High-throughput metabarcoding of eukaryotic diversity for environmental monitoring of offshore oil-drilling activities

Saline mine water influences eukaryote life in shallow groundwater of a tropical sandy stream

Eukaryotic communities in groundwater may be particularly sensitive to disturbance because they are adapted to stable environmental conditions and often have narrow spatial distributions. Traditional methods for characterising these communities, focussing on groundwater-inhabiting macro- and meiofauna (stygofauna), are challenging because of limited taxonomic knowledge and expertise (particularly in less-explored regions), and the time and expense of morphological identification. The primary objective of this study was to evaluate the vulnerability of eukaryote communities in shallow groundwater to mine water discharge containing elevated concentrations of magnesium (Mg) and sulfate (SO4). The study was undertaken in a shallow sand bed aquifer within a wet-dry tropical setting. The aquifer, featuring a saline mine water gradient primarily composed of elevated Mg and SO4, was sampled from piezometers in the creek channel upstream and downstream of the mine water influence during the dry season when only subsurface water flow was present. Groundwater communities were characterised using both morphological assessments of stygofauna from net samples and environmental DNA (eDNA) targeting the 18S rDNA and COI mtDNA genes. eDNA data revealed significant shifts in community composition in response to mine waters, contrasting with findings from traditional morphological composition data. Changes in communities determined using eDNA data were notably associated with concentrations of SO42-, Mg2+ and Na+, and water levels in the piezometers. This underscores the importance of incorporating molecular approaches in impact assessments, as relying solely on traditional stygofauna sampling methods in similar environments may lead to inaccurate conclusions about the responses of the assemblage to studied impacts.

Assessing the potential of nematode metabarcoding for benthic monitoring of offshore oil platforms

Environmental DNA metabarcoding is gaining momentum as a time and cost-effective tool for biomonitoring and environmental impact assessment. Yet, its use as a replacement for the conventional marine benthic monitoring based on morphological analysis of macrofauna is still challenging. Here we propose to study the meiofauna, which is much better represented in sediment DNA samples. We focus on nematodes, which are the most numerous and diverse group of meiofauna. Our aim is to assess the potential of nematode metabarcoding to monitor impacts associated with offshore oil platform activities. To achieve this goal, we used nematode-optimized marker (18S V1V2-Nema) and universal eukaryotic marker (18S V9) region to analyse 252 sediment DNA samples collected near three offshore oil platforms in the North Sea. For both markers, we analysed changes in alpha and beta diversity in relation to distance from the platforms and environmental variables. We also defined three impact classes based on selected environmental variables that are associated with oil extraction activities and used random forest classifiers to compare the predictive performance of both datasets. Our results show that alpha- and beta-diversity of nematodes varies with the increasing distance from the platforms. The variables directly related to platform activity, such as Ba and THC, strongly influence the nematode community. The nematode metabarcoding data provide more robust predictive models than eukaryotic data. Furthermore, the nematode community appears more stable in time and space, as illustrated by the overlap of nematode datasets obtained from the same platform three years apart. A significative negative correlation between distance and Shannon diversity also advocates for higher performance of the V1V2-Nema over the V9. Overall, these results suggest that the sensitivity of nematodes is higher compared to the eukaryotic community. Hence, nematode metabarcoding has the potential to become an effective tool for benthic monitoring in marine environment.

Environmental drivers of Arctic communities based on metabarcoding of marine sediment eDNA

Our ability to assess biodiversity at relevant spatial and temporal scales for informing management is of increasing importance given this is foundational to identify and mitigate the impacts of global change. Collecting baseline information and tracking ecological changes are particularly important for areas experiencing rapid changes and representing data gaps such as Arctic marine ecosystems. Environmental DNA has the potential to provide such data. We extracted environmental DNA from 90 surface sediment samples to assess eukaryote diversity around Greenland and Svalbard using two separate primer pairs amplifying different sections of the 18S rRNA gene. We detected 27 different phyla and 99 different orders and found that temperature and the change in temperature explained the most variation in the community in a single linear model, while latitude, sea ice cover and change in temperature explained the most variation in the community when assessed by individual non-linear models. We identified potential indicator taxa for Arctic climate change, including a terebellid annelid worm. In conclusion, our study demonstrates that environmental DNA offers a feasible method to assess biodiversity and identifies warming as a key driver of differences in biodiversity across these remote ecosystems.

Dominance of species sorting over dispersal at microgeographical scales in polluted lotic ecosystems

Global rivers, particularly those in populated urban areas, are challenged by multiple stressors such as pollution from anthropogenic activities. Dissecting the relative role of each ecological process involved in structuring biotic communities is fundamental in both theoretical and applied ecology. The ecological niche-based species sorting and stochastic dynamics-based dispersal are two major competing processes in determining community structure. Studies have reached a common realization on the environmental gradient-geographical scale relationship (EGGSR), resulting in species sorting over dispersal in determining community structure at large geographical scales where significant environmental gradients often exist. However, this relationship has been recently challenged at fine geographical scales when significant environmental gradients are formed by local anthropogenic activities. Here, we used three receiving rivers of wastewater treatment plants (WWTPs) as the promising system to test the hypothesis that species sorting plays a dominant role over dispersal in structuring zooplankton communities at microgeographical scales (∼1.2 km). After WWTP effluent discharge, we consistently detected significant environmental changes in all three receiving rivers, leading to significant variation in both community structure and taxonomic co-occurrence networks. Variation partitioning showed that environmental variables explained higher proportions of community variation than spatial ones, supporting that species sorting played a dominant role over dispersal in structuring zooplankton communities. Thus, our findings here reject EGGSR, illustrating that the effect of species sorting has been overlooked in disturbed aquatic ecosystems at fine spatial scales. More importantly, all analyses in multiple rivers here validate the "microscale species sorting" hypothesis. The validation of such hypothesis provides a novel methodology for point source pollution management by assessing environment-community interactions and functional changes of biological communities. The differed variables underlying species sorting among three rivers illustrate that ecological management should be case-specific, with the full consideration of local water quality background and pollutant composition of each point pollution source.

