Watered-down biodiversity? A comparison of metabarcoding results from DNA extracted from matched water and bulk tissue biomonitoring samples

Temporal and Depth-Driven Variability of Pelagic Bacterial Communities in Lake Erie: Biofilm and Plankton Dynamics

Despite constituting an important component of freshwater ecosystems, biofilm assemblages have remained relatively understudied compared to plankton, especially in freshwater systems such as the western basin of Lake Erie (WBLE). This study therefore aimed to elucidate temporal and vertical shifts of microbial communities of planktonic and biofilm growth on artificial substrates in the WBLE water column at discrete depths, investigating the overlap of shared taxa between community types. Sequencing of the 16S rRNA gene revealed concurrent biofilm-plankton samples shared a low percentage (~10%) of amplicon sequence variants (ASVs) indicating distinct communities between free-living and substrate-attached bacteria. Plankton communities did not significantly differ between surface and bottom depths (1 and 8 m), whereas biofilm communities differed between upper (1-4 m) and lower (5-8 m) water columns. Temporal variation in community composition was observed in biofilm, with early periods (June-July) showing significant dissimilarity followed by compositional convergence in late summer onwards (August-October). With the expansion of artificial infrastructure in aquatic systems, there is novel substrate material to observe spatiotemporal patterns of microbial colonisation throughout the pelagic zone. These results demonstrate the complexity of bacterial biofilm communities from plankton in freshwater, providing insight into microbial assembly through temporal succession and across depth.

North Atlantic deep-sea benthic biodiversity unveiled through sponge natural sampler DNA

The deep-sea remains the biggest challenge to biodiversity exploration, and anthropogenic disturbances extend well into this realm, calling for urgent management strategies. One of the most diverse, productive, and vulnerable ecosystems in the deep sea are sponge grounds. Currently, environmental DNA (eDNA) metabarcoding is revolutionising the field of biodiversity monitoring, yet complex deep-sea benthic ecosystems remain challenging to assess even with these novel technologies. Here, we evaluate the effectiveness of whole-community metabarcoding to characterise metazoan diversity in sponge grounds across the North Atlantic by leveraging the natural eDNA sampling properties of deep-sea sponges themselves. We sampled 97 sponge tissues from four species across four North-Atlantic biogeographic regions in the deep sea and screened them using the universal COI barcode region. We recovered unprecedented levels of taxonomic diversity per unit effort, especially across the phyla Chordata, Cnidaria, Echinodermata and Porifera, with at least 406 metazoan species found in our study area. These assemblages identify strong spatial patterns in relation to both latitude and depth, and detect emblematic species currently employed as indicators for these vulnerable habitats. The remarkable performance of this approach in different species of sponges, in different biogeographic regions and across the whole animal kingdom, illustrates the vast potential of natural samplers as high-resolution biomonitoring solutions for highly diverse and vulnerable deep-sea ecosystems.

Taxonomic accuracy and complementarity between bulk and eDNA metabarcoding provides an alternative to morphology for biological assessment of freshwater macroinvertebrates

Determining biological status of freshwater ecosystems is critical for ensuring ecosystem health and maintaining associated services to such ecosystems. Freshwater macroinvertebrates respond predictably to environmental disturbances and are widely used in biomonitoring programs. However, many freshwater species are difficult to capture and sort from debris or substrate and morphological identification is challenging, especially larval stages, damaged specimens, or hyperdiverse groups such as Diptera. The advent of high throughput sequencing technologies has enhanced DNA barcoding tools to automatise species identification for whole communities, as metabarcoding is increasingly used to monitor biodiversity. However, recent comparisons have revealed little congruence between morphological and molecular-based identifications. Using broad range universal primers for DNA barcode marker cox1, we compare community composition captured between morphological and molecular-based approaches from different sources - tissue-based (bulk benthic and bulk drift samples) and environmental DNA (eDNA, filtered water) metabarcoding - for samples collected along a gradient of anthropogenic disturbances. For comparability, metabarcoding taxonomic assignments were filtered by taxa included in the standardised national biological metric IBMWP. At the family level, bulk benthic metabarcoding showed the highest congruence with morphology, and the most abundant taxa were captured by all techniques. Richness captured by morphology and bulk benthic metabarcoding decreased along the gradient, whereas richness recorded by eDNA remained constant and increased downstream when sequencing bulk drift. Estimates of biological metrics were higher using molecular than morphological identification. At species level, diversity captured by bulk benthic samples were higher than the other techniques. Importantly, bulk benthic and eDNA metabarcoding captured different and complementary portions of the community - benthic versus water column, respectively - and their combined use is recommended. While bulk benthic metabarcoding can likely replace morphology using similar benthic biological indices, water eDNA will require new metrics because this technique sequences a different portion of the community.

From DNA to diagnostics: A case study using macroinvertebrate metabarcoding to assess the effectiveness of restoration measures in a Dutch stream

Stream ecosystems are under pressure due to multiple stressors. Restoration measures can halt further degradation and improve their ecological status. However, assessment of the effectiveness of the implemented measures is often insufficient because of logistic and financial constraints. DNA-metabarcoding has been proposed to scale up sample processing, although its application as a diagnostic tool has received less attention. The aim of our study was to evaluate if DNA-metabarcoding of stream macroinvertebrates can be used to compute a stressor-specific index to assess the effectiveness of a stream restoration project. For this purpose, we sampled the upstream, restored, and downstream section of a recently restored lowland stream in the Netherlands. At each site, we applied three different methods of macroinvertebrate identification: morphological identification of bulk samples (morphology), DNA-metabarcoding of the same bulk samples (DNA) and metabarcoding of eDNA extracted from the water (eDNA). First, we compared the community composition identified by each method. The communities identified by morphology and DNA were highly similar, whereas the communities generated by the eDNA differed. Second, we analysed whether the identification methods could be used to assess the effectiveness of the restoration project, focussing on a stressor-specific index for flow as the restoration measures aimed at improving flow conditions. Both the morphology and bulk DNA samples indicated improved flow conditions in the restored section of the stream (i.e., less stress from the reduction or absence of flow than in the unrestored sections). Contrary, the eDNA-water samples did not differentiate the amount of stress throughout the catchment, although applying recent developments in eDNA sampling could lead to more robust results. In conclusion, this study forms proof of concept that DNA from bulk samples can be utilized to assess the effectiveness of restoration measures, showing the added value of this approach for water managers.

A new sampling device for metabarcoding surveillance of port communities and detection of non-indigenous species

Metabarcoding techniques are revolutionizing studies of marine biodiversity. They can be used for monitoring non-indigenous species (NIS) in ports and harbors. However, they are often biased by inconsistent sampling methods and incomplete reference databases. Logistic constraints in ports prompt the development of simple, easy-to-deploy samplers. We tested a new device called polyamide mesh for ports organismal monitoring (POMPOM) with a high surface-to-volume ratio. POMPOMS were deployed inside a fishing and recreational port in the Mediterranean alongside conventional settlement plates. We also compiled a curated database with cytochrome oxidase (COI) sequences of Mediterranean NIS. COI metabarcoding of the communities settled in the POMPOMs captured a similar biodiversity than settlement plates, with shared molecular operational units (MOTUs) representing ca. 99% of reads. 38 NIS were detected in the port accounting for ca. 26% of reads. POMPOMs were easy to deploy and handle and provide an efficient method for NIS surveillance.

Creating, curating and evaluating a mitogenomic reference database to improve regional species identification using environmental DNA

Species detection using eDNA is revolutionizing global capacity to monitor biodiversity. However, the lack of regional, vouchered, genomic sequence information-especially sequence information that includes intraspecific variation-creates a bottleneck for management agencies wanting to harness the complete power of eDNA to monitor taxa and implement eDNA analyses. eDNA studies depend upon regional databases of mitogenomic sequence information to evaluate the effectiveness of such data to detect and identify taxa. We created the Oregon Biodiversity Genome Project to create a database of complete, nearly error-free mitogenomic sequences for all of Oregon's fishes. We have successfully assembled the complete mitogenomes of 313 specimens of freshwater, anadromous and estuarine fishes representing 24 families, 55 genera and 129 species and lineages. Comparative analyses of these sequences illustrate that many regions of the mitogenome are taxonomically informative, that the short (~150 bp) mitochondrial 'barcode' regions typically used for eDNA assays do not consistently diagnose for species and that complete single or multiple genes of the mitogenome are preferable for identifying Oregon's fishes. This project provides a blueprint for other researchers to follow as they build regional databases, illustrates the taxonomic value and limits of complete mitogenomic sequences and offers clues as to how current eDNA assays and environmental genomics methods of the future can best leverage this information.

Assessing arthropod diversity metrics derived from stream environmental DNA: spatiotemporal variation and paired comparisons with manual sampling

Background

Benthic invertebrate (BI) surveys have been widely used to characterize freshwater environmental quality but can be challenging to implement at desired spatial scales and frequency. Environmental DNA (eDNA) allows an alternative BI survey approach, one that can potentially be implemented more rapidly and cheaply than traditional methods.

Methods

We evaluated eDNA analogs of BI metrics in the Potomac River watershed of the eastern United States. We first compared arthropod diversity detected with primers targeting mitochondrial 16S (mt16S) and cytochrome c oxidase 1 (cox1 or COI) loci to that detected by manual surveys conducted in parallel. We then evaluated spatial and temporal variation in arthropod diversity metrics with repeated sampling in three focal parks. We also investigated technical factors such as filter type used to capture eDNA and PCR inhibition treatment.

Results

Our results indicate that genus-level assessment of eDNA compositions is achievable at both loci with modest technical noise, although database gaps remain substantial at mt16S for regional taxa. While the specific taxa identified by eDNA did not strongly overlap with paired manual surveys, some metrics derived from eDNA compositions were rank-correlated with previously derived biological indices of environmental quality. Repeated sampling revealed statistical differences between high- and low-quality sites based on taxonomic diversity, functional diversity, and tolerance scores weighted by taxon proportions in transformed counts. We conclude that eDNA compositions are efficient and informative of stream condition. Further development and validation of scoring schemes analogous to commonly used biological indices should allow increased application of the approach to management needs.

Multi-marker DNA metabarcoding detects suites of environmental gradients from an urban harbour

There is increasing need for biodiversity monitoring, especially in places where potential anthropogenic disturbance may significantly impact ecosystem health. We employed a combination of traditional morphological and bulk macroinvertebrate metabarcoding analyses to benthic samples collected from Toronto Harbour (Ontario, Canada) to compare taxonomic and functional diversity of macroinvertebrates and their responses to environmental gradients. At the species rank, sites assessed using COI metabarcoding showed more variation than sites assessed using morphological methods. Depending on the assessment method, we detected gradients in magnesium (morphological taxa), ammonia (morphological taxa, COI sequence variants), pH (18S sequence variants) as well as gradients in contaminants such as metals (COI & 18S sequence variants) and organochlorines (COI sequence variants). Observed responses to contaminants such as aromatic hydrocarbons and metals align with known patchy distributions in harbour sediments. We determined that the morphological approach may limit the detection of macroinvertebrate responses to lake environmental conditions due to the effort needed to obtain fine level taxonomic assignments necessary to investigate responses. DNA metabarcoding, however, need not be limited to macroinvertebrates, can be automated, and taxonomic assignments are associated with a certain level of accuracy from sequence variants to named taxonomic groups. The capacity to detect change using a scalable approach such as metabarcoding is critical for addressing challenges associated with biodiversity monitoring and ecological investigations.

Comparing eDNA metabarcoding primers for assessing fish communities in a biodiverse estuary

Metabarcoding of environmental DNA is increasingly used for biodiversity assessments in aquatic communities. The efficiency and outcome of these efforts are dependent upon either de novo primer design or selecting an appropriate primer set from the dozens that have already been published. Unfortunately, there is a lack of studies that have directly compared the efficacy of different metabarcoding primers in marine and estuarine systems. Here we evaluate five commonly used primer sets designed to amplify rRNA barcoding genes in fishes and compare their performance using water samples collected from estuarine sites in the highly biodiverse Indian River Lagoon in Florida. Three of the five primer sets amplify a portion of the mitochondrial 12S gene (MiFish_12S, 171bp; Riaz_12S, 106 bp; Valentini_12S, 63 bp), one amplifies 219 bp of the mitochondrial 16S gene (Berry_16S), and the other amplifies 271 bp of the nuclear 18S gene (MacDonald_18S). The vast majority of the metabarcoding reads (> 99%) generated using the 18S primer set assigned to non-target (non-fish) taxa and therefore this primer set was omitted from most analyses. Using a conservative 99% similarity threshold for species level assignments, we detected a comparable number of species (55 and 49, respectively) and similarly high Shannon’s diversity values for the Riaz_12S and Berry_16S primer sets. Meanwhile, just 34 and 32 species were detected using the MiFish_12S and Valentini_12S primer sets, respectively. We were able to amplify both bony and cartilaginous fishes using the four primer sets with the vast majority of reads (>99%) assigned to the former. We detected the greatest number of elasmobranchs (six species) with the Riaz_12S primer set suggesting that it may be a suitable candidate set for the detection of sharks and rays. Of the total 76 fish species that were identified across all datasets, the combined three 12S primer sets detected 85.5% (65 species) while the combination of the Riaz_12S and Berry_16S primers detected 93.4% (71 species). These results highlight the importance of employing multiple primer sets as well as using primers that target different genomic regions. Moreover, our results suggest that the widely adopted MiFish_12S primers may not be the best choice, rather we found that the Riaz_12S primer set was the most effective for eDNA-based fish surveys in our system.

The bacterial hitchhiker’s guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind

Environmental DNA (eDNA) metabarcoding from water samples has, in recent years, shown great promise for biodiversity monitoring. However, universal primers targeting the cytochrome oxidase I (COI) marker gene popular in metazoan studies have displayed high levels of nontarget amplification. To date, enrichment methods bypassing amplification have not been able to match the detection levels of conventional metabarcoding. This study evaluated the use of universal metabarcoding primers as capture probes to either isolate target DNA or to remove nontarget DNA, prior to amplification, by using biotinylated versions of universal metazoan and bacterial barcoding primers, namely metazoan COI (mlCOIintF) and bacterial 16S (515F). Additionally, each step of the protocol was assessed by amplifying for both metazoan COI (mlCOIintF/jgHCO2198) and bacterial 16S (515F/806R) to investigate the effect on the metazoan and bacterial communities. Bacterial read abundance increased significantly in response to the captures (COI library), while the quality of the captured DNA was also improved. The metazoan-oriented probe captured bacterial DNA in a range that was also amplifiable with the 16S primers, demonstrating the ability of capture probes to isolate fragments of DNA spanning over a longer distance than perhaps expected, from eDNA. Although the use of the tested COI probe cannot be recommended for metazoan enrichment, based on the experimental results, the concept of capturing these longer fragments could be applied to metazoan metabarcoding. By using a truly conserved site without a high-level taxonomic resolution as a target for capture, it may be possible to isolate DNA fragments large enough to span over a nearby barcoding region (e.g., COI), which can then be processed through a conventional metabarcoding-by-amplification protocol.

LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

Background

Identification of biomarkers, which are measurable characteristics of biological datasets, can be challenging. Although amplicon sequence variants (ASVs) can be considered potential biomarkers, identifying important ASVs in high-throughput sequencing datasets is challenging. Noise, algorithmic failures to account for specific distributional properties, and feature interactions can complicate the discovery of ASV biomarkers. In addition, these issues can impact the replicability of various models and elevate false-discovery rates. Contemporary machine learning approaches can be leveraged to address these issues. Ensembles of decision trees are particularly effective at classifying the types of data commonly generated in high-throughput sequencing (HTS) studies due to their robustness when the number of features in the training data is orders of magnitude larger than the number of samples. In addition, when combined with appropriate model introspection algorithms, machine learning algorithms can also be used to discover and select potential biomarkers. However, the construction of these models could introduce various biases which potentially obfuscate feature discovery.

Results

We developed a decision tree ensemble, LANDMark, which uses oblique and non-linear cuts at each node. In synthetic and toy tests LANDMark consistently ranked as the best classifier and often outperformed the Random Forest classifier. When trained on the full metabarcoding dataset obtained from Canada’s Wood Buffalo National Park, LANDMark was able to create highly predictive models and achieved an overall balanced accuracy score of 0.96 ± 0.06. The use of recursive feature elimination did not impact LANDMark’s generalization performance and, when trained on data from the BE amplicon, it was able to outperform the Linear Support Vector Machine, Logistic Regression models, and Stochastic Gradient Descent models (p ≤ 0.05). Finally, LANDMark distinguishes itself due to its ability to learn smoother non-linear decision boundaries.

Conclusions

Our work introduces LANDMark, a meta-classifier which blends the characteristics of several machine learning models into a decision tree and ensemble learning framework. To our knowledge, this is the first study to apply this type of ensemble approach to amplicon sequencing data and we have shown that analyzing these datasets using LANDMark can produce highly predictive and consistent models.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04631-z.

Environmental DNA gives comparable results to morphology-based indices of macroinvertebrates in a large-scale ecological assessment

Anthropogenic activities are changing the state of ecosystems worldwide, affecting community composition and often resulting in loss of biodiversity. Rivers are among the most impacted ecosystems. Recording their current state with regular biomonitoring is important to assess the future trajectory of biodiversity. Traditional monitoring methods for ecological assessments are costly and time-intensive. Here, we compared monitoring of macroinvertebrates based on environmental DNA (eDNA) sampling with monitoring based on traditional kick-net sampling to assess biodiversity patterns at 92 river sites covering all major Swiss river catchments. From the kick-net community data, a biotic index (IBCH) based on 145 indicator taxa had been established. The index was matched by the taxonomically annotated eDNA data by using a machine learning approach. Our comparison of diversity patterns only uses the zero-radius Operational Taxonomic Units assigned to the indicator taxa. Overall, we found a strong congruence between both methods for the assessment of the total indicator community composition (gamma diversity). However, when assessing biodiversity at the site level (alpha diversity), the methods were less consistent and gave complementary data on composition. Specifically, environmental DNA retrieved significantly fewer indicator taxa per site than the kick-net approach. Importantly, however, the subsequent ecological classification of rivers based on the detected indicators resulted in similar biotic index scores for the kick-net and the eDNA data that was classified using a random forest approach. The majority of the predictions (72%) from the random forest classification resulted in the same river status categories as the kick-net approach. Thus, environmental DNA validly detected indicator communities and, combined with machine learning, provided reliable classifications of the ecological state of rivers. Overall, while environmental DNA gives complementary data on the macroinvertebrate community composition compared to the kick-net approach, the subsequently calculated indices for the ecological classification of river sites are nevertheless directly comparable and consistent.

A bright idea-metabarcoding arthropods from light fixtures

Arthropod communities in buildings have not been extensively studied, although humans have always shared their homes with them. In this study we explored if arthropod DNA can be retrieved and metabarcoded from indoor environments through the collection of dead specimens in light fixtures to better understand what shapes arthropod diversity in our homes. Insects were collected from 45 light fixtures at the Centre for Biodiversity Genomics (CBG, Guelph, Canada), and by community scientists at 12 different residential homes in Southern Ontario. The CBG ground floor of the CBG showed the greatest arthropod diversity, especially in light fixtures that were continuously illuminated. The community scientist samples varied strongly by light fixture type, lightbulb used, time passed since lamp was last cleaned, and specimen size. In all cases, the majority of OTUs was not shared between samples even within the same building. This study demonstrates that light fixtures might be a useful resource to determine arthropod diversity in our homes, but individual samples are likely not representative of the full diversity.

Wet grinding of invertebrate bulk samples – a scalable and cost-efficient protocol for metabarcoding and metagenomics

Most metabarcoding protocols for invertebrate bulk samples start with sample homogenisation, followed by DNA extraction, amplification of a specific marker region, and sequencing. Many of the above-mentioned laboratory steps have been verified thoroughly and best practice strategies exist, yet, no clear recommendation for the basis of almost all metabarcoding studies exists: the homogenisation of samples itself. Two different categories of devices are typically used for homogenisation: bead mills or blenders. Both have upsides and downsides. Bead mills rely on single-use plastics and therefore produce a lot of waste and are expensive. In addition to that, processing times can go up to 30 minutes making them unsuitable for large-scale studies. Blenders can handle larger sample volumes in a shorter time, and be cleaned – yet suffer from an increased risk of cross-contamination. We aimed to develop a fast, robust, cheap, and reliable sample homogenisation protocol that overcomes limitations of both approaches, i.e. does not produce difficult to discard waste and avoid single-use plastics while reducing overall costs. We tested the performance of the new protocol using six size-sorted Malaise trap samples and six unsorted stream macroinvertebrate kick-net samples. We used 14 replicates per sample and included many negative controls at different steps of the protocol to quantify the impacts of i) insufficient homogenisation and ii) cross-contamination. Our results show that 3-min homogenisation is sufficient to recover about 80% of OTUs per sample in each replicate and that a non-hazardous DIY cleaning solution provides an effective and efficient way of cleaning. The improvements of the protocol in terms of speed, ease of handling, an overall reduction of costs as well as the documented reliability and robustness make it an important candidate for sample homogenisation after sampling in particular for large-scale and regulatory metabarcoding but also metagenomics biodiversity assessments and monitoring.

Evaluating sediment and water sampling methods for the estimation of deep-sea biodiversity using environmental DNA

Despite representing one of the largest biomes on earth, biodiversity of the deep seafloor is still poorly known. Environmental DNA metabarcoding offers prospects for fast inventories and surveys, yet requires standardized sampling approaches and careful choice of environmental substrate. Here, we aimed to optimize the genetic assessment of prokaryote (16S), protistan (18S V4), and metazoan (18S V1-V2, COI) communities, by evaluating sampling strategies for sediment and aboveground water, deployed simultaneously at one deep-sea site. For sediment, while size-class sorting through sieving had no significant effect on total detected alpha diversity and resolved similar taxonomic compositions at the phylum level for all markers studied, it effectively increased the detection of meiofauna phyla. For water, large volumes obtained from an in situ pump (~ 6000 L) detected significantly more metazoan diversity than 7.5 L collected in sampling boxes. However, the pump being limited by larger mesh sizes (> 20 µm), only captured a fraction of microbial diversity, while sampling boxes allowed access to the pico- and nanoplankton. More importantly, communities characterized by aboveground water samples significantly differed from those characterized by sediment, whatever volume used, and both sample types only shared between 3 and 8% of molecular units. Together, these results underline that sediment sieving may be recommended when targeting metazoans, and aboveground water does not represent an alternative to sediment sampling for inventories of benthic diversity.

Integration of DNA-Based Approaches in Aquatic Ecological Assessment Using Benthic Macroinvertebrates

Benthic macroinvertebrates are among the most used biological quality elements for assessing the condition of all types of aquatic ecosystems worldwide (i.e., fresh water, transitional, and marine). Current morphology-based assessments have several limitations that may be circumvented by using DNA-based approaches. Here, we present a comprehensive review of 90 publications on the use of DNA metabarcoding of benthic macroinvertebrates in aquatic ecosystems bioassessments. Metabarcoding of bulk macrozoobenthos has been preferentially used in fresh waters, whereas in marine waters, environmental DNA (eDNA) from sediment and bulk communities from deployed artificial structures has been favored. DNA extraction has been done predominantly through commercial kits, and cytochrome c oxidase subunit I (COI) has been, by far, the most used marker, occasionally combined with others, namely, the 18S rRNA gene. Current limitations include the lack of standardized protocols and broad-coverage primers, the incompleteness of reference libraries, and the inability to reliably extrapolate abundance data. In addition, morphology versus DNA benchmarking of ecological status and biotic indexes are required to allow general worldwide implementation and higher end-user confidence. The increased sensitivity, high throughput, and faster execution of DNA metabarcoding can provide much higher spatial and temporal data resolution on aquatic ecological status, thereby being more responsive to immediate management needs.

Ethanol eDNA Reveals Unique Community Composition of Aquatic Macroinvertebrates Compared to Bulk Tissue Metabarcoding in a Biomonitoring Sampling Scheme

Freshwater ecosystems provide essential ecosystem services and support biodiversity; however, their water quality and biological communities are influenced by adjacent agricultural land use. Aquatic macroinvertebrates are commonly used as bioindicators of stream conditions in freshwater biomonitoring programs. Sorting benthic samples for molecular identification is a time-consuming process, and this study investigates the potential of ethanol-collected environmental DNA (eDNA) for metabarcoding macroinvertebrates, especially for common bioindicator groups. The objective of this study was to compare macroinvertebrate composition between paired bulk tissue and ethanol eDNA samples, as eDNA could provide a less time-consuming and non-destructive method of sampling macroinvertebrates. We collected benthic samples from streams in Ontario, Canada, and found that community composition varied greatly between sampling methods and that few taxa were shared between paired tissue and ethanol samples, suggesting that ethanol eDNA is not an acceptable substitute. It is unclear why we did not detect all the organisms that were preserved in the ethanol, or the origin of the DNA we did detect. Furthermore, we also detected no difference in community composition for bioindicator taxa due to surrounding land use or water chemistry, suggesting sites were similar in ecological condition.

Metabarcoding From Microbes to Mammals: Comprehensive Bioassessment on a Global Scale

Global biodiversity loss is unprecedented, and threats to existing biodiversity are growing. Given pervasive global change, a major challenge facing resource managers is a lack of scalable tools to rapidly and consistently measure Earth's biodiversity. Environmental genomic tools provide some hope in the face of this crisis, and DNA metabarcoding, in particular, is a powerful approach for biodiversity assessment at large spatial scales. However, metabarcoding studies are variable in their taxonomic, temporal, or spatial scope, investigating individual species, specific taxonomic groups, or targeted communities at local or regional scales. With the advent of modern, ultra-high throughput sequencing platforms, conducting deep sequencing metabarcoding surveys with multiple DNA markers will enhance the breadth of biodiversity coverage, enabling comprehensive, rapid bioassessment of all the organisms in a sample. Here, we report on a systematic literature review of 1,563 articles published about DNA metabarcoding and summarize how this approach is rapidly revolutionizing global bioassessment efforts. Specifically, we quantify the stakeholders using DNA metabarcoding, the dominant applications of this technology, and the taxonomic groups assessed in these studies. We show that while DNA metabarcoding has reached global coverage, few studies deliver on its promise of near-comprehensive biodiversity assessment. We then outline how DNA metabarcoding can help us move toward real-time, global bioassessment, illustrating how different stakeholders could benefit from DNA metabarcoding. Next, we address barriers to widespread adoption of DNA metabarcoding, highlighting the need for standardized sampling protocols, experts and computational resources to handle the deluge of genomic data, and standardized, open-source bioinformatic pipelines. Finally, we explore how technological and scientific advances will realize the promise of total biodiversity assessment in a sample—from microbes to mammals—and unlock the rich information genomics exposes, opening new possibilities for merging whole-system DNA metabarcoding with (1) abundance and biomass quantification, (2) advanced modeling, such as species occupancy models, to improve species detection, (3) population genetics, (4) phylogenetics, and (5) food web and functional gene analysis. While many challenges need to be addressed to facilitate widespread adoption of environmental genomic approaches, concurrent scientific and technological advances will usher in methods to supplement existing bioassessment tools reliant on morphological and abiotic data. This expanded toolbox will help ensure that the best tool is used for the job and enable exciting integrative techniques that capitalize on multiple tools. Collectively, these new approaches will aid in addressing the global biodiversity crisis we now face.

Morphological vs. DNA metabarcoding approaches for the evaluation of stream ecological status with benthic invertebrates: Testing different combinations of markers and strategies of data filtering

Macroinvertebrate assemblages are the most common bioindicators used for stream biomonitoring, yet the standard approach exhibits several time-consuming steps, including the sorting and identification of organisms based on morphological criteria. In this study, we examined if DNA metabarcoding could be used as an efficient molecular-based alternative to the morphology-based monitoring of streams using macroinvertebrates. We compared results achieved with the standard morphological identification of organisms sampled in 18 sites located on 15 French wadeable streams to results obtained with the DNA metabarcoding identification of sorted bulk material of the same macroinvertebrate samples, using read numbers (expressed as relative frequencies) as a proxy for abundances. In particular, we evaluated how combining and filtering metabarcoding data obtained from three different markers (COI: BF1-BR2, 18S: Euka02 and 16S: Inse01) could improve the efficiency of bioassessment. In total, 140 taxa were identified based on morphological criteria, and 127 were identified based on DNA metabarcoding using the three markers, with an overlap of 99 taxa. The threshold values used for sequence filtering based on the "best identity" criterion and the number of reads had an effect on the assessment efficiency of data obtained with each marker. Compared to single marker results, combining data from different markers allowed us to improve the match between biotic index values obtained with the bulk DNA versus morphology-based approaches. Both approaches assigned the same ecological quality class to a majority (86%) of the site sampling events, highlighting both the efficiency of metabarcoding as a biomonitoring tool but also the need for further research to improve this efficiency.

