Evaluating multiplexed next-generation sequencing as a method in palynology for mixed pollen samples.

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.

Pyrrolizidine alkaloids in honey: comparison of analytical methods.

Pyrrolizidine alkaloids (PAs) are a structurally diverse group of toxicologically relevant secondary plant metabolites. Currently, two analytical methods are used to determine PA content in honey. To achieve reasonably high sensitivity and selectivity, mass spectrometry detection is demanded. One method is an HPLC-ESI-MS-MS approach, the other a sum parameter method utilising HRGC-EI-MS operated in the selected ion monitoring mode (SIM). To date, no fully validated or standardised method exists to measure the PA content in honey. To establish an LC-MS method, several hundred standard pollen analysis results of raw honey were analysed. Possible PA plants were identified and typical commercially available marker PA-N-oxides (PANOs). Three distinct honey sets were analysed with both methods. Set A consisted of pure Echium honey (61-80% Echium pollen). Echium is an attractive bee plant. It is quite common in all temperate zones worldwide and is one of the major reasons for PA contamination in honey. Although only echimidine/echimidine-N-oxide were available as reference for the LC-MS target approach, the results for both analytical techniques matched very well (n = 8; PA content ranging from 311 to 520 µg kg(-1)). The second batch (B) consisted of a set of randomly picked raw honeys, mostly originating from Eupatorium spp. (0-15%), another common PA plant, usually characterised by the occurrence of lycopsamine-type PA. Again, the results showed good consistency in terms of PA-positive samples and quantification results (n = 8; ranging from 0 to 625 µg kg(-1) retronecine equivalents). The last set (C) was obtained by consciously placing beehives in areas with a high abundance of Jacobaea vulgaris (ragwort) from the Veluwe region (the Netherlands). J. vulgaris increasingly invades countrysides in Central Europe, especially areas with reduced farming or sites with natural restorations. Honey from two seasons (2007 and 2008) was sampled. While only trace amounts of ragwort pollen were detected (0-6.3%), in some cases extremely high PA values were detected (n = 31; ranging from 0 to 13019 µg kg(-1), average = 1261 or 76 µg kg(-1) for GC-MS and LC-MS, respectively). Here the results showed significantly different quantification results. The GC-MS sum parameter showed in average higher values (on average differing by a factor 17). The main reason for the discrepancy is most likely the incomplete coverage of the J. vulgaris PA pattern. Major J. vulgaris PAs like jacobine-type PAs or erucifoline/acetylerucifoline were not available as reference compounds for the LC-MS target approach. Based on the direct comparison, both methods are considered from various perspectives and the respective individual strengths and weaknesses for each method are presented in detail.