Zeta diversity patterns in metabarcoded lotic algal assemblages as a tool for bioassessment

Assessments of the ecological health of algal assemblages in streams typically focus on measures of their local diversity and classify individuals by morphotaxonomy. Such assemblages are often connected through various ecological processes, such as dispersal, and may be more accurately assessed as components of regional-, rather than local-scale assemblages. With recent declines in the costs of sequencing and computation, it has also become increasingly feasible to use metabarcoding to more accurately classify algal species and perform regional-scale bioassessments. Recently, zeta diversity has been explored as a novel method of constructing regional bioassessments for groups of streams. Here, we model the use of zeta diversity to investigate whether stream health can be determined by the landscape diversity of algal assemblages. We also compare the use of DNA metabarcoding and morphotaxonomy classifications in these zeta diversity-based bioassessments of regional stream health. From 96 stream samples in California, we used various orders of zeta diversity to construct models of biotic integrity for multiple assemblages of diatoms, as well as hybrid assemblages of diatoms in combination with soft-bodied algae, using taxonomy data generated with both DNA sequencing as well as traditional morphotaxonomic approaches. We compared our ability to evaluate the ecological health of streams with the performance of multiple algal indices of biological condition. Our zeta diversity-based models of regional biotic integrity were more strongly correlated with existing indices for algal assemblages classified using metabarcoding compared to morphotaxonomy. Metabarcoding for diatoms and hybrid algal assemblages involved rbcL and 18S V9 primers, respectively. Importantly, we also found that these algal assemblages, independent of the classification method, are more likely to be assembled under a process of niche differentiation rather than stochastically. Taken together, these results suggest the potential for zeta diversity patterns of algal assemblages classified using metabarcoding to inform stream bioassessments.

Arsenic biotransformation genes and As transportation in soil-rice system affected by iron-oxidizing strain (Ochrobactrum sp.)

Arsenic (As) biotransformation in soil affects As biogeochemical cycling and is associated with As accumulation in rice. After inoculation with 1% iron-oxidizing bacteria (FeOB) in paddy soil, As speciation, As biotransformation genes in soil, As/Fe in Fe plaques, and As accumulation in rice were characterized. Compared with the control, the available As concentrations in soils decreased while amorphous and poorly crystalline Fe-Al oxidized As and crystalline Fe-Al oxidized As fractions increased of F (FeOB) and RF (rice and FeOB) treatments. Fe concentrations increased and positively correlated with As concentrations in Fe plaques on the rice root surface (***P < 0.001). Compared with R (rice), Monomethyl As (MMA), dimethyl As (DMA), arsenate (As(V)), and arsenite (As(III)) concentrations in rice plants showed a downwards trend of RF treatment. The As concentration in grains was below the National Standard for Food Safety (GB 2762-2017). A total of 16 As biotransformation genes in rhizosphere soils of different treatments (CK, F, R and RF were quantified by high-throughput qPCR (HT-qPCR). Compared with the control, the As(V) reduction and As transport genes abundance in other treatments increased respectively by 54.54%-69.17% and 54.63%-73.71%; the As(III) oxidation and As (de) methylation genes did not change significantly; however, several As(III) oxidation genes (aoxA, aoxB, aoxS, and arsH) increased. These results revealed that FeOB could reduce, transport As, and maybe also oxidize As. In addition, As(III) oxidation gene (aoxC) in rhizosphere soil was more abundant than in non-rhizosphere soil. It indicated that radial oxygen loss (ROL) promoted As(III) oxidation in rhizosphere soils. The results provide evidence for As biotransformation by ROL and FeOB in soil-rice system. ROL affects As oxidation and immobilization, and FeOB affects As reduction, transportation and may also affect As oxidation.

Environmental DNA-based profiling of benthic bacterial and eukaryote communities along a crude oil spill gradient in a coral reef in the Persian Gulf

Coral reef ecosystems in the Persian Gulf are frequently exposed to crude oil spills. We investigated benthic bacterial and eukaryote community structures at such coral reef sites subjected to different degrees of polycyclic aromatic hydrocarbon (PAH) pollution using environmental DNA (eDNA) metabarcoding. Both bacterial and eukaryote communities responded with pronounced shifts to crude oil pollution and distinguished control sites, moderately and heavily impacted sites with significant confidentiality. The observed community patterns were predominantly driven by Alphaproteobacteria and metazoans. Among these, we identified individual genera that were previously linked to oil spill stress, but also taxa, for which a link to hydrocarbon still remains to be established. Considering the lack of an early-warning system for the environmental status of coral reef ecosystems exposed to frequent crude-oil spills, our results encourage further research towards the development of an eDNA-based biomonitoring tool that exploits benthic bacterial and eukaryote communities as bioindicators.

