSP) and sequenced for comparison against cytochrome c oxidase subunit I barcodes to infer host identification. Detectable bloodmeals decreased as time since moult increased for both assays. For the SSP assay, detection of bloodmeals decreased from 96.7% (n = 29/30) in day 0 nymphs to 3.3% (n = 1/30) and 6.7% (n = 2/30) at 4- and 5-mo post-moult, respectively. A shorter temporal detection period was achieved with the UP assay, declining from 16.7% (n = 5/30) in day 0 nymphs to 0/30 in 3-d-old nymphs. Bloodmeal detection was nonexistent for the remaining cohorts, with the exception of 1/30 nymphs at 2-mo post-moult. Host detection was significantly more likely using the SSP assay compared to the UP assay in the first three time cohorts (day 0: χ 2 = 39.1, P < 0.005; day 2: χ 2 = 19.2, P < 0.005; day 3: χ 2 = 23.3, P < 0.005). Regardless of the primer set used, the next-generation sequencing DNA barcoding assay was able to detect host DNA from a larval bloodmeal in the nymphal life stage; however, a short window with a high proportion of detection post-moult was achieved.

DNA traces the origin of honey by identifying plants, bacteria and fungi

The regional origin of a food product commonly affects its value. To this, DNA-based identification of tissue remains could offer fine resolution. For honey, this would allow the usage of not only pollen but all plant tissue, and also that of microbes in the product, for discerning the origin. Here we examined how plant, bacterial and fungal taxa identified by DNA metabarcoding and metagenomics differentiate between honey samples from three neighbouring countries. To establish how the taxonomic contents of honey reflect the country of origin, we used joint species distribution modelling. At the lowest taxonomic level by metabarcoding, with operational taxonomic units, the country of origin explained the majority of variation in the data (70-79%), with plant and fungal gene regions providing the clearest distinction between countries. At the taxonomic level of genera, plants provided the most separation between countries with both metabarcoding and metagenomics. The DNA-based methods distinguish the countries more than the morphological pollen identification and the removal of pollen has only a minor effect on taxonomic recovery by DNA. As we find good resolution among honeys from regions with similar biota, DNA-based methods hold great promise for resolving honey origins among more different regions.

The application of next-generation sequence-based DNA barcoding for bloodmeal detection in host-seeking wild-caught Ixodes scapularis nymphs

Objective

Our objective was to apply next-generation sequence-based DNA barcoding to identify the remnant larval bloodmeals in wild-caught host-seeking (unengorged) Ixodes scapularis nymphs (n = 216). To infer host species identification, vertebrate DNA was amplified using universal primers for cytochrome c oxidase subunit I (COI) and sequenced using next-generation sequencing (NGS) for comparison against known barcode references.

Results

Bloodmeal identification was unsuccessful in most samples (99% of 216 specimens) demonstrating a very low detection rate of this assay. Sequences that surpassed quality thresholds were obtained for 41.7% of nymphs (n = 90) and of those, confident species identification was obtained for 15.6% of nymphs (n = 14). Wild host identifications were only obtained from 2 specimens, where DNA from the eastern grey squirrel (Sciurus carolinensis) was identified. Human and bovine DNA was identified in remaining nymphs and considered to be contaminants. Further optimization of the technique is required to improve detection of remnant bloodmeals in host-seeking nymphs.

Testing the effect of pollen exine rupture on metabarcoding with Illumina sequencing

Pollen metabarcoding has received much attention recently for its potential to increase taxonomic resolution of the identifications of pollen grains necessary for various public health, ecological and environmental inquiry. However, methodologies implemented are widely varied across studies confounding comparisons and casting uncertainty on the reliability of results. In this study, we investigated part of the methodology, the effects of level of exine rupture and lysis incubation time, on the performance of DNA extraction and Illumina sequencing. We examined 15 species of plants from 12 families with pollen that varies in size, shape, and aperture number to evaluate effort necessary for exine rupture. Then created mock communities of 14 of the species from DNA extractions at 4 levels of exine rupture (0, 33, 67, and 100%) and two levels of increased lysis incubation time without exine rupture (2 or 24 hours). Quantities of these DNA extractions displayed a positive correlation between increased rupture and DNA yield, however increasing time of lysis incubation was associated with decreased DNA yield. Illumina sequencing was performed with these artificial community treatments with three common plant DNA barcode regions (rbcL, ITS1, ITS2) with two different primer pairings for ITS2 and rbcL. We found decreased performance in treatments with 0% or 100% exine rupture compared to 33% and 67% rupture, based on deviation from expected proportions and species retrieval, and increased lysis incubation was found to be detrimental to results.

