The study of microbiomes across organisms and environments has become a prominent focus in molecular ecology. This perspective article explores methodological advancements, common challenges and future directions in the field. Key research areas include understanding the drivers of microbiome community assembly, linking microbiome composition to host genetics, exploring microbial functions, transience, and spatial partitioning, and disentangling non-bacterial components of the microbiome. Methodological advancements, such as quantifying absolute abundances, sequencing complete genomes, and utilizing novel statistical approaches, are also useful tools for understanding complex microbial diversity patterns. Our aims are to encourage robust practices in microbiome studies and inspire researchers to explore the next frontier of this rapidly changing field.

Availability of suitable nectar and pollen resources is a limiting factor for pollinator survival, with both overall resource quantity and quality, along with provision throughout the season, being critical. Yet, our understanding of how the selection of floral resources changes over time, and how this relates to floral availability within the landscape is limited. To fill this knowledge gap, we characterise floral use by honeybee (Apis mellifera) colonies, in a diverse horticultural and agricultural landscape, from April to September, over two years, using pollen DNA metabarcoding of honey samples. We compared the pollen found to the availability of host plants within the surrounding landscape using floral surveys. Honeybees used a total of 143 plant taxa, but only 10 of these were determined as major sources (>10% of total sequence reads in any month) and total plant use represented a small proportion of the available floral resources (23% of genera). Distinct patterns of diet specialisation were identified in June and August, where colonies diverged in their floral preferences before re-aligning in July and September. Following optimal foraging theory, these patterns represent periods of resource limitation. Honeybees showed a preference for flowering trees in the spring, followed by shrubs and herbs in summer and used native and near-native plants more than horticultural plants, as major food sources. DNA metabarcoding allows an increased ecological insight into floral resource use by honeybees and highlights the importance of providing continuous and sufficient floral resources throughout the year.

Metabarcoding of DNA extracted from environmental or bulk specimen samples is increasingly used to detect plant and animal taxa in basic and applied biodiversity research because of its targeted nature that allows sequencing of genetic markers from many samples in parallel. To achieve this, PCR amplification is carried out with primers designed to target a taxonomically informative marker within a taxonomic group, and sample-specific nucleotide identifiers are added to the amplicons prior to sequencing. This enables assignment of the sequences back to the samples they originated from. Nucleotide identifiers can be added during the metabarcoding PCR and/or during ‘library preparation’, i.e. when amplicons are prepared for sequencing. Different strategies to achieve this labelling exist. All have advantages, challenges and limitations, some of which can lead to misleading results, and in the worst case compromise the fidelity of the metabarcoding data. Given the range of questions addressed using metabarcoding, the importance of ensuring that data generation is robust and fit for purpose should be at the forefront of practitioners seeking to employ metabarcoding for biodiversity assessments. Here, we present an overview of the three main workflows for sample-specific labelling and library preparation in metabarcoding studies on Illumina sequencing platforms. Further, we distil the key considerations for researchers seeking to select an appropriate metabarcoding strategy for their specific study. Ultimately, by gaining insights into the consequences of different metabarcoding workflows, we hope to further consolidate the power of metabarcoding as a tool to assess biodiversity across a range of applications.

Benthic macrofauna is regularly used in monitoring programmes, however the vast majority of benthic eukaryotic biodiversity lies mostly in microscopic organisms, such as meiofauna (invertebrates < 1 mm) and protists, that rapidly responds to environmental change. These communities have traditionally been hard to sample and handle in the laboratory, but DNA sequencing has made such work less time consuming. Compared to DNA sequencing that captures both alive and dead organisms, environmental RNA (eRNA) can be used to better target alive communities. Here, we assessed the biodiversity of three known bioindicator microeukaryote groups (nematodes, foraminifera, and ciliates) in sediment samples collected at seven coastal sites along an organic carbon (OC) gradient. We aimed to investigate if eRNA shotgun sequencing can be used to simultaneously detect differences in 1) biodiversity of multiple microeukaryotic communities, and 2) functional feeding traits of nematodes. Results showed that biodiversity was lower for nematodes and foraminifera in high OC (6.2–6.9 %), when compared to low OC sediments (1.2–2.8 %). The beta diversity for all three groups were different along the OC gradient, as well as the classified feeding type of nematode genera (with more non-selective deposit feeders in high OC sediment). High relative abundant genera included nematode Sabatieria and foraminifera Elphidium in high OC, and Cryptocaryon-like ciliates in low OC sediments. Considering that future sequencing technologies are likely to decrease in cost, the use of eRNA shotgun sequencing to assess biodiversity of living benthic microeukaryotes could be a powerful tool in recurring monitoring programmes.