Metabarcoding of harmful algal bloom species in sediments from four coastal areas of the southeast China

In the past three decades, harmful algal blooms (HAB) have become more frequent and widespread in southeast Chinese sea areas. Resting stages are regarded as the “seed bank” of algal blooms, and play an important role in initiating HABs. The distribution of resting stages in sediments especially those of HAB species can make good predictions about the potential risk of future blooms, however with limited reports. In this study, surface sediment samples were collected in the four sea areas along the southeast Chinese coasts, including Dafeng Port (DF) in the southern Yellow Sea, Xiangshan Bay (XS), Funing Bay (FN), and Dongshan Bay (DS) in the East China Sea. Diversity and community structure of eukaryotic microalgae in surface sediments were assessed by metabarcoding V4 region of the 18S rDNA, focusing on the distribution of HAB species. Biogenic elements including total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), biogenic silicon (BSi), and moisture content (MC) were analyzed. A total of 454 eukaryotic algal OTUs were detected, which belonged to 31 classes of 9 phyla. Altogether 149 algal species were detected in this study, and 59 taxa have been reported to form resting stages. Eukaryotic algal community was similar in XS, FN and DS of the East China Sea, which were predominated by dinoflagellates. However, algal community was different in DF of the Yellow Sea, and characterized by the dominance of chrysophytes and low OTU richness. The distribution of most abundant HAB species showed positive correlations with TN, BSi, and TOC, suggesting that eutrophication and consequent increase in diatom productivity may have a significant influence on the distribution of HAB species and facilitate the occurrence of HABs. Furthermore, HAB species occurred more abundantly and widely in FN. Our results suggest high potential risks of HABs in the southeast Chinese coast especially in Funing Bay.

Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods

Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.

Fish Diversity Monitored by Environmental DNA in the Yangtze River Mainstream

Surveys and assessments based on environmental DNA are not only efficient and time-saving, but also cause less harm to monitoring targets. Environmental DNA has become a common tool for the assessment and monitoring of aquatic organisms. In this study, we investigated fish resources in the Yangtze River mainstream using environmental DNA, and the variations in fish during two seasons (spring and autumn) were compared. The results showed that 13 species were identified in spring, and nine species of fish were identified in autumn. The fish with higher eDNA detection were Sinibotia superciliaris, Tachysurus fulvidraco, Cyprinus carpio, Ctenopharyngodon Idella, Monopterus albus, Acanthogobius hasta, Saurogobio dabryi, Oncorhynchus mykiss, Mugil cephalus, Odontamblyopus rubicundus. Seasonal variation between spring and autumn was not significant, and the environmental factors had different effects on fish assemblages during the two seasons. Our study used the eDNA technique to monitor the composition of fish in the spring and autumn in the Yangtze River mainstream, providing a new technology for the long-term management and protection of fishery resources in the region. Of course, problems such as pollution and insufficient databases are the current shortcomings of environmental DNA, which will be the focus of our future research and study.

Comparing sediment preservation methods for genomic biomonitoring of coastal marine ecosystems

To avoid loss of genetic information in environmental DNA (eDNA) field samples, the preservation of nucleic acids during field sampling is a critical step. In the development of standard operating procedures (SOPs) for eDNA-based compliance monitoring, the effect of different routinely used sediment preservations on biological community structures serving as bioindicators has gone untested. We compared eDNA metabarcoding results of marine bacterial communities from sample aliquots that were treated with a nucleic acid preservation solution (treated samples) and aliquots that were frozen without further treatment (non-treated samples). Sediment samples were obtained from coastal locations subjected to different stressors (aquaculture, urbanization, industry). DNA extraction efficiency, bacterial community profiles, and measures of alpha- and beta-diversity were highly congruent between treated and non-treated samples. As both preservation methods provide the same relevant information to environmental managers and regulators, we recommend the inclusion of both methods into SOPs for biomonitoring in marine coastal environments.

Quantification of marine benthic communities with metabarcoding

DNA metabarcoding methods have been implemented in studies aimed at detecting and quantifying marine benthic biodiversity. In such surveys, universal barcodes are amplified and sequenced from environmental DNA. To quantify biodiversity with DNA metabarcoding, a relation between the number of DNA sequences of a species and its biomass and/or the abundance is required. However, this relationship is complicated by many factors, and it is often unknown. In this study, we validate estimates of biomass and abundance from molecular approaches with those from the traditional morphological approach. Abundance and biomass were quantified from 126 samples of benthic intertidal mudflat using traditional morphological approaches and compared with frequency of occurrence and relative read abundance estimates from a molecular approach. A relationship between biomass and relative read abundance was found for two widely dispersed annelid taxa (Pygospio and Scoloplos). None of the other taxons, however, showed such a relationship. We discuss how quantification of abundance and biomass using molecular approaches are hampered by the ecology of DNA i.e. all the processes that determine the amount of DNA in the environment, including the ecology of the benthic species as well as the compositional nature of sequencing data.

