A DNA barcoding approach to characterize pollen collected by honeybees

Generalisation and specialisation in hoverfly (Syrphidae) grassland pollen transport networks revealed by DNA metabarcoding

Pollination by insects is a key ecosystem service and important to wider ecosystem function. Most species-level pollination networks studied have a generalised structure, with plants having several potential pollinators, and pollinators in turn visiting a number of different plant species. This is in apparent contrast to a plant's need for efficient conspecific pollen transfer. The aim of this study was to investigate the structure of pollen transport networks at three levels of biological hierarchy: community, species and individual. We did this using hoverflies in the genus Eristalis, a key group of non-Hymenopteran pollinators. We constructed pollen transport networks using DNA metabarcoding to identify pollen. We captured hoverflies in conservation grasslands in west Wales, UK, removed external pollen loads, sequenced the pollen DNA on the Illumina MiSeq platform using the standard plant barcode rbcL, and matched sequences using a pre-existing plant DNA barcode reference library. We found that Eristalis hoverflies transport pollen from 65 plant taxa, more than previously appreciated. Networks were generalised at the site and species level, suggesting some degree of functional redundancy, and were more generalised in late summer compared to early summer. In contrast, pollen transport at the individual level showed some degree of specialisation. Hoverflies defined as "single-plant visitors" varied from 40% of those captured in early summer to 24% in late summer. Individual hoverflies became more generalised in late summer, possibly in response to an increase in floral resources. Rubus fruticosus agg. and Succisa pratensis were key plant species for hoverflies at our sites Our results contribute to resolving the apparent paradox of how generalised pollinator networks can provide efficient pollination to plant species. Generalised hoverfly pollen transport networks may result from a varied range of short-term specialised feeding bouts by individual insects. The generalisation and functional redundancy of Eristalis pollen transport networks may increase the stability of the pollination service they deliver.

A DNA barcoding method for identifying and quantifying the composition of pollen species collected by European honeybees, Apis mellifera (Hymenoptera: Apidae)

The European honeybee, Apis mellifera L. (Hymenoptera: Apidae), is the most important crop pollinator, and there is an urgent need for a sustained supply of honeybee colonies. Understanding the availability of pollen resources around apiaries throughout the brood-rearing season is crucial to increasing the number of colonies. However, detailed information on the floral resources used by honeybees is limited due to a scarcity of efficient methods for identifying pollen species composition. Therefore, we developed a DNA barcoding method for identifying the species of each pollen pellet and for quantifying the species composition by summing the weights of the pellets for each species. To establish the molecular biological protocol, we analyzed 1008 pellets collected between late July and early September 2016 from five hives placed in a forest/agricultural landscape of Hokkaido, northern Japan. Pollen was classified into 31 plant taxa, of which 29 were identified with satisfactory discrimination (25 species and 4 genera) using trnL-trnF and ITS2 as DNA barcoding regions together with available floral and phenological information. The remaining two taxa were classified to the species level using other DNA barcoding regions. Of the 1008 pollen pellets tested, 1005 (99.7%) were successfully identified. As an example of the use of this method, we demonstrated the change in species composition of pollen pellets collected each week for 9 weeks from the same hive.

New biomolecular tools for aerobiological monitoring: Identification of major allergenic Poaceae species through fast real-time PCR

Grasses (Poaceae) are very common plants, which are widespread in all environments and urban areas. Despite their economical importance, they can represent a problem to humans due to their abundant production of allergenic pollen. Detailed information about the pollen season for these species is needed in order to plan adequate therapies and to warn allergic people about the risks they take in certain areas at certain moments. Moreover, precise identification of the causative species and their allergens is necessary when the patient is treated with allergen‐specific immunotherapy. The intrafamily morphological similarity of grass pollen grains makes it impossible to distinguish which particular species is present in the atmosphere at a given moment. This study aimed at developing new biomolecular tools to analyze aerobiological samples and identifying major allergenic Poaceae taxa at subfamily or species level, exploiting fast real‐time PCR. Protocols were tested for DNA extraction from pollen sampled with volumetric and gravimetric methods. A fragment of the matK plastidial gene was amplified and sequenced in Poaceae species known to have high allergological impact. Species‐ and subfamily‐specific primer–probe systems were designed and tested in fast real‐time PCRs to evaluate the presence of these taxa in aerobiological pollen samples. Species‐specific systems were obtained for four of five studied species. A primer–probe set was also proposed for the detection of Pooideae (a grass subfamily that includes also major cereal grains) in aerobiological samples, as this subfamily includes species carrying both grass allergens from groups 1 and 5. These, among the 11 groups in which grass pollen allergens are classified, are considered responsible for the most frequent and severe symptoms.

