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. 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). 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.

“Bee pollen” is pollen collected from flowers by honey bees. It is used by the bees to nourish themselves, mainly by providing royal jelly and brood food, but it is also used for human nutrition. For the latter purpose, it is collected at the hive entrance as pellets that the bees bring to the hive. Bee pollen has diverse bioactivities, and thus has been used as a health food, and even as medication in some countries. In this paper, we provide standard methods for carrying out research on bee pollen. First, we introduce a method for the production and storage of bee pollen which assures quality of the product. Routine methods are then provided for the identification of the pollen’s floral sources, and determination of the more important quality criteria such as water content and content of proteins, carbohydrates, fatty acids, vitamins, alkaloids, phenolic and polyphenolic compounds. Finally, methods are described for the determination of some important bioactivities of bee pollen such as its antioxidant, anti-inflammatory, antimicrobial and antimutagenic properties. Métodos estándar Para la investigación del polen El "polen de abeja" es el polen recogido de las flores por las abejas melíferas. El polen de abeja es utilizado para nutrir a las propias abejas, principalmente para proporcionar jalea real y alimento para las crías, pero también se utiliza para la nutrición humana. Para este último fin, se recoge en la entrada de la colmena en forma de gránulos que las abejas llevan a la colmena. El polen de abeja tiene diversas bioactividades, por lo que se hautilizado como alimento para la salud, e incluso como medicamento en algunos países. En este artículo, proporcionamos métodos estándar para llevar a cabo investigaciones sobre el polen de abeja. En primer lugar, presentamos un método de producción y almacenamiento de polen de abeja que garantiza la calidad del producto. A continuación, se ofrecen métodos de rutina para la identificación de las fuentes florales del polen y la determinación de los criterios de calidad más importantes, como el contenido de agua y de proteínas, carbohidratos, ácidos grasos, vitaminas, alcaloides y compuestos fenólicos y polifenólicos. Por último, se describen métodos para la determinación de algunas bioactividades importantes del polen de abeja, como sus propiedades antioxidantes, antiinflamatorias, antimicrobianas y antimutagénicas.

Tropical peat swamp forests sequester globally significant stores of carbon in deep layers of waterlogged, anoxic, acidic and nutrient-depleted peat. The roles of microbes in supporting these forests through the formation of peat, carbon sequestration and nutrient cycling are virtually unknown. This study investigated physicochemical peat properties and microbial diversity between three dominant tree species: Shorea uliginosa (Dipterocarpaceae), Koompassia malaccensis (legumes associated with nitrogen-fixing bacteria), Eleiodoxa conferta (palm) and depths (surface, 45 and 90 cm) using microbial 16S rRNA gene amplicon sequencing. Water pH, oxygen, nitrogen, phosphorus, total phenolic contents and C/N ratio differed significantly between depths, but not tree species. Depth also strongly influenced microbial diversity and composition, while both depth and tree species exhibited significant impact on the archaeal communities. Microbial diversity was highest at the surface, where fresh leaf litter accumulates, and nutrient supply is guaranteed. Nitrogen was the core parameter correlating to microbial communities, but the interactive effects from various environmental variables displayed significant correlation to relative abundance of major microbial groups. Proteobacteria was the dominant phylum and the most abundant genus, Rhodoplanes, might be involved in nitrogen fixation. The most abundant methanogens and methanotrophs affiliated, respectively, to families Methanomassiliicoccaceae and Methylocystaceae. Our results demonstrated diverse microbial communities and provide valuable insights on microbial ecology in these extreme ecosystems.

Biodiversity is declining at alarming rates worldwide and large-scale monitoring is urgently needed to understand changes and their drivers. While classical taxonomic identification of species is time and labour intensive, the combination with DNA-based methods could upscale monitoring activities to achieve larger spatial coverage and increased sampling effort. However, challenges remain for DNA-based methods when the number of individuals per species and/or biomass estimates are required. Several methodological advancements exist to improve the potential of DNA metabarcoding for abundance analysis, which however need further evaluation. Here, we discuss laboratory, as well as some bioinformatic adjustments to DNA metabarcoding workflows regarding their potential to achieve species abundance estimation from arthropod community samples. Our review includes pre-laboratory processing methods such as specimen photography, laboratory methods such as the use of spike-in DNA as an internal standard and bioinformatic advancements like correction factors. We conclude that specimen photography coupled with DNA metabarcoding currently promises the greatest potential to achieve estimates of the number of individuals per species and biomass estimates, but that approaches such as spike-ins and correction factors are promising methods to pursue further.

In previous studies, the gram-positive firmicute genus Paenibacillus was found with significant abundances in nests of wild solitary bees. Paenibacillus larvae is well-known for beekeepers as a severe pathogen causing the fatal honey bee disease American foulbrood, and other members of the genus are either secondary invaders of European foulbrood or considered a threat to honey bees. We thus investigated whether Paenibacillus is a common bacterium associated with various wild bees and hence poses a latent threat to honey bees visiting the same flowers. We collected 202 samples from 82 individuals or nests of 13 bee species at the same location and screened each for Paenibacillus using high-throughput sequencing-based 16S metabarcoding. We then isolated the identified strain Paenibacillus MBD-MB06 from a solitary bee nest and sequenced its genome. We did find conserved toxin genes and such encoding for chitin-binding proteins, yet none specifically related to foulbrood virulence or chitinases. Phylogenomic analysis revealed a closer relationship to strains of root-associated Paenibacillus rather than strains causing foulbrood or other accompanying diseases. We found anti-microbial evidence within the genome, confirmed by experimental bioassays with strong growth inhibition of selected fungi as well as gram-positive and gram-negative bacteria. The isolated wild bee associate Paenibacillus MBD-MB06 is a common, but irregularly occurring part of wild bee microbiomes, present on adult body surfaces and guts and within nests especially in megachilids. It was phylogenetically and functionally distinct from harmful members causing honey bee colony diseases, although it shared few conserved proteins putatively toxic to insects that might indicate ancestral predisposition for the evolution of insect pathogens within the group. By contrast, our strain showed anti-microbial capabilities and the genome further indicates abilities for chitin-binding and biofilm-forming, suggesting it is likely a useful associate to avoid fungal penetration of the bee cuticula and a beneficial inhabitant of nests to repress fungal threats in humid and nutrient-rich environments of wild bee nests.