Changes in protist communities in drainages across the Pearl River Delta under anthropogenic influence

Drainages in the Pearl River Delta urban agglomeration (PRDUA) host vital aquatic ecosystems and face enormous pressures from human activities in one of the largest urban agglomerations in the world. Despite being crucial components of aquatic ecosystems, the interactions and assembly processes of the protistan community are rarely explored in areas with serious anthropogenic disturbance. To elucidate the mechanisms of these processes, we used environmental DNA sequencing of 18S rDNA to investigate the influence of environmental factors and species interactions on the protistan community and its assembly in drainages of the PRDUA during summer. The protistan community showed a high level of diversity and a marked spatial pattern in this region. Community assembly was driven primarily by stochastic processes based on the Sloan neutral community model, explaining 74.28%, 75.82%, 73.67%, 74.40% and 51.24% of community variations in the BJ (Beijiang), XJ (Xijiang), PRD (Pearl River Delta), PRE (Pearl River Estuary) areas and in total, respectively. Meanwhile, environmental variables including temperature, pH, dissolved oxygen, transparency, nutrients and land use were strongly correlated with the composition and assembly of the protistan community, explaining 40.40% of variation in the protistan community. Furthermore, the bacterial community was simultaneously analysed by the 16S rDNA sequencing. Co-occurrence network analysis revealed that species interactions within bacteria (81.41% positive) or protists (82.80% positive), and those between bacteria and protists (50% positive and 50% negative) impacted the protistan community assembly. In summary, stochastic processes dominated, whereas species interactions and environmental factors also played important roles in shaping the protistan communities in drainages across the PRDUA. This study provides insights into the ecological patterns, assembly processes and species interactions underlying protistan dynamics in urban aquatic ecosystems experiencing serious anthropogenic disturbance.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Grab what you can-an evaluation of spatial replication to decrease heterogeneity in sediment eDNA metabarcoding

Environmental DNA methods such as metabarcoding have been suggested as possible alternatives or complements to the current practice of morphology-based diversity assessment for characterizing benthic communities in marine sediment. However, the source volume used in sediment eDNA studies is several magnitudes lower than that used in morphological identification. Here, we used data from a North Sea benthic sampling station to investigate to what extent metabarcoding data is affected by sampling bias and spatial heterogeneity. Using three grab parallels, we sampled five separate sediment samples from each grab. We then made five DNA extraction replicates from each sediment sample. Each extract was amplified targeting both the 18S SSU rRNA V1–V2 region for total eukaryotic composition, and the cytochrome c oxidase subunit I (COI) gene for metazoans only. In both datasets, extract replicates from the same sediment sample were significantly more similar than different samples from the same grab. Further, samples from different grabs were less similar than those from the same grab for 18S. Interestingly, this was not true for COI metabarcoding, where the differences within the same grab were similar to the differences between grabs. We also investigated how much of the total identified richness could be covered by extract replicates, individual sediment samples and all sediment samples from a single grab, as well as the variability of Shannon diversity and, for COI, macrofaunal biotic indices indicating environmental status. These results were largely consistent with the beta diversity findings, and show that total eukaryotic diversity can be well represented using 18S metabarcoding with a manageable number of biological replicates. Based on these results, we strongly recommend the combination of different parts of the surface of single grabs for eDNA extraction as well as several grab replicates, or alternatively box cores or similar. This will dilute the effects of dominating species and increase the coverage of alpha diversity. COI-based metabarcoding consistency was found to be lower compared to 18S, but COI macrofauna-based indices were more consistent than direct COI alpha diversity measures.

A step towards the validation of bacteria biotic indices using DNA metabarcoding for benthic monitoring

Environmental genomics is a promising field for monitoring biodiversity in a timely fashion. Efforts have increasingly been dedicated to the use of bacteria DNA derived data to develop biotic indices for benthic monitoring. However, a substantial debate exists about whether bacteria-derived data using DNA metabarcoding should follow, for example, a taxonomy-based or a taxonomy-free approach to marine bioassessments. Here, we showcase the value of DNA-based monitoring using the impact of fish farming as an example of anthropogenic disturbances in coastal areas and compare the performance of taxonomy-based and taxonomy-free approaches in detecting environmental alterations. We analysed samples collected near to the farm cages and along distance gradients from two aquaculture installations, and at control sites, to evaluate the effect of this activity on bacterial assemblages. Using the putative response of bacterial taxa to stress we calculated the taxonomy-based biotic index microgAMBI. The distribution of individual amplicon sequence variants (ASVs), as a function of a gradient in sediment acid volatile sulphides, was then used to derive a taxonomy-free bacterial biotic index specific for this data set using a de novo approach based on quantile regression splines. Our results show that microgAMBI revealed a organically enriched environment along the gradient. However, the de novo biotic index outperformed microgAMBI by providing a higher discriminatory power in detecting changes in abiotic factors directly related to fish production, whilst allowing the identification of new ASVs bioindicators. The de novo strategy applied here represents a robust method to define new bioindicators in regions or habitats where no previous information about the response of bacteria to environmental stressors exists.