DNA metabarcoding uncovers fungal diversity of mixed airborne samples in Italy

Fungal spores and mycelium fragments are particles which become and remain airborne and have been subjects of aerobiological studies. The presence and the abundance of taxa in aerobiological samples can be very variable and impaired by changeable climatic conditions. Because many fungi produce mycotoxins and both their mycelium fragments and spores are potential allergens, monitoring the presence of these taxa is of key importance. So far data on exposure and sensitization to fungal allergens are mainly based on the assessment of few, easily identifiable taxa and focused only on certain environments. The microscopic method used to analyze aerobiological samples and the inconspicuous fungal characters do not allow a in depth taxonomical identification. Here, we present a first assessment of fungal diversity from airborne samples using a DNA metabarcoding analysis. The nuclear ITS2 region was selected as barcode to catch fungal diversity in mixed airborne samples gathered during two weeks in four sites of North-Eastern and Central Italy. We assessed the taxonomic composition and diversity within and among the sampled sites and compared the molecular data with those obtained by traditional microscopy. The molecular analyses provide a tenfold more comprehensive determination of the taxa than the traditional morphological inspections. Our results prove that the metabarcoding analysis is a promising approach to increases quality and sensitivity of the aerobiological monitoring. The laboratory and bioinformatic workflow implemented here is now suitable for routine, high-throughput, regional analyses of airborne fungi.

Molecular-Assisted Pollen Grain Analysis Reveals Spatiotemporal Origin of Long-Distance Migrants of a Noctuid Moth

Pollen grains are regularly used as markers to determine an insect’s movement patterns or host (plant) feeding behavior, yet conventional morphology-based pollen grain analysis (or palynology) encounters a number of important limitations. In the present study, we combine conventional analytical approaches with DNA meta-barcoding to identify pollen grains attached to migrating adults of the turnip moth, Agrotis segetum (Lepidoptera: Noctuidae) in Northeast China. More specifically, pollen grains were dislodged from 2566 A. segetum long-distance migrants captured on Beihuang Island (Bohai Sea) and identified to many (plant) species level. Pollen belonged to 26 families of plants, including Fagaceae, Oleaceae, Leguminosae, Asteraceae, Pinaceae and Rosaceae, including common species such as Citrus sinensis, Olea europaea, Ligustrum lucidum, Robinia pseudoacacia, Castanopsis echinocarpa, Melia azedarach and Castanea henryi. As the above plants are indigenous to southern climes, we deduce that A. segetum forage on plants in those locales prior to engaging in northward spring migration. Our work validates the use of DNA-assisted approaches in lepidopteran pollination ecology research and provides unique and valuable information on the adult feeding range and geographical origin of A. segetum. Our findings also enable targeted (area-wide) pest management interventions or guide the future isolation of volatile attractants.

DNA metabarcoding data unveils invisible pollination networks

Animal pollination, essential for both ecological services and ecosystem functioning, is threatened by ongoing global changes. New methodologies to decipher their effects on pollinator composition to ecosystem health are urgently required. We compare the main structural parameters of pollination networks based on DNA metabarcoding data with networks based on direct observations of insect visits to plants at three resolution levels. By detecting numerous additional hidden interactions, metabarcoding data largely alters the properties of the pollination networks compared to visit surveys. Molecular data shows that pollinators are much more generalist than expected from visit surveys. However, pollinator species were composed of relatively specialized individuals and formed functional groups highly specialized upon floral morphs. We discuss pros and cons of metabarcoding data relative to data obtained from traditional methods and their potential contribution to both current and future research. This molecular method seems a very promising avenue to address many outstanding scientific issues at a resolution level which remains unattained to date; especially for those studies requiring pollinator and plant community investigations over macro-ecological scales.

