Shifts in honeybee foraging reveal historical changes in floral resources

A primer on pollen assignment by nanopore-based DNA sequencing

The possibility to identify plants based on the taxonomic information coming from their pollen grains offers many applications within various biological disciplines. In the past and depending on the application or research in question, pollen origin was analyzed by microscopy, usually preceded by chemical treatment methods. This procedure for identification of pollen grains is both time-consuming and requires expert knowledge of morphological features. Additionally, these microscopically recognizable features usually have a low resolution at species-level. Since a few decades, DNA has been used for the identification of pollen taxa, as sequencing technologies evolved both in their handling and affordability. We discuss advantages and challenges of pollen DNA analyses compared to traditional methods. With readers with little experience in this field in mind, we present a hands-on primer for genetic pollen analysis by nanopore sequencing. As our lab mainly works with pollen collected within agroecological research projects, we focus on pollen collected by pollinating insects. We briefly consider sample collection, storage and processing in the laboratory as well as bioinformatic aspects. Currently, pollen metabarcoding is mostly conducted with next-generation sequencing methods that generate short sequence reads (<1 kb). Increasingly, however, pollen DNA analysis is carried out using the long-read generating (several kb), low-budget and mobile MinION nanopore sequencing platform by Oxford Nanopore Technologies. Therefore, we are focusing on aspects for palynology with the MinION DNA sequencing device.

Geographical and Seasonal Analysis of the Honeybee Microbiome

We previously showed that colonies of thriving and non-thriving honeybees co-located in a single geographically isolated apiary harboured strikingly different microbiomes when sampled at a single time point in the honey season. Here, we profiled the microbiome in returning forager bees from 10 to 12 hives in each of 6 apiaries across the southern half of Ireland, at early, middle, and late time points in the 2019 honey production season. Despite the wide range of geographical locations and forage available, apiary site was not the strongest determinant of the honeybee microbiome. However, there was clear clustering of the honeybee microbiome by time point across all apiaries, independent of which apiary was sampled. The clustering of microbiome by time was weaker although still significant in three of the apiaries, which may be connected to their geographic location and other external factors. The potential forage effect was strongest at the second timepoint (June-July) when the apiaries also displayed greatest difference in microbiome diversity. We identified bacteria in the forager bee microbiome that correlated with hive health as measured by counts of larvae, bees, and honey production. These findings support the hypothesis that the global honeybee microbiome and its constituent species support thriving hives.

Beehives possess their own distinct microbiomes

BACKGROUND

Honeybees use plant material to manufacture their own food. These insect pollinators visit flowers repeatedly to collect nectar and pollen, which are shared with other hive bees to produce honey and beebread. While producing these products, beehives accumulate a considerable number of microbes, including bacteria that derive from plants and different parts of the honeybees' body. Whether bacteria form similar communities amongst beehives, even if located in close proximity, is an ecologically important question that has been addressed in this study. Specific ecological factors such as the surrounding environment and the beekeeping methods used can shape the microbiome of the beehive as a whole, and eventually influence the health of the honeybees and their ecosystem.

RESULTS

We conducted 16S rRNA meta-taxonomic analysis on honey and beebread samples that were collected from 15 apiaries in the southeast of England to quantify the bacteria associated with different beehives. We observed that honeybee products carry a significant variety of bacterial groups that comprise bee commensals, environmental bacteria and symbionts and pathogens of plants and animals. Remarkably, this bacterial diversity differs not only amongst apiaries, but also between the beehives of the same apiary. In particular, the levels of the bee commensals varied significantly, and their fluctuations correlated with the presence of different environmental bacteria and various apiculture practices.

CONCLUSIONS

Our results show that every hive possesses their own distinct microbiome and that this very defined fingerprint is affected by multiple factors such as the nectar and pollen gathered from local plants, the management of the apiaries and the bacterial communities living around the beehives. Based on our findings, we suggest that the microbiome of beehives could be used as a valuable biosensor informing of the health of the honeybees and their surrounding environment.

Citizen science monitoring reveals links between honeybee health, pesticide exposure and seasonal availability of floral resources

We use a national citizen science monitoring scheme to quantify how agricultural intensification affects honeybee diet breadth (number of plant species). To do this we used DNA metabarcoding to identify the plants present in 527 honey samples collected in 2019 across Great Britain. The species richness of forage plants was negatively correlated with arable cropping area, although this was only found early in the year when the abundance of flowering plants was more limited. Within intensively farmed areas, honeybee diets were dominated by Brassica crops (including oilseed rape). We demonstrate how the structure and complexity of honeybee foraging relationships with plants is negatively affected by the area of arable crops surrounding hives. Using information collected from the beekeepers on the incidence of an economically damaging bee disease (Deformed Wing Virus) we found that the occurrence of this disease increased where bees foraged in agricultural land where there was a high use of foliar insecticides. Understanding impacts of land use on resource availability is fundamental to assessing long-term viability of pollinator populations. These findings highlight the importance of supporting temporally timed resources as mitigation strategies to support wider pollinator population viability.

