Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces

The role of seasonality in shaping the interactions of honeybees with other taxa

The Eltonian niche of a species is defined as its set of interactions with other taxa. How this set varies with biotic, abiotic and human influences is a core question of modern ecology. In seasonal environments, the realized Eltonian niche is likely to vary due to periodic changes in the occurrence and abundance of interaction partners and changes in species behavior and preferences. Also, human management decisions may leave strong imprints on species interactions. To compare the impact of seasonality to that of management effects, honeybees provide an excellent model system. Based on DNA traces of interaction partners archived in honey, we can infer honeybee interactions with floral resources and microbes in the surrounding habitats, their hives, and themselves. Here, we resolved seasonal and management-based impacts on honeybee interactions by sampling beehives repeatedly during the honey-storing period of honeybees in Finland. We then use a genome-skimming approach to identify the taxonomic contents of the DNA in the samples. To compare the effects of the season to the effects of location, management, and the colony itself in shaping honeybee interactions, we used joint species distribution modeling. We found that honeybee interactions with other taxa varied greatly among taxonomic and functional groups. Against a backdrop of wide variation in the interactions documented in the DNA content of honey from bees from different hives, regions, and beekeepers, the imprint of the season remained relatively small. Overall, a honey-based approach offers unique insights into seasonal variation in the identity and abundance of interaction partners among honeybees. During the summer, the availability and use of different interaction partners changed substantially, but hive- and taxon-specific patterns were largely idiosyncratic as modified by hive management. Thus, the beekeeper and colony identity are as important determinants of the honeybee's realized Eltonian niche as is seasonality.

Honeybees' foraging choices for nectar and pollen revealed by DNA metabarcoding

Honeybees are the most widespread managed pollinators of our food crops, and a crucial part of their well-being is a suitable diet. Yet, we do not know how they choose flowers to collect nectar or pollen from. Here we studied forty-three honeybee colonies in six apiaries over a summer, identifying the floral origins of honey and hive-stored pollen samples by DNA-metabarcoding. We recorded the available flowering plants and analyzed the specialized metabolites in honey. Overall, we find that honeybees use mostly the same plants for both nectar and pollen, yet per colony less than half of the plant genera are used for both nectar and pollen at a time. Across samples, on average fewer plant genera were used for pollen, but the composition was more variable among samples, suggesting higher selectivity for pollen sources. Of the available flowering plants, honeybees used only a fraction for either nectar or pollen foraging. The time of summer guided the plant choices the most, and the location impacted both the plants selected and the specialized metabolite composition in honey. Thus, honeybees are selective for both nectar and pollen, implicating a need of a wide variety of floral resources to choose an optimal diet from.

DNA traces the origin of honey by identifying plants, bacteria and fungi

The regional origin of a food product commonly affects its value. To this, DNA-based identification of tissue remains could offer fine resolution. For honey, this would allow the usage of not only pollen but all plant tissue, and also that of microbes in the product, for discerning the origin. Here we examined how plant, bacterial and fungal taxa identified by DNA metabarcoding and metagenomics differentiate between honey samples from three neighbouring countries. To establish how the taxonomic contents of honey reflect the country of origin, we used joint species distribution modelling. At the lowest taxonomic level by metabarcoding, with operational taxonomic units, the country of origin explained the majority of variation in the data (70-79%), with plant and fungal gene regions providing the clearest distinction between countries. At the taxonomic level of genera, plants provided the most separation between countries with both metabarcoding and metagenomics. The DNA-based methods distinguish the countries more than the morphological pollen identification and the removal of pollen has only a minor effect on taxonomic recovery by DNA. As we find good resolution among honeys from regions with similar biota, DNA-based methods hold great promise for resolving honey origins among more different regions.

A multi-kingdom metabarcoding study on cattle grazing Alpine pastures discloses intra-seasonal shifts in plant selection and faecal microbiota

Diet selection by grazing livestock may affect animal performance as well as the biodiversity of grazed areas. Recent DNA barcoding techniques allow to assess dietary plant composition in faecal samples, which may be additionally integrated by the description of gut microbiota. In this high throughput metabarcoding study, we investigated the diversity of plant, fungal and bacterial taxa in faecal samples of lactating cows of two breeds grazing an Alpine semi-natural grassland during summer. The estimated plant composition of the diet comprised 67 genera and 39 species, which varied remarkably during summer, suggesting a decline of the diet forage value with the advancing of the vegetative season. The fungal community included Neocallimastigomycota gut symbionts, but also Ascomycota and Basidiomycota plant parasite and coprophilous taxa, likely ingested during grazing. The proportion of ingested fungi was remarkably higher than in other studies, and varied during summer, although less than that observed for plants. Some variation related to breed was also detected. The gut bacterial taxa remained stable through the summer but displayed a breed-specific composition. The study provided insights in the reciprocal organisms' interactions affecting, and being affected by, the foraging behaviour: plants showed a high temporal variation, fungi a smaller one, while bacteria had practically none; conversely, the same kingdoms showed the opposite gradient of variation as respect to the animal host breed, as bacteria revealed to be the group mostly characterized by host-specificity.

Estimation of the relative abundance of species in artificial mixtures of insects using low-coverage shotgun metagenomics

Amplicon metabarcoding is an established technique to analyse the taxonomic composition of communities of organisms using high-throughput DNA sequencing, but there are doubts about its ability to quantify the relative proportions of the species, as opposed to the species list. Here, we bypass the enrichment step and avoid the PCR-bias, by directly sequencing the extracted DNA using shotgun metagenomics. This approach is common practice in prokaryotes, but not in eukaryotes, because of the low number of sequenced genomes of eukaryotic species. We tested the metagenomics approach using insect species whose genome is already sequenced and assembled to an advanced degree. We shotgun-sequenced, at low-coverage, 18 species of insects in 22 single-species and 6 mixed-species libraries and mapped the reads against 110 reference genomes of insects. We used the single-species libraries to calibrate the process of assignation of reads to species and the libraries created from species mixtures to evaluate the ability of the method to quantify the relative species abundance. Our results showed that the shotgun metagenomic method is easily able to set apart closely-related insect species, like four species of Drosophila included in the artificial libraries. However, to avoid the counting of rare misclassified reads in samples, it was necessary to use a rather stringent detection limit of 0.001, so species with a lower relative abundance are ignored. We also identified that approximately half the raw reads were informative for taxonomic purposes. Finally, using the mixed-species libraries, we showed that it was feasible to quantify with confidence the relative abundance of individual species in the mixtures.