The identification of pollen plays an important role in ecology, palaeo-climatology, honey quality control and other areas. Currently, expert knowledge and reference collections are essential to identify pollen origin through light microscopy. Pollen identification through molecular sequencing and DNA barcoding has been proposed as an alternative approach, but the assessment of mixed pollen samples originating from multiple plant species is still a tedious and error-prone task. Next-generation sequencing has been proposed to avoid this hindrance. In this study we assessed mixed pollen probes through next-generation sequencing of amplicons from the highly variable, species-specific internal transcribed spacer 2 region of nuclear ribosomal DNA. Further, we developed a bioinformatic workflow to analyse these high-throughput data with a newly created reference database. To evaluate the feasibility, we compared results from classical identification based on light microscopy from the same samples with our sequencing results. We assessed in total 16 mixed pollen samples, 14 originated from honeybee colonies and two from solitary bee nests. The sequencing technique resulted in higher taxon richness (deeper assignments and more identified taxa) compared to light microscopy. Abundance estimations from sequencing data were significantly correlated with counted abundances through light microscopy. Simulation analyses of taxon specificity and sensitivity indicate that 96% of taxa present in the database are correctly identifiable at the genus level and 70% at the species level. Next-generation sequencing thus presents a useful and efficient workflow to identify pollen at the genus and species level without requiring specialised palynological expert knowledge.

BackgroundMeta-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.ResultsWe 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).ConclusionsThis 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12898-015-0051-y) contains supplementary material, which is available to authorized users.

Microbial activity is known to have profound impact on bee ecology and physiology, both by beneficial and pathogenic effects. Most information about such associations is available for colony-building organisms, and especially the honey bee. There, active manipulations through worker bees result in a restricted diversity of microbes present within the colony environment. Microbial diversity in solitary bee nests remains unstudied, although their larvae face a very different situation compared with social bees by growing up in isolated compartments. Here, we assessed the microbiota present in nests and pre-adults of Osmia bicornis, the red mason bee, by culture-independent pyrosequencing. We found high bacterial diversity not comparable with honey bee colonies. We identified a variety of bacteria potentially with positive or negative interactions for bee larvae. However, most of the other diverse bacteria present in the nests seem to originate from environmental sources through incorporated nest building material and stored pollen. This diversity of microorganisms may cause severe larval mortality and require specific physiological or symbiotic adaptations against microbial threats. They may however also profit from such a diverse environment through gain of mutualistic partners. We conclude that further studies of microbiota interaction in solitary bees will improve the understanding of fitness components and populations dynamics.

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Solitary bees build their nests by modifying the interior of natural cavities, and they provision them with food by importing collected pollen. As a result, the microbiota of the solitary bee nests may be highly dependent on introduced materials. In order to investigate how the collected pollen is associated with the nest microbiota, we used metabarcoding of the ITS2 rDNA and the 16S rDNA to simultaneously characterize the pollen composition and the bacterial communities of 100 solitary bee nest chambers belonging to seven megachilid species. We found a weak correlation between bacterial and pollen alpha diversity and significant associations between the composition of pollen and that of the nest microbiota, contributing to the understanding of the link between foraging and bacteria acquisition for solitary bees. Since solitary bees cannot establish bacterial transmission routes through eusociality, this link could be essential for obtaining bacterial symbionts for this group of valuable pollinators. Open Research Badges This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at https://www.ebi.ac.uk/ena/data/view/PRJEB27223, https://www.ebi.ac.uk/ena/data/view/PRJEB31610, and https://doi.org/10.5061/dryad.qk36k8q