Environmental DNA analysis as an emerging non-destructive method for plant biodiversity monitoring: a review

Environmental DNA (eDNA) analysis has recently transformed and modernized biodiversity monitoring. The accurate detection, and to some extent quantification, of organisms (individuals/populations/communities) in environmental samples is galvanizing eDNA as a successful cost and time-efficient biomonitoring technique. Currently, eDNA's application to plants remains more limited in implementation and scope compared to animals and microorganisms. This review evaluates the development of eDNA-based methods for (vascular) plants, comparing its performance and power of detection with that of traditional methods, to critically evaluate and advise best-practices needed to innovate plant biomonitoring. Recent advancements, standardization and field applications of eDNA-based methods have provided enough scope to utilize it in conservation biology for numerous organisms. Despite our review demonstrating only 13% of all eDNA studies focus on plant taxa to date, eDNA has considerable environmental DNA has considerable potential for plants, where successful detection of invasive, endangered and rare species, and community-level interpretations have provided proof-of-concept. Monitoring methods using eDNA were found to be equal or more effective than traditional methods; however, species detection increased when both methods were coupled. Additionally, eDNA methods were found to be effective in studying species interactions, community dynamics and even effects of anthropogenic pressure. Currently, elimination of potential obstacles (e.g. lack of relevant DNA reference libraries for plants) and the development of user-friendly protocols would greatly contribute to comprehensive eDNA-based plant monitoring programs. This is particularly needed in the data-depauperate tropics and for some plant groups (e.g., Bryophytes and Pteridophytes). We further advocate to coupling traditional methods with eDNA approaches, as the former is often cheaper and methodologically more straightforward, while the latter offers non-destructive approaches with increased discrimination ability. Furthermore, to make a global platform for eDNA, governmental and academic-industrial collaborations are essential to make eDNA surveys a broadly adopted and implemented, rapid, cost-effective and non-invasive plant monitoring approach.

Moths complement bumblebee pollination of red clover: a case for day-and-night insect surveillance

Recent decades have seen a surge in awareness about insect pollinator declines. Social bees receive the most attention, but most flower-visiting species are lesser known, non-bee insects. Nocturnal flower visitors, e.g. moths, are especially difficult to observe and largely ignored in pollination studies. Clearly, achieving balanced monitoring of all pollinator taxa represents a major scientific challenge. Here, we use time-lapse cameras for season-wide, day-and-night pollinator surveillance of Trifolium pratense (L.; red clover) in an alpine grassland. We reveal the first evidence to suggest that moths, mainly Noctua pronuba (L.; large yellow underwing), pollinate this important wildflower and forage crop, providing 34% of visits (bumblebees: 61%). This is a remarkable finding; moths have received no recognition throughout a century of T. pratense pollinator research. We conclude that despite a non-negligible frequency and duration of nocturnal flower visits, nocturnal pollinators of T. pratense have been systematically overlooked. We further show how the relationship between visitation and seed set may only become clear after accounting for moth visits. As such, population trends in moths, as well as bees, could profoundly affect T. pratense seed yield. Ultimately, camera surveillance gives fair representation to non-bee pollinators and lays a foundation for automated monitoring of species interactions in future.

Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey

Honeybees (Apis mellifera) continue to succumb to human and environmental pressures despite their crucial role in providing essential ecosystem services. Owing to their foraging and honey production activities, honeybees form complex relationships with species across all domains, such as plants, viruses, bacteria and other hive pests, making honey a valuable biomonitoring tool for assessing their ecological niche. Thus, the application of honey shotgun metagenomics (SM) has paved the way for a detailed description of the species honeybees interact with. Nevertheless, SM bioinformatics tools and DNA extraction methods rely on resources not necessarily optimized for honey. In this study, we compared five widely used taxonomic classifiers using simulated species communities commonly found in honey. We found that Kraken 2 with a threshold of 0.5 performs best in assessing species distribution. We also optimized a simple NaOH-based honey DNA extraction methodology (Direct-SM), which profiled species seasonal variability similarly to an established column-based DNA extraction approach (SM). Both approaches produce results consistent with melissopalinology analysis describing the botanical landscape surrounding the apiary. Interestingly, we detected a strong stability of the bacteria constituting the core and noncore gut microbiome across seasons, pointing to the potential utility of honey for noninvasive assessment of bee microbiota. Finally, the Direct-SM approach to detect Varroa correlates well with the biomonitoring of mite infestation observed in hives. These observations suggest that Direct-SM methodology has the potential to comprehensively describe honeybee ecological niches and can be tested as a building block for large-scale studies to assess bee health in the field.