Employing DNA metabarcoding to determine the geographical origin of honey

Unfavourable climatic conditions force Iranian beekeepers to translocate over large distances in the course of the year. However, irrespective of the main place of production, the honey is always labeled with the name of the beekeepers' hometown, which leads consequently to mislabeled products. The present study investigates the capability of DNA metabarcoding to locate the geographical origin of honey. The molecular markers (ITS2 and rbcL) allowed identification of 926 plant species in studied samples. A comprehensive review of floristic reference books specified 34 key species that could be used to successfully determine the geographical origin in 91.4% of samples. These key species were usually present in honey with tiny amounts and thus, conventional palynology might not be able to detect them. The present investigation indicates that although ITS2 is able to detect more species than rbcL, utilizing a combination of both markers provides more robust evidence of geographical origin.

DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand

Traditional medicines are widely traded across the globe and have received considerable attention in the recent past, with expectations of heightened demand in the future. However, there are increasing global concerns over admixture, which can affect the quality, safety, and efficacy of herbal medicinal products. In this study, we aimed to use DNA metabarcoding to identify 39 Thai herbal products on the Thai National List of Essential Medicines (NLEM) and assess species composition and admixture. Among the products, 24 samples were in-house-prepared formulations, and 15 samples were registered formulations. In our study, DNA metabarcoding analysis using ITS2 and rbcL barcode regions were employed to identify herbal ingredients mentioned in the products. The nuclear region, ITS2, was able to identify herbal ingredients in the products at the genus- and family-levels in 55% and 63% of cases, respectively. The chloroplast gene, rbcL, enabled genus- and family-level identifications in 58% and 73% of cases, respectively. In addition, plant species were detected in larger numbers (Family identified, absolute %) in registered herbal products than in in-house-prepared formulations. The level of fidelity increases concerns about the reliability of the products. This study highlights that DNA metabarcoding is a useful analytical tool when combined with advanced chemical techniques for the identification of plant species in highly processed, multi-ingredient herbal products.

An Alternative, High Throughput Method to Identify Csd Alleles of the Honey Bee

Applying instrumental insemination in closely related honey bee colonies often leads to frequent lethality of offspring causing colony collapse. This is due to the peculiarities of honey bee reproductive biology, where the complementary sex determination (csd) gene drives sex determination within a haplodiploid system. Diploid drones containing homozygous genotypes are lethal. Tracking of csd alleles using molecular markers prevents this unwanted event in closed breeding programs. Our approach described here is based on high throughput sequencing (HTS) that provides more data than traditional molecular techniques and is capable of analysing sources containing multiple alleles, including diploid individuals as the bee queen. The approach combines HTS technique and clipping wings as a minimally invasive method to detect the complementary sex determiner (csd) alleles directly from honey bee queens. Furthermore, it might also be suitable for screening alleles of honey harvested from hives of a closed breeding facility. Data on alleles of the csd gene from different honey bee subspecies are provided. It might contribute to future databases that could potentially be used to track the origin of honey. With the help of tracking csd alleles, more focused crossings will be possible, which could in turn accelerate honey bee breeding programmes targeting increase tolerance against varroosis as well.