A Comparison of DNA Metabarcoding and Microscopy Methodologies for the Study of Aquatic Microbial Eukaryotes

The procedures and methodologies employed to study microbial eukaryotic plankton have been thoroughly discussed. Two main schools exist—one insisting on classic microscopy methodologies and the other supporting modern high-throughput sequencing (DNA metabarcoding). However, few studies have attempted to combine both these approaches; most studies implement one method while ignoring the other. This work aims to contribute to this discussion and examine the advantages and disadvantages of each methodology by comparing marine plankton community results from microscopy and DNA metabarcoding. The results obtained by the two methodologies do not vary significantly for Bacillariophyta, although they do for Dinoflagellata and Ciliophora. The lower the taxonomic level, the higher the inconsistency between the two methodologies for all the studied groups. Considering the different characteristics of microscopy-based identification and DNA metabarcoding, this work underlines that each method should be chosen depending on the aims of the study. DNA metabarcoding provides a better estimate of the taxonomic richness of an ecosystem while microscopy provides more accurate quantitative results regarding abundance and biomass. In any case, the combined use of the two methods, if properly standardized, can provide much more reliable and accurate results for the study of marine microbial eukaryotes.

Biotic signals associated with benthic impacts of salmon farms from eDNA metabarcoding of sediments

Environmental DNA (eDNA) metabarcoding can rapidly characterize the composition and diversity of benthic communities, thus it has high potential utility for routine assessments of benthic impacts of marine finfish farming. In this study, 126 sediment grab samples from 42 stations were collected at six salmon farms in British Columbia, Canada. Benthic community changes were assessed by both eDNA metabarcoding of metazoans and macrofaunal polychaete surveys. The latter was done by analysing 11,466 individuals using a combination of morphology-based taxonomy and DNA barcoding. Study objectives were to: (i) compare biotic signals associated with benthic impacts of salmon farming in the two data sources, and (ii) identify potential eDNA indicators to facilitate monitoring in Canada. Alpha diversity parameters were consistently reduced near fish cage edge and negatively correlated with pore-water sulphide concentration, with coefficients ranging from -0.62 to -0.48. Although Polychaeta are a common indicator group, the negative correlation with pore-water sulphide concentration was much stronger for Nematoda OTU richness (correlation coefficient: -0.86) than for Polychaeta (correlation coefficient: -0.38). Presence/absence of Capitella generally agreed well between the two methods despite that they differed in the volume of sediments sampled and the molecular marker used. Multiple approaches were used to identify OTUs related to organic enrichment statuses. We demonstrate that eDNA metabarcoding generates biotic signals that could be leveraged for environmental assessment of benthic impacts of fish farms in multiple ways: both alpha diversity and Nematoda OTU richness could be used to assess the spatial extent of impact, and OTUs related to organic enrichment could be used to develop local biotic indices.

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.

Translational Molecular Ecology in practice: Linking DNA-based methods to actionable marine environmental management

Molecular-based approaches can provide timely biodiversity assessments, showing an immense potential to facilitate decision-making in marine environmental management. However, the uptake of molecular data into environmental policy remains minimal. Here, we showcase a selection of local to global scale studies applying molecular-based methodologies for environmental management at various stages of implementation. Drawing upon lessons learned from these case-studies, we provide a roadmap to facilitate applications of DNA-based methods to marine policies and to overcome the existing challenges. The main impediment identified is the need for standardized protocols to guarantee data comparison across spatial and temporal scales. Adoption of Translational Molecular Ecology - the sustained collaboration between molecular ecologists and stakeholders, will enhance consensus with regards to the objectives, methods, and outcomes of environmental management projects. Establishing a sustained dialogue among stakeholders is key to accelerating the adoption of molecular-based approaches for marine monitoring and assessment.

Monitoring the ecological status of rivers with diatom eDNA metabarcoding: A comparison of taxonomic markers and analytical approaches for the inference of a molecular diatom index

Recently, several studies demonstrated the usefulness of diatom eDNA metabarcoding as an alternative to assess the ecological quality of rivers and streams. However, the choice of the taxonomic marker as well as the methodology for data analysis differ between these studies, hampering the comparison of their results and effectiveness. The aim of this study was to compare two taxonomic markers commonly used in diatom metabarcoding and three distinct analytical approaches to infer a molecular diatom index. We used the values of classical morphological diatom index as a benchmark for this comparison. We amplified and sequenced both a fragment of the rbcL gene and the V4 region of the 18S rRNA gene for 112 epilithic samples from Swiss and French rivers. We inferred index values using three analytical approaches: by computing it directly from taxonomically assigned sequences, by calibrating de novo the ecovalues of all metabarcodes, and by using a supervised machine learning algorithm to train predictive models. In general, the values of index obtained using the two "taxonomy-free" approaches, encompassing molecular assignment and machine learning, were closer correlated to the values of the morphological index than the values based on taxonomically assigned sequences. The correlations of the three analytical approaches were higher in the case of rbcL compared to the 18S marker, highlighting the importance of the reference database which is more complete for the rbcL marker. Our study confirms the effectiveness of diatom metabarcoding as an operational tool for rivers ecological quality assessment and shows that the analytical approaches by-passing the taxonomic assignments are particularly efficient when reference databases are incomplete.