Forecasting pollination declines through DNA barcoding: the potential contributions of macroecological and macroevolutionary scales of inquiry

While pollinators are widely acknowledged as important contributors to seed production in plant communities, we do not yet have a good understanding of the importance of pollinator specialists for this ecosystem service. Determination of the prevalence of pollinator specialists is often hindered by the occurrence of cryptic species and the limitations of observational data on pollinator visitation rates, two areas where DNA barcoding of pollinators and pollen can be useful. Further, the demonstrated adequacy of pollen DNA barcoding from historical records offers opportunities to observe the effects of pollinator loss over longer timescales, and phylogenetic approaches can elucidate the historical rates of extinction of specialist lineages. In this Viewpoint article, we review how advances in DNA barcoding and metabarcoding of plants and pollinators have brought important developments to our understanding of specialization in plant-pollinator interactions. We then put forth several lines of inquiry that we feel are especially promising for providing insight on changes in plant-pollinator interactions over space and time. Obtaining estimates of the effects of reductions in specialists will contribute to forecasting the loss of ecosystem services that will accompany the erosion of plant and pollinator diversity.

Molecular analysis confirms the long-distance transport of Juniperus ashei pollen

Although considered rare, airborne pollen can be deposited far from its place of origin under a confluence of favorable conditions. Temporally anomalous records of Cupressacean pollen collected from January air samples in London, Ontario, Canada have been cited as a new case of long-distance transport. Data on pollination season implicated Juniperus ashei (mountain cedar), with populations in central Texas and south central Oklahoma, as the nearest source of the Cupressacean pollen in the Canadian air samples. This finding is of special significance given the allergenicity of mountain cedar pollen. While microscopy is used extensively to identify particles in the air spora, pollen from all members of the Cupressaceae, including Juniperus, are morphologically indistinguishable. Consequently, we implemented a molecular approach to characterize Juniperus pollen using PCR in order to test the long-distance transport hypothesis. Our PCR results using species-specific primers confirmed that the anomalous Cupressacean pollen collected in Canada was from J. ashei. Forward trajectory analysis from source areas in Texas and the Arbuckle Mountains in Oklahoma and backward trajectory analysis from the destination area near London, Ontario were completed using models implemented in HYSPLIT4 (Hybrid Single-Particle Lagrangian Integrated Trajectory). Results from these trajectory analyses strongly supported the conclusion that the J. ashei pollen detected in Canada had its origins in Texas or Oklahoma. The results from the molecular findings are significant as they provide a new method to confirm the long-distance transport of pollen that bears allergenic importance.

A Comparison of Honey Bee-Collected Pollen From Working Agricultural Lands Using Light Microscopy and ITS Metabarcoding

Taxonomic identification of pollen has historically been accomplished via light microscopy but requires specialized knowledge and reference collections, particularly when identification to lower taxonomic levels is necessary. Recently, next-generation sequencing technology has been used as a cost-effective alternative for identifying bee-collected pollen; however, this novel approach has not been tested on a spatially or temporally robust number of pollen samples. Here, we compare pollen identification results derived from light microscopy and DNA sequencing techniques with samples collected from honey bee colonies embedded within a gradient of intensive agricultural landscapes in the Northern Great Plains throughout the 2010-2011 growing seasons. We demonstrate that at all taxonomic levels, DNA sequencing was able to discern a greater number of taxa, and was particularly useful for the identification of infrequently detected species. Importantly, substantial phenological overlap did occur for commonly detected taxa using either technique, suggesting that DNA sequencing is an appropriate, and enhancing, substitutive technique for accurately capturing the breadth of bee-collected species of pollen present across agricultural landscapes. We also show that honey bees located in high and low intensity agricultural settings forage on dissimilar plants, though with overlap of the most abundantly collected pollen taxa. We highlight practical applications of utilizing sequencing technology, including addressing ecological issues surrounding land use, climate change, importance of taxa relative to abundance, and evaluating the impact of conservation program habitat enhancement efforts.

