Environmental DNA (eDNA) techniques are increasingly employed in biodiversity monitoring of aquatic and terrestrial animals, plants, and fungi, holding great potential to revolutionize biodiversity assessments. However, sampling and basic laboratory protocols still require refinement to optimize eDNA metabarcoding performance. Homogenization as a pre-treatment for eDNA extraction is known to enhance the concentration and quality of extracted eDNA for some groups of organisms. We previously developed a simple and efficient method for capturing arboreal biodiversity using stemflow as a source of eDNA; however, its performance with or without homogenization had not yet been compared. In this study, we evaluated the performance of two different homogenization methods using eDNA metabarcoding and qPCR assays. Metabarcoding analyses revealed that the method without homogenization detected the fewest species, while nearly identical and higher numbers of species were detected in samples subjected to bead-beating and frozen bead-beating homogenization. Similarly, qPCR analyses revealed that the method without homogenization yielded the lowest DNA concentration, while nearly identical and higher DNA yields were observed for bead-beating and frozen bead-beating homogenization. These findings suggest that, considering cost and effort, the bead-beating method without freezing is the most advantageous.

Ants are often the most ubiquitous and ecologically influential components of terrestrial systems, exhibiting an exceptionally high level of endemic diversity. Simultaneously, exotic ants can be amongst the most environmentally and economically devastating biological invaders. Distinguishing between exotic and related natives is essential for early detection and to reduce the chance of establishment, but at the species-level there remains a great deal of uncertainty among several of the most diverse, widespread and ecologically dominant genera. This taxonomic impediment negatively impacts the use of molecular techniques relying on reference databases, due to the poor state of ant DNA sequences in publicly available repositories, with many species not represented at all and others incorrectly identified. As a result, biosecurity screening for targeted exotic ants and assigning ant species-level identifications for biodiversity remain two separate areas of focus in Australia. Here we propose a workflow for the identification of ants that enables simultaneous processing of large numbers of “bulk” ant samples each containing many individuals, increasing resolution for taxonomic assignment, and generating a curated database linked to voucher specimens. We use a non-destructive DNA extraction method and compare two high throughput sequencing (HTS) metabarcoding platforms – MiSeq (Illumina) and MinION (Oxford Nanopore Technologies) – processing up to 180 bulk mixed ant samples per run. This approach allowed for the acquisition of curated DNA sequences from voucher specimens morphologically examined by expert taxonomists. This work highlights the advantages and current limitations of DNA-based identifications, the needs for standardisation, as well as the importance of a taxonomy-based curation of DNA database for both biodiversity and biosecurity.

Cetaceans are key sentinel species of marine ecosystems and ocean health, being a strategic taxonomic group that evaluates the well-being of aquatic habitats and detects harmful environmental trends. Respiratory diseases are amongst the main causes of death in these animals, so identifying the microbiome community in their exhaled breath condensates (EBC), i.e. blow, has been proposed as a key biomarker for assessing respiratory health. Yet, to characterise microbiomes related to these animals’ respiratory tract and use them as a proxy for health status, it is necessary to develop baseline data on the microorganisms associated with cetaceans. Here, the short-finned pilot whale (SFPW, Globicephala macrorhynchus) was used as a case study to validate the most suitable primer set to explore the prokaryotic diversity of the cetaceans’ respiratory tract. DNA extracted from blow samples (n = 12) of animals off Madeira Island was sequenced to amplify both V3-V4 and V4-V5 hypervariable regions of the 16S rRNA gene, using the same sequencing platform (Illumina MiSeq). Independently of the primer set used, all blows shared Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria phyla in their composition. V3-V4 resulted in a higher diversity of taxa with relative abundance above 1%, whereas the V4-V5 primers captured a higher number of microbial Amplicon Sequence Variants, detecting the rare microbial biosphere with pathogen potential. Additionally, it captured the core microbiome more efficiently. Thus, this study provides a detailed characterisation of SFPW respiratory-associated microbial communities, strengthening the idea of sociality influencing microbiome composition in the respiratory tract. Moreover, it supports the use of blow as a relevant biomarker for the physiological state of the airways in free-ranging cetaceans.

The Store Mosse National Park in the south of Sweden was surveyed for nematode diversity and distribution using DNA metabarcoding. Fifty samples were collected from five vegetation types in the park across a range of habitats (e.g. soil, litter, lichens, sphagnum and roots). The other habitats, aside from soil and litter, were sampled in order to capture the diversity of nematodes that may be uniquely associated with them. Nematodes were characterised using the V7-V8 variable domain (~ 350 bp) of the 18S ribosomal RNA gene. We identified 46 families, 76 genera (21 new to Swedish fauna) and 60 species (31 new to Swedish fauna). Some nematodes showed strong associations with their habitats, especially at the species level. Although soil and litter supported the most diverse nematode communities, our results support a strong justification for sampling across different media types to quantify nematode diversity accurately. Soil and litter communities showed high levels of stability with balanced distribution of all the various trophic and coloniser-persister groups.