Benthic monitoring of oil and gas offshore platforms in the North Sea using environmental DNA metabarcoding

Since 2010, considerable efforts have been undertaken to monitor the environmental status of European marine waters and ensuring the development of methodological standards for the evaluation of this status. However, the current routine biomonitoring implicates time-consuming and costly manual sorting and morphological identification of benthic macrofauna. Environmental DNA (eDNA) metabarcoding represents an alternative to the traditional monitoring method with very promising results. Here, we tested it further by performing eDNA metabarcoding of benthic eukaryotic communities in the vicinity of two offshore oil and gas platforms in the North Sea. Three different genetic markers (18S V1V2, 18S V9 and COI) were used to assess the environmental pressures induced by the platforms. All markers showed patterns of alpha and beta diversity consistent with morphology-based macrofauna analyses. In particular, the communities' structure inferred from metabarcoding and morphological data significantly changed along distance gradients from the platforms. The impact of the operational discharges was also detected by the variation of biotic index values, AMBI index showing the best correlation between morphological and eDNA data sets. Finally, the sediment physicochemical parameters were used to build a local de novo pressure index that served as benchmark to test the potential of a taxonomy-free approach. Our study demonstrates that metabarcoding approach outperforms morphology-based approach and can be used as a cost and time-saving alternative solution to the traditional morphology-based monitoring in order to monitor more efficiently the impact of industrial activities on marine biodiversity.

qPCR-based assessment of microfaunal indicators of oil for monitoring benthos around oil and gas platforms

Today's benthic offshore biological monitoring of oil & gas (O&G) activities relies on macrofauna taxa enumeration. For the future, analysis of DNA isolated directly from sediments holds great potential for multi-trophic biodiversity surveys and the monitoring of a larger spectrum of benthic taxa, including micro-fauna. Here, we evaluate more specifically the potential of microfauna-specific gene quantification in relation to both petroleum-related discharge compounds and other seafloor environmental properties. We carried out this evaluation using sediment samples collected at drilling Region III on the Norwegian continental shelf where DNA metabarcoding of eukaryotic diversity was already performed. Generally, the quantification of microfauna indicator taxa related well to the gradient of contamination on the seafloor. Contrary to eukaryotic Euplotida, metabarcoding data and qPCR numbers for indicative prokaryotic taxa showed the same relationship to offshore contaminants (both showed positive relationship). We found absolute numbers of SSU rRNA gene copies of (1) Dinophyceae, Bacillariophyceae and Alcanivorax were correlated with the level of petroleum-related compounds but not with other environmental variables, (2) bacteria closely related to Shewanella were correlated with the concentration of Ba, PAH, as well to percent of gravel, (3) Desulfobacteriales correlated with petroleum-related contaminants, but as well with percent of gravel and grain size. Findings from our study suggest that biomonitoring surveys of O&G activities on benthos could benefit from quantification of specific micro-fauna indicators that is simpler and faster than the methods currently used for impact assessment of benthos.

Environmental DNA and RNA as Records of Human Exposome, Including Biotic/Abiotic Exposures and Its Implications in the Assessment of the Role of Environment in Chronic Diseases

Most of environment-related diseases often result from multiple exposures of abiotic and/or biotic stressors across various life stages. The application of environmental DNA/RNA (eDNA/eRNA) to advance ecological understanding has been very successfully used. However, the eminent extension of eDNA/eRNA-based approaches to estimate human exposure to biotic and/or abiotic environmental stressors to understand the environmental causes of chronic diseases has yet to start. Here, we introduce the potential of eDNA/eRNA for bio-monitoring of human exposome and health effects in the real environmental or occupational settings. This review is the first of its kind to discuss how eDNA/eRNA-based approaches can be applied for assessing the human exposome. eDNA-based exposome assessment is expected to rely on our ability to capture the genome- and epigenome-wide signatures left behind by individuals in the indoor and outdoor physical spaces through shedding, excreting, etc. Records of eDNA/eRNA exposome may reflect the early appearance, persistence, and presence of biotic and/or abiotic-exposure-mediated modifications in these nucleic acid molecules. Functional genome- and epigenome-wide mapping of eDNA offer great promise to help elucidate the human exposome. Assessment of longitudinal exposure to physical, biological, and chemical agents present in the environment through eDNA/eRNA may enable the building of an integrative causal dynamic stochastic model to estimate environmental causes of human health deficits. This model is expected to incorporate key biological pathways and gene networks linking individuals, their geographic locations, and random multi-hits of environmental factors. Development and validation of monitoring of eDNA/eRNA exposome should seriously be considered to introduce into safety and risk assessment and as surrogates of chronic exposure to environmental stressors. Here we highlight that eDNA/eRNA reflecting longitudinal exposure of both biotic and abiotic environmental stressors may serve as records of human exposome and discuss its application as molecular tools for understanding the toxicogenomics basis of environment-related health deficits.

Evaluation of a eukaryote phylogenetic microarray for environmental monitoring of marine sediments

Increased exploitation of resources in sensitive marine ecosystems emphasizes the importance of knowledge regarding ecological impacts. However, current bio-monitoring practices are limited in terms of target-organisms and temporal resolution. Hence, developing new technologies is vital for enhanced ecosystem understanding. In this study, we have applied a prototype version of a phylogenetic microarray to assess the eukaryote community structures of marine sediments from an area with ongoing oil and gas drilling activity. The results were compared with data from both sequencing (metabarcoding) and morphology-based monitoring to evaluate whether microarrays were capable of detecting ecosystem disturbances. A significant correlation between microarray data and chemical pollution indicators, as well as sequencing-based results, was demonstrated, and several potential indicator organisms for pollution-associated parameters were identified, among them a large fraction of microorganisms not covered by traditional morphology-based monitoring. This suggests that microarrays have a potential in future environmental monitoring.