Temporal Patterns of Honeybee Foraging in a Diverse Floral Landscape Revealed Using Pollen DNA Metabarcoding of Honey

Understanding the plants pollinators use through the year is vital to support pollinator populations and mitigate for declines in floral resources due to habitat loss. DNA metabarcoding allows the temporal picture of nectar and pollen foraging to be examined in detail. Here, we use DNA metabarcoding to examine the forage use of honeybees (Apis mellifera L.) within a florally diverse landscape within the UK, documenting the key forage plants used and seasonal progression over two years. The total number of plant taxa detected in the honey was 120, but only 16 of these were found with a high relative read abundance of DNA, across the main foraging months (April-September). Only a small proportion of the available flowering genera in the landscape were used by the honeybees. The greatest relative read abundance came from native or near-native plants, including Rubus spp., Trifolium repens, the Maleae tribe including Crataegus, Malus and Cotoneaster, and Hedera helix. Tree species were important forage in the spring months, followed by increased use of herbs and shrubs later in the foraging season. Garden habitat increased the taxon richness of native, near-native and horticultural plants found in the honey. Although horticultural plants were rarely found abundantly within the honey samples, they may be important for increasing nutritional diversity of the pollen forage.

Seasonality and Landscape Composition Drive the Diversity of Pollen Collected by Managed Honey Bees

The western honey bee, Apis mellifera, is the most important and widespread managed pollinator species. Honey bee diet is based on nectar and pollen, and pollen diversity and composition, in particular, affect colony health and fitness. As landscape composition is strongly linked to floral resource heterogeneity, it could influence the resource intake of honey bees. This work aimed to explore how the composition of pollen collected by honey bees was modulated by seasonality and landscape composition heterogeneity in a mountainous cultivated area of Northern Italy. We selected 13 locations, and at each location, we placed two honey bee colonies from which we collected pollen samples every month during the whole flowering season for two consecutive years. We then analyzed pollen samples in the laboratory and determined the Shannon diversity index of each pollen sample and the temporal pollen taxon replacement. We extracted the cover of the main habitat types at three spatial scales and tested the effect of landscape diversity and composition using Principal Component Analysis. Honey bees foraged on a high number of floral resources, however, they mostly collected pollen from a small number of taxa, with pollen type composition changing throughout the flowering season. In early spring and late summer, most pollen grains were collected from a few plant species, while from May to August the number of collected pollen types was significantly higher. Landscape composition affected pollen diversity only at the end of the flowering season. While honey bees were able to collect highly diverse pollen throughout spring and summer regardless of landscape composition, in late summer, when pollen collected is fundamental for the overwintering of the colony and its development in the following season, semi-natural areas became crucial for honey bee foraging activities, with pollen diversity increasing with increasing percentages of semi-natural areas. Our research highlighted the importance for honey bees of certain seasonal resources and of semi-natural habitats at the end of the flowering season, which ensure the subsistence of their colonies throughout the year.

Using DNA Metabarcoding to Identify Floral Visitation by Pollinators

The identification of floral visitation by pollinators provides an opportunity to improve our understanding of the fine-scale ecological interactions between plants and pollinators, contributing to biodiversity conservation and promoting ecosystem health. In this review, we outline the various methods which can be used to identify floral visitation, including plant-focused and insect-focused methods. We reviewed the literature covering the ways in which DNA metabarcoding has been used to answer ecological questions relating to plant use by pollinators and discuss the findings of this research. We present detailed methodological considerations for each step of the metabarcoding workflow, from sampling through to amplification, and finally bioinformatic analysis. Detailed guidance is provided to researchers for utilisation of these techniques, emphasising the importance of standardisation of methods and improving the reliability of results. Future opportunities and directions of using molecular methods to analyse plant–pollinator interactions are then discussed.

Preservation methods of honey bee-collected pollen are not a source of bias in ITS2 metabarcoding

Pollen metabarcoding is emerging as a powerful tool for ecological research and offers unprecedented scale in citizen science projects for environmental monitoring via honey bees. Biases in metabarcoding can be introduced at any stage of sample processing and preservation is at the forefront of the pipeline. While in metabarcoding studies pollen has been preserved at - 20 °C (FRZ), this is not the best method for citizen scientists. Herein, we compared this method with ethanol (EtOH), silica gel (SG) and room temperature (RT) for preservation of pollen collected from hives in Austria and Denmark. After ~ 4 months of storage, DNAs were extracted with a food kit, and their quality and concentration measured. Most DNA extracts exhibited 260/280 absorbance ratios close to the optimal 1.8, with RT samples from Austria performing slightly worse than FRZ and SG samples (P < 0.027). Statistical differences were also detected for DNA concentration, with EtOH samples producing lower yields than RT and FRZ samples in both countries and SG in Austria (P < 0.042). Yet, qualitative and quantitative assessments of floral composition obtained using high-throughput sequencing with the ITS2 barcode gave non-significant effects of preservation methods on richness, relative abundance and Shannon diversity, in both countries. While freezing and ethanol are commonly employed for archiving tissue for molecular applications, desiccation is cheaper and easier to use regarding both storage and transportation. Since SG is less dependent on ambient humidity and less prone to contamination than RT, we recommend SG for preserving pollen for metabarcoding. SG is straightforward for laymen to use and hence robust for widespread application in citizen science studies.

Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches

Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable.

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.