Introduced trout can induce trophic cascades, however, a lack of pre-introduction data limits knowledge on their impact in many lakes. Traditional paleolimnological approaches have been used to study historic species changes, but until recently these have been restricted to taxa with preservable body-parts. To explore the ecosystem effects of Salmo trutta (brown trout) introduction on an oligotrophic lake in Aotearoa-New Zealand, we used a multi-marker sedimentary environmental DNA (sedDNA) approach coupled with pigments to detect changes across multiple trophic levels. DNA was extracted from core depths capturing approximately 100 years before and after the expected arrival of S. trutta, and metabarcoding was undertaken with four primer sets targeting the 12S rRNA (fish), 18S rRNA (eukaryotes) and cytochrome c oxidase (COI; eukaryotes) genes. The earliest detection of S. trutta eDNA was 1906 (1892–1919 CE with 95% high probability density function) suggesting their introduction was shortly before this. Native fish diversity (12S and 18S rRNA) decreased after the detection of S. trutta, albeit the data was patchy. A shift in overall eukaryotic and algal communities (18S rRNA and COI) was observed around 1856 (1841–1871 CE) to 1891 (1877–1904 CE), which aligns with the expected S. trutta introduction. However, taxonomy could not be assigned to many of the 18S rRNA and COI sequences. Pigment concentrations did not change markedly after S. trutta introduction. SedDNA provides a new tool for understanding the impact of disturbances such as the introduction of non-native species; however, there are still several methodological challenges to overcome.

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.

Implementation of DNA metabarcoding for diatoms for environmental monitoring is now moving from a research to an operational phase, requiring rigorous guidelines and standards. In particular, the first steps of the diatom metabarcoding process, which consist of sampling and storage, have been addressed in various ways in scientific and pilot studies and now need to be rationalised. The objective of this study was to compare three currently applied preservation protocols through different storage durations (ranging from one day to one year) for phytobenthos and phytoplankton samples intended for diatom DNA metabarcoding analysis. The experimental design used samples from four freshwater and two marine sites of diverse ecological characteristics. The impact of the sample preservation and storage duration was assessed through diatom metabarcoding endpoints: DNA quality and quantity, diversity and richness, diatom assemblage composition and ecological index values (for freshwater samples). The yield and quality of extracted DNA only decreased for freshwater phytobenthos samples preserved with ethanol. Diatom diversity was not affected and their taxonomic composition predominantly reflected the site origin. Only rare taxa (< 100 reads) differed among preservation methods and storage durations. For biomonitoring purposes, freshwater ecological index values were not affected by the preservation method and storage duration tested (including ethanol preservation), all treatments returning the same ecological status for a site. This study contributes to consolidating diatom metabarcoding. Thus, accompanied by operational standards, the method will be ready to be confidently deployed and prescribed in future regulatory monitoring.

The karst aquifer of the Yucatán Peninsula (YP) in southeastern Mexico is a unique ecosystem in which water-filled sinkholes, locally known as cenotes, connect subterranean waters with the surface. This system is home to around 20 species of freshwater fishes, including several that are endemic and/or threatened. Studies on this unique ichthyofauna have been partially hampered by the technical difficulties associated with sampling these habitats, particularly submerged caves. In this proof-of-concept study, we use environmental DNA (eDNA) metabarcoding to survey the diversity of freshwater fishes associated with the YP karst aquifer by sampling six cenotes from across the Ring of Cenotes region in northwestern Yucatán, a 180-km-diameter semicircular band of abundant karst sinkholes. Through a combination of conventional sampling (direct observation, fishing) and eDNA metabarcoding, we detected eight species of freshwater fishes across the six sampled cenotes. Overall, our eDNA metabarcoding approach was effective at detecting the presence of fishes from cenote water samples, including one of the two endemic cave-dwelling fish species restricted to the subterranean section of the aquifer. Although our study was focused on detecting fishes via eDNA, we also recovered DNA from several other vertebrate groups, particularly bats. These results suggest that the eDNA metabarcoding approach represents a promising and largely noninvasive method to assay aquatic biodiversity in these vulnerable habitats, allowing more effective, frequent, and wide-ranging surveys. Our detection of DNA from aerial and terrestrial vertebrate fauna implies that eDNA from cenotes, besides being a means to survey aquatic fauna, may also offer an effective way to quickly survey non-aquatic biodiversity associated with these persistent water bodies.

Sagami Bay, Japan is influenced by both the warm Kuroshio Current and the cold Oyashio Current and rich nutrients are supplied from multiple river sources and the deep-sea, forming a dynamic ecosystem. The aim of the present study was to investigate eukaryotic and bacterial communities in the coastal waters of Sagami Bay, using 16S rRNA and 18S rRNA sequencing and to assess the seasonal and vertical dynamics in relation to physicochemical and biological conditions. Eukaryotic and bacterial communities showed synchronous seasonal and vertical changes along with environmental variability. Diversity of plankton community suspended in the surface was lower than those at the subsurface layers in both the eukaryotes and bacteria communities; however, community diversity showed different characteristics in the subsurface where the eukaryotic community at the deeper layer (100 m) was as low as the surface and highest in intermediate depth layers (10–50 m), while that of bacterial community was highest in the deeper layer (100 m). The annual variability of the coastal microbial communities was driven, not only by the seasonal changes of abiotic and biotic factors and short-term rapid changes by river water inflow and phytoplankton blooms, but also largely influenced by deep-seawater upwellings due to the unique seafloor topography.

The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.