Pollen DNA barcoding: current applications and future prospects

Identification of the species origin of pollen has many applications, including assessment of plant–pollinator networks, reconstruction of ancient plant communities, product authentication, allergen monitoring, and forensics. Such applications, however, have previously been limited by microscopy-based identification of pollen, which is slow, has low taxonomic resolution, and has few expert practitioners. One alternative is pollen DNA barcoding, which could overcome these issues. Recent studies demonstrate that both chloroplast and nuclear barcoding markers can be amplified from pollen. These recent validations of pollen metabarcoding indicate that now is the time for researchers in various fields to consider applying these methods to their research programs. In this paper, we review the nascent field of pollen DNA barcoding and discuss potential new applications of this technology, highlighting existing limitations and future research developments that will improve its utility in a wide range of applications.

Evaluating the efficacy of restoration plantings through DNA barcoding of frugivorous bird diets

Frugivores are critical components of restoration programs because they are seed dispersers. Thus, knowledge about bird-plant trophic relationships is essential in the evaluation of the efficacy of restoration processes. Traditionally, the diet of frugivores is characterized by microscopically identifying plant residues in droppings, which is time-consuming, requires botanical knowledge, and cannot be used for fragments lacking detectable morphological characteristics (e.g., fragmented seeds and skins). We examined whether DNA barcoding can be used as a universal tool to rapidly characterize the diet of a frugivorous bird, Eurasian blackcap (Sylvia atricapilla). We used the DNA barcoding results to assess restoration efforts and monitor the diversity of potentially dispersed plants in a protected area in northern Italy. We collected 642 Eurasian Blackcap droppings at the restored site during the autumn migration over 3 years. Intact seeds and fragmented plant material were analyzed at 2 plastidial barcode loci (rbcL and trnH-psbA), and the resulting plant identifications were validated by comparison with a reference molecular data set of local flora. At least 17 plant species, including 7 of the 11 newly transplanted taxa, were found. Our results demonstrate the potential for DNA barcoding to be used to monitor the effectiveness of restoration plantings and to obtain information about fruit consumption and dispersal of invasive or unexpected plant species. Such an approach provides valuable information that could be used to study local plant biodiversity and to survey its evolution over time.

Using metabarcoding to reveal and quantify plant-pollinator interactions

Given the ongoing decline of both pollinators and plants, it is crucial to implement effective methods to describe complex pollination networks across time and space in a comprehensive and high-throughput way. Here we tested if metabarcoding may circumvent the limits of conventional methodologies in detecting and quantifying plant-pollinator interactions. Metabarcoding experiments on pollen DNA mixtures described a positive relationship between the amounts of DNA from focal species and the number of trnL and ITS1 sequences yielded. The study of pollen loads of insects captured in plant communities revealed that as compared to the observation of visits, metabarcoding revealed 2.5 times more plant species involved in plant-pollinator interactions. We further observed a tight positive relationship between the pollen-carrying capacities of insect taxa and the number of trnL and ITS1 sequences. The number of visits received per plant species also positively correlated to the number of their ITS1 and trnL sequences in insect pollen loads. By revealing interactions hard to observe otherwise, metabarcoding significantly enlarges the spatiotemporal observation window of pollination interactions. By providing new qualitative and quantitative information, metabarcoding holds great promise for investigating diverse facets of interactions and will provide a new perception of pollination networks as a whole.

Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food

In the last decades, food science has greatly developed, turning from the consideration of food as mere source of energy to a growing awareness on its importance for health and particularly in reducing the risk of diseases. Such vision led to an increasing attention towards the origin and quality of raw materials as well as their derived food products. The continuous advance in molecular biology allowed setting up efficient and universal omics tools to unequivocally identify the origin of food items and their traceability. In this review, we considered the application of a genomics approach known as DNA barcoding in characterizing the composition of foodstuffs and its traceability along the food supply chain. Moreover, metabolomics analytical strategies based on Nuclear Magnetic Resonance (NMR) and Mass Spectroscopy (MS) were discussed as they also work well in evaluating food quality. The combination of both approaches allows us to define a sort of molecular labelling of food that is easily understandable by the operators involved in the food sector: producers, distributors, and consumers. Current technologies based on digital information systems such as web platforms and smartphone apps can facilitate the adoption of such molecular labelling.

Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach

PREMISE OF THE STUDY

Difficulties inherent in microscopic pollen identification have resulted in limited implementation for large-scale studies. Metabarcoding, a relatively novel approach, could make pollen analysis less onerous; however, improved understanding of the quantitative capacity of various plant metabarcode regions and primer sets is needed to ensure that such applications are accurate and precise.

METHODS AND RESULTS

We applied metabarcoding, targeting the ITS2, matK, and rbcL loci, to characterize six samples of pollen collected by honey bees, Apis mellifera. Additionally, samples were analyzed by light microscopy. We found significant rank-based associations between the relative abundance of pollen types within our samples as inferred by the two methods.

CONCLUSIONS

Our findings suggest metabarcoding data from plastid loci, as opposed to the ribosomal locus, are more reliable for quantitative characterization of pollen assemblages. Furthermore, multilocus metabarcoding of pollen may be more reliable than single-locus analyses, underscoring the need for discovering novel barcodes and barcode combinations optimized for molecular palynology.

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.

Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach

BACKGROUND

Meta-barcoding of mixed pollen samples constitutes a suitable alternative to conventional pollen identification via light microscopy. Current approaches however have limitations in practicability due to low sample throughput and/or inefficient processing methods, e.g. separate steps for amplification and sample indexing.

RESULTS

We thus developed a new primer-adapter design for high throughput sequencing with the Illumina technology that remedies these issues. It uses a dual-indexing strategy, where sample-specific combinations of forward and reverse identifiers attached to the barcode marker allow high sample throughput with a single sequencing run. It does not require further adapter ligation steps after amplification. We applied this protocol to 384 pollen samples collected by solitary bees and sequenced all samples together on a single Illumina MiSeq v2 flow cell. According to rarefaction curves, 2,000-3,000 high quality reads per sample were sufficient to assess the complete diversity of 95% of the samples. We were able to detect 650 different plant taxa in total, of which 95% were classified at the species level. Together with the laboratory protocol, we also present an update of the reference database used by the classifier software, which increases the total number of covered global plant species included in the database from 37,403 to 72,325 (93% increase).

CONCLUSIONS

This study thus offers improvements for the laboratory and bioinformatical workflow to existing approaches regarding data quantity and quality as well as processing effort and cost-effectiveness. Although only tested for pollen samples, it is furthermore applicable to other research questions requiring plant identification in mixed and challenging samples.

Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem

PREMISE OF THE STUDY

Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. •

METHODS

Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. •

RESULTS

Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. •

DISCUSSION

For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.

Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in an agroecosystem

PREMISE OF THE STUDY

Melissopalynology, the identification of bee-collected pollen, provides insight into the flowers exploited by foraging bees. Information provided by melissopalynology could guide floral enrichment efforts aimed at supporting pollinators, but it has rarely been used because traditional methods of pollen identification are laborious and require expert knowledge. We approach melissopalynology in a novel way, employing a molecular method to study the pollen foraging of honey bees (Apis mellifera) in a landscape dominated by field crops, and compare these results to those obtained by microscopic melissopalynology. •

METHODS

Pollen was collected from honey bee colonies in Madison County, Ohio, USA, during a two-week period in midspring and identified using microscopic methods and ITS2 metabarcoding. •

RESULTS

Metabarcoding identified 19 plant families and exhibited sensitivity for identifying the taxa present in large and diverse pollen samples relative to microscopy, which identified eight families. The bulk of pollen collected by honey bees was from trees (Sapindaceae, Oleaceae, and Rosaceae), although dandelion (Taraxacum officinale) and mustard (Brassicaceae) pollen were also abundant. •

DISCUSSION

For quantitative analysis of pollen, using both metabarcoding and microscopic identification is superior to either individual method. For qualitative analysis, ITS2 metabarcoding is superior, providing heightened sensitivity and genus-level resolution.