Microbial metabarcoding highlights different bacterial and fungal populations in honey samples from local beekeepers and market in north-eastern Italy

Due to its chemical properties, honey does not foster the growth of microorganisms, however it may contain a rich microbial community, including viable, stressed, and not viable microbes. In order to characterize honey microbiota focusing on the difference between products from beekeepers and large retail in the present study a culture-independent approach based on DNA metabarcoding was applied. Honey samples were collected from Local Beekeepers (LB) and Market sales (M) during four years with the aim to investigate the microbiological quality in the honey market. Extraction and amplification of DNA from honey samples showed reduced efficiency with increasing age of honey, with the loss of 50-80% of samples four years old (2014). For this reason, only samples of similar age were compared and the analysis of microbial communities focused on year 2017, for a total of 75 samples. Differences in alpha and beta-diversity were evidenced comparing microbial communities between LB and M samples. In particular, contaminant bacteria dominated the microbiota in M samples while LB samples were enriched in Lactic Acid Bacteria (LAB) that cannot be isolated with culture-dependent approaches.

Shotgun sequencing of honey DNA can describe honey bee derived environmental signatures and the honey bee hologenome complexity

Honey bees are large-scale monitoring tools due to their extensive environmental exploration. In their activities and from the hive ecosystem complex, they get in close contact with many organisms whose traces can be transferred into the honey, which can represent an interesting reservoir of environmental DNA (eDNA) signatures and information useful to analyse the honey bee hologenome complexity. In this study, we tested a deep shotgun sequencing approach of honey DNA coupled with a specifically adapted bioinformatic pipeline. This methodology was applied to a few honey samples pointing out DNA sequences from 191 organisms spanning different kingdoms or phyla (viruses, bacteria, plants, fungi, protozoans, arthropods, mammals). Bacteria included the largest number of species. These multi-kingdom signatures listed common hive and honey bee gut microorganisms, honey bee pathogens, parasites and pests, which resembled a complex interplay that might provide a general picture of the honey bee pathosphere. Based on the Apis mellifera filamentous virus genome diversity (the most abundant detected DNA source) we obtained information that could define the origin of the honey at the apiary level. Mining Apis mellifera sequences made it possible to identify the honey bee subspecies both at the mitochondrial and nuclear genome levels.

Microfluidic Enrichment Barcoding (MEBarcoding): a new method for high throughput plant DNA barcoding

DNA barcoding is a valuable tool to support species identification with broad applications from traditional taxonomy, ecology, forensics, food analysis, and environmental science. We introduce Microfluidic Enrichment Barcoding (MEBarcoding) for plant DNA Barcoding, a cost-effective method for high-throughput DNA barcoding. MEBarcoding uses the Fluidigm Access Array to simultaneously amplify targeted regions for 48 DNA samples and hundreds of PCR primer pairs (producing up to 23,040 PCR products) during a single thermal cycling protocol. As a proof of concept, we developed a microfluidic PCR workflow using the Fluidigm Access Array and Illumina MiSeq. We tested 96 samples for each of the four primary DNA barcode loci in plants: rbcL, matK, trnH-psbA, and ITS. This workflow was used to build a reference library for 78 families and 96 genera from all major plant lineages - many currently lacking in public databases. Our results show that this technique is an efficient alternative to traditional PCR and Sanger sequencing to generate large amounts of plant DNA barcodes and build more comprehensive barcode databases.

Food authentication in real life: How to link nontargeted approaches with routine analytics?

In times of increasing globalization and the resulting complexity of trade flows, securing food quality is an increasing challenge. The development of analytical methods for checking the integrity and, thus, the safety of food is one of the central questions for actors from science, politics, and industry. Targeted methods, for the detection of a few selected analytes, still play the most important role in routine analysis. In the past 5 years, nontargeted methods that do not aim at individual analytes but on analyte profiles that are as comprehensive as possible have increasingly come into focus. Instead of investigating individual chemical structures, data patterns are collected, evaluated and, depending on the problem, fed into databases that can be used for further nontargeted approaches. Alternatively, individual markers can be extracted and transferred to targeted methods. Such an approach requires (i) the availability of authentic reference material, (ii) the corresponding high-resolution laboratory infrastructure, and (iii) extensive expertise in processing and storing very large amounts of data. Probably due to the requirements mentioned above, only a few methods have really established themselves in routine analysis. This review article focuses on the establishment of nontargeted methods in routine laboratories. Challenges are summarized and possible solutions are presented.