Microbial driven iron reduction affects arsenic transformation and transportation in soil-rice system

The microbe-driven iron cycle plays an important role in speciation transformation and migration of arsenic (As) in soil-rice systems. In this study, pot experiments were used to investigate the effect of bacterial iron (Fe) reduction processes in soils on As speciation and migration, as well as on As uptake in soil-rice system. During the rice growth period, pH and electrical conductivity (EC) in soil solutions initially increased and then decreased, with the ranges of 7.4-8.8 and 116.3-820 mS cm^-1, respectively. The concentrations of Fe, total As and As(III) showed an increasing trend in the rhizosphere and non-rhizosphere soil solutions with the increasing time. Fe concentrations were significantly positively correlated with total As and As(III) concentrations (***p < 0.001) in the soil solutions. The abundances of the arsenate reductase gene (arsC) and the As(III) S-adenosylmethionine methyltransferase gene (arsM) in rhizosphere soils were higher than those in non-rhizosphere soils, while the abundance of the Fe-reducing bacteria (Geo) showed an opposite trend. Moreover, it showed that the Geo abundance was significantly positively correlated with that of the arsC (***p < 0.001) and arsM (**p < 0.01) genes, respectively. The abundances of Geo, arsC and arsM genes were significantly positively correlated with the concentrations of Fe, total As and As(III) in the soil solutions (*p < 0.05). Moreover, the abundances of arsC and arsM genes were significantly negatively correlated with total As and As(III) in rice grains (*P < 0.05). These results showed that the interaction of bacterial Fe reduction process and radial oxygen loss from roots promoted the reduction and methylation of As, and then decreased As uptake by rice, which provided a theoretical basis for alleviating As pollution in paddy soils.

Marine environmental DNA: Approaches, applications, and opportunities

Environmental DNA (eDNA) is increasingly being used to document species distributions and habitat use in marine systems, with much of the recent effort focused on leveraging advances in next-generation DNA sequencing to assess and track biodiversity across taxonomic groups. Environmental DNA offers a number of important advantages over traditional survey techniques, including non-invasive sampling, sampling where traditional approaches are impractical or inefficient (e.g. deep oceans), reduced cost, and increased detection sensitivity. However, eDNA applications are currently limited because of an insufficient understanding of the influence of sample source, analytical approach, and marker type on eDNA detections. Because approaches vary considerably among eDNA studies, we present a summary of the current state of the field and emerging best practices. The impact of observed variation in rates of eDNA production, persistence, and transport are also discussed and future research needs are highlighted with the goal of expanding eDNA applications, including the development of statistical models to improve the predictability of eDNA detection and quantification.

Metabarcoding successfully tracks temporal changes in eukaryotic communities in coastal sediments

Metabarcoding is a method that combines high-throughput DNA sequencing and DNA-based identification. Previously, this method has been successfully used to target spatial variation of eukaryote communities in marine sediments, however, the temporal changes in these communities remain understudied. Here, we follow the temporal changes of the eukaryote communities in Baltic Sea surface sediments collected from two coastal localities during three seasons of two consecutive years. Our study reveals that the structure of the sediment eukaryotic ecosystem was primarily driven by annual and seasonal changes in prevailing environmental conditions, whereas spatial variation was a less significant factor in explaining the variance in eukaryotic communities over time. Therefore, our data suggests that shifts in regional climate regime or large-scale changes in the environment are the overdriving factors in shaping the coastal eukaryotic sediment ecosystems rather than small-scale changes in local environmental conditions or heterogeneity in ecosystem structure. More studies targeting temporal changes are needed to further understand the long-term trends in ecosystem stability and response to climate change. Furthermore, this work contributes to the recent efforts in developing metabarcoding applications for environmental biomonitoring, proving a comprehensive option for traditional monitoring approaches.

Characterization of ecto- and endoparasite communities of wild Mediterranean teleosts by a metabarcoding approach

Next-generation sequencing methods are increasingly used to identify eukaryotic, unicellular and multicellular symbiont communities within hosts. In this study, we analyzed the non-specific reads obtained during a metabarcoding survey of the bacterial communities associated to three different tissues collected from 13 wild Mediterranean teleost fish species. In total, 30 eukaryotic genera were identified as putative parasites of teleosts, associated to skin mucus, gills mucus and intestine: 2 ascomycetes, 4 arthropods, 2 cnidarians, 7 nematodes, 10 platyhelminthes, 4 apicomplexans, 1 ciliate as well as one order in dinoflagellates (Syndiniales). These results highlighted that (1) the metabarcoding approach was able to uncover a large spectrum of symbiotic organisms associated to the fish species studied, (2) symbionts not yet identified in several teleost species were putatively present, (3) the parasitic diversity differed markedly across host species and (4) in most cases, the distribution of known parasitic genera within tissues is in accordance with the literature. The current work illustrates the large insights that can be gained by making maximum use of data from a metabarcoding approach.