Freshwater diatom biomonitoring through benthic kick-net metabarcoding

Biomonitoring is an essential tool for assessing ecological conditions and informing management strategies. The application of DNA metabarcoding and high throughput sequencing has improved data quantity and resolution for biomonitoring of taxa such as macroinvertebrates, yet, there remains the need to optimise these methods for other taxonomic groups. Diatoms have a longstanding history in freshwater biomonitoring as bioindicators of water quality status. However, multi-substrate periphyton collection, a common diatom sampling practice, is time-consuming and thus costly in terms of labour. This study examined whether the benthic kick-net technique used for macroinvertebrate biomonitoring could be applied to bulk-sample diatoms for metabarcoding. To test this approach, we collected samples using both conventional multi-substrate microhabitat periphyton collections and bulk-tissue kick-net methodologies in parallel from replicated sites with different habitat status (good/fair). We found there was no significant difference in community assemblages between conventional periphyton collection and kick-net methodologies or site status, but there was significant difference between diatom communities depending on site (P = 0.042). These results show the diatom taxonomic coverage achieved through DNA metabarcoding of kick-net is suitable for ecological biomonitoring applications. The shift to a more robust sampling approach and capturing diatoms as well as macroinvertebrates in a single sampling event has the potential to significantly improve efficiency of biomonitoring programmes that currently only use the kick-net technique to sample macroinvertebrates.

Modelling technical and biological biases in macroinvertebrate community assessment from bulk preservative using multiple metabarcoding markers

DNA metabarcoding from the ethanol used to store macroinvertebrate bulk samples is a convenient methodological option in molecular biodiversity assessment and biomonitoring of aquatic ecosystems, as it preserves specimens and reduces problems associated with sample sorting. However, this method may be affected by errors and biases, which need to be thoroughly quantified before it can be mainstreamed into biomonitoring programmes. Here, we used 80 unsorted macroinvertebrate samples collected in Portugal under a Water Framework Directive monitoring programme, to compare community diversity and taxonomic composition metrics estimated through morphotaxonomy versus metabarcoding from storage ethanol using three markers (COI‐M19BR2, 16S‐Inse01 and 18S‐Euka02) and a multimarker approach. A preliminary in silico analysis showed that the three markers were adequate for the target taxa, with detection failures related primarily to the lack of adequate barcodes in public databases. Metabarcoding of ethanol samples retrieved far less taxa per site (alpha diversity) than morphotaxonomy, albeit with smaller differences for COI‐M19BR2 and the multimarker approach, while estimates of taxa turnover (beta diversity) among sites were similar across methods. Using generalized linear mixed models, we found that after controlling for differences in read coverage across samples, the probability of detection of a taxon was positively related to its proportional abundance, and negatively so to the presence of heavily sclerotized exoskeleton (e.g., Coleoptera). Overall, using our experimental protocol with different template dilutions, the COI marker showed the best performance, but we recommend the use of a multimarker approach to detect a wider range of taxa in freshwater macroinvertebrate samples. Further methodological development and optimization efforts are needed to reduce biases associated with body armouring and rarity in some macroinvertebrate taxa.

Marine biomonitoring with eDNA: Can metabarcoding of water samples cut it as a tool for surveying benthic communities?

In the marine realm, biomonitoring using environmental DNA (eDNA) of benthic communities requires destructive direct sampling or the setting-up of settlement structures. Comparatively much less effort is required to sample the water column, which can be accessed remotely. In this study we assess the feasibility of obtaining information from the eukaryotic benthic communities by sampling the adjacent water layer. We studied two different rocky-substrate benthic communities with a technique based on quadrat sampling. We also took replicate water samples at four distances (0, 0.5, 1.5, and 20 m) from the benthic habitat. Using broad range primers to amplify a ca. 313 bp fragment of the cytochrome oxidase subunit I gene, we obtained a total of 3,543 molecular operational taxonomic units (MOTUs). The structure obtained in the two environments was markedly different, with Metazoa, Archaeplastida and Stramenopiles being the most diverse groups in benthic samples, and Hacrobia, Metazoa and Alveolata in the water. Only 265 MOTUs (7.5%) were shared between benthos and water samples and, of these, 180 (5.1%) were identified as benthic taxa that left their DNA in the water. Most of them were found immediately adjacent to the benthos, and their number decreased as we moved apart from the benthic habitat. It was concluded that water eDNA, even in the close vicinity of the benthos, was a poor proxy for the analysis of benthic structure, and that direct sampling methods are required for monitoring these complex communities via metabarcoding.

Assessment of stream macroinvertebrate communities with eDNA is not congruent with tissue-based metabarcoding

Freshwater biomonitoring programmes routinely sample aquatic macroinvertebrates. These samples are time-consuming to collect, as well as challenging and costly to identify reliably genus or species. Environmental DNA (eDNA) metabarcoding has emerged as a surrogate to traditional collection techniques and has been used in whole-community approaches across several taxa and ecosystems. However, the usefulness of eDNA-based detection of freshwater macroinvertebrates has not been extensively explored. Few studies have directly compared bulk sample and eDNA metabarcoding at a local scale to assess how effective each method is at characterizing aquatic macroinvertebrate communities. Here, we collected both eDNA and kicknet samples at the same sample transect locations across nine different streams in southern Ontario, Canada. We observed minimal overlap in community composition between these paired samples. Bulk tissue metabarcoding resulted in a greater proportion of sequences belonging to metazoan taxa (over 99%) than eDNA (12%) and had higher OTU richness for macroinvertebrate taxa. We suggest that degenerate primers are not effective for eDNA metabarcoding due to the high degree of nontarget amplification and subsequently low yield of target DNA. While both bulk sample and eDNA metabarcoding had the power to detect differences between stream communities, eDNA did not represent local communities. Bulk tissue metabarcoding thus provides a more accurate representation of local stream macroinvertebrate communities and is the preferred method if smaller-scale spatial resolution is an important factor in data analyses.

Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks

Current approaches to ecological assessment are limited by the traditional morpho-taxonomic methods presently employed and the inability to meet increasing demands for rapid assessments. Advancements in high throughput sequencing now enable rapid high-resolution ecological assessment using environmental DNA (eDNA). Here we test the ability of using eDNA-based ecological assessment methods against traditional assessment of two key indicator groups (diatoms and macroinvertebrates) and show how eDNA across multiple gene regions (COI, rbcL, 12S and 18S) can be used to infer interactive networks that link to ecological assessment criteria. We compared results between taxonomic and eDNA based assessments and found significant positive associations between macroinvertebrate (p < 0.001 R² = 0.645) and diatom (p = 0.015, R² = 0.222) assessment metrics. We further assessed the ability of eDNA based assessment to identify environmentally sensitive genera and found an order of magnitude greater potential for 18S, versus COI or rbcL, to determine environmental filtering of ecologically assessed communities. Lastly, we compared the ability of traditional metrics against co-occurrence network properties of our combined 18S, COI and rbcL indicator genera to infer habitat quality measures currently used by managers. We found that transitivity (network connectivity), linkage density and cohesion were significantly associated with habitat modification scores (HMS), whereas network properties were inconsistent with linking to the habitat quality score (HQS) metric. The incorporation of multi-marker eDNA network assessment opens up a means for finer scale ecological assessment, currently limited using traditional methods. While utilization of eDNA-based assessment is recommended, direct comparisons with traditional approaches are difficult as the methods are intrinsically different and should be treated as such with regards to future research. Overall, our findings show that eDNA can be used for effective ecological assessment while offering a wider range of scope and application compared to traditional assessment methods.

Aquatic insect community structure revealed by eDNA metabarcoding derives indices for environmental assessment

Environmental DNA (eDNA) analysis provides an efficient and objective approach for monitoring and assessing ecological status; however, studies on the eDNA of aquatic insects, such as Ephemeroptera, Plecoptera, and Trichoptera (EPT), are limited despite its potential as a useful indicator of river health. Here, we investigated the community structures of aquatic insects using eDNA and evaluated the applicability of eDNA data for calculating assessment indices. Field surveys were conducted to sample river water for eDNA at six locations from upstream to downstream of two rivers in Japan in July and November 2016. Simultaneously, aquatic insects were collected using the traditional Surber net survey method. The communities of aquatic insects were revealed using eDNA by targeting the cytochrome oxidase subunit I gene in mitochondrial DNA via metabarcoding analyses. As a result, the eDNA revealed 63 families and 75 genera of aquatic insects, which was double than that detected by the Surber net survey (especially for families in Diptera and Hemiptera). The seasonal differences of communities were distinguished by both the eDNA and Surber net survey data. Furthermore, the total nitrogen concentration, a surrogate of organic pollution, showed positive correlations with biotic environmental assessment indices (i.e., EPT index and Chironomidae index) calculated using eDNA at the genus-level resolution but the indices calculated using the Surber net survey data. Our results demonstrated that eDNA analysis with higher taxonomic resolution can provide as a more sensitive environmental assessment index than the traditional method that requires biotic samples.

Method for the Identification of Plant DNA in Food Using Alignment-Free Analysis of Sequencing Reads: A Case Study on Lupin

Fast and reliable analytical methods for the identification of plants from metagenomic samples play an important role in identifying the components of complex mixtures of processed biological materials, including food, herbal products, gut contents or environmental samples. Different PCR-based methods that are commonly used for plant identification from metagenomic samples are often inapplicable due to DNA degradation, a low level of successful amplification or a lack of detection power. We introduce a method that combines metagenomic sequencing and an alignment-free k-mer based approach for the identification of plant DNA in processed metagenomic samples. Our method identifies plant DNA directly from metagenomic sequencing reads and does not require mapping or assembly of the reads. We identified more than 31,000 Lupinus-specific 32-mers from assembled chloroplast genome sequences. We demonstrate that lupin DNA can be detected from controlled mixtures of sequences from target species (different Lupinus species) and closely related non-target species (Arachis hypogaea, Glycine max, Pisum sativum, Vicia faba, Phaseolus vulgaris, Lens culinaris, and Cicer arietinum). Moreover, these 32-mers are detectable in the following processed samples: lupin flour, conserved seeds and baked cookies containing different amounts of lupin flour. Under controlled conditions, lupin-specific components are detectable in baked cookies containing a minimum of 0.05% of lupin flour in wheat flour.