Microbial Eukaryotes in Oil Sands Environments: Heterotrophs in the Spotlight

Hydrocarbon extraction and exploitation is a global, trillion-dollar industry. However, for decades it has also been known that fossil fuel usage is environmentally detrimental; the burning of hydrocarbons results in climate change, and environmental damage during extraction and transport can also occur. Substantial global efforts into mitigating this environmental disruption are underway. The global petroleum industry is moving more and more into exploiting unconventional oil reserves, such as oil sands and shale oil. The Albertan oil sands are one example of unconventional oil reserves; this mixture of sand and heavy bitumen lying under the boreal forest of Northern Alberta represent one of the world’s largest hydrocarbon reserves, but extraction also requires the disturbance of a delicate northern ecosystem. Considerable effort is being made by various stakeholders to mitigate environmental impact and reclaim anthropogenically disturbed environments associated with oil sand extraction. In this review, we discuss the eukaryotic microbial communities associated with the boreal ecosystem and how this is affected by hydrocarbon extraction, with a particular emphasis on the reclamation of tailings ponds, where oil sands extraction waste is stored. Microbial eukaryotes, or protists, are an essential part of every global ecosystem, but our understanding of how they affect reclamation is limited due to our fledgling understanding of these organisms in anthropogenically hydrocarbon-associated environments and the difficulties of studying them. We advocate for an environmental DNA sequencing-based approach to determine the microbial communities of oil sands associated environments, and the importance of studying the heterotrophic components of these environments to gain a full understanding of how these environments operate and thus how they can be integrated with the natural watersheds of the region.

Multi-marker eDNA metabarcoding survey to assess the environmental impact of three offshore gas platforms in the North Adriatic Sea (Italy)

The environmental DNA (eDNA) metabarcoding represents a new promising tool for biomonitoring and environmental impact assessment. One of the main advantages of eDNA metabarcoding, compared to the traditional morphotaxonomy-based methods, is to provide a more holistic biodiversity information that includes inconspicuous morphologically non-identifiable taxa. Here, we use eDNA metabarcoding to survey marine biodiversity in the vicinity of the three offshore gas platforms in North Adriatic Sea (Italy). We isolated eDNA from 576 water and sediment samples collected at 32 sampling sites situated along four axes at increasing distances from the gas platforms. We obtained about 46 million eDNA sequences for 5 markers from nuclear 18S V1V2, 18S V4, 18S 37F and mitochondrial 16S and COI genes that cover a wide diversity of benthic and planktonic eukaryotes. Our results showed some impact of platform activities on benthic and pelagic communities at very close distance (<50 m), while communities for intermediate (125 m, 250 m, 500 m) and reference (1000 m, 2000 m) sites did not show any particular biodiversity changes that could be related to platforms activities. The most significant community change along the distance gradient was obtained with the 18S V1V2 marker targeting benthic eukaryotes, even though other markers showed similar trends, but to a lesser extent. These results were congruent with the AMBI index inferred from the eDNA sequences assigned to benthic macrofauna. We finally explored the relation between various physicochemical parameters, including hydrocarbons, on benthic community in the case of one of the platforms. Our results showed that these communities were not significantly impacted by most of hydrocarbons, but rather by macro-elements and sediment texture.

SLIM: a flexible web application for the reproducible processing of environmental DNA metabarcoding data

Background

High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) has become a routine tool for biodiversity survey and ecological studies. By including sample-specific tags in the primers prior PCR amplification, it is possible to multiplex hundreds of samples in a single sequencing run. The analysis of millions of sequences spread into hundreds to thousands of samples prompts for efficient, automated yet flexible analysis pipelines. Various algorithms and software have been developed to perform one or multiple processing steps, such as paired-end reads assembly, chimera filtering, Operational Taxonomic Unit (OTU) clustering and taxonomic assignment. Some of these software are now well established and widely used by scientists as part of their workflow. Wrappers that are capable to process metabarcoding data from raw sequencing data to annotated OTU-to-sample matrix were also developed to facilitate the analysis for non-specialist users. Yet, most of them require basic bioinformatic or command-line knowledge, which can limit the accessibility to such integrative toolkits. Furthermore, for flexibility reasons, these tools have adopted a step-by-step approach, which can prevent an easy automation of the workflow, and hence hamper the analysis reproducibility.

Results

We introduce SLIM, an open-source web application that simplifies the creation and execution of metabarcoding data processing pipelines through an intuitive Graphic User Interface (GUI). The GUI interact with well-established software and their associated parameters, so that the processing steps are performed seamlessly from the raw sequencing data to an annotated OTU-to-sample matrix. Thanks to a module-centered organization, SLIM can be used for a wide range of metabarcoding cases, and can also be extended by developers for custom needs or for the integration of new software. The pipeline configuration (i.e. the modules chaining and all their parameters) is stored in a file that can be used for reproducing the same analysis.

Conclusion

This web application has been designed to be user-friendly for non-specialists yet flexible with advanced settings and extensibility for advanced users and bioinformaticians. The source code along with full documentation is available on the GitHub repository (https://github.com/yoann-dufresne/SLIM) and a demonstration server is accessible through the application website (https://trtcrd.github.io/SLIM/).

The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs.

Sample size effects on the assessment of eukaryotic diversity and community structure in aquatic sediments using high-throughput sequencing

Understanding how biodiversity changes in time and space is vital to assess the effects of environmental change on benthic ecosystems. Due to the limitations of morphological methods, there has been a rapid expansion in the application of high-throughput sequencing methods to study benthic eukaryotic communities. However, the effect of sample size and small-scale spatial variation on the assessment of benthic eukaryotic diversity is still not well understood. Here, we investigate the effect of different sample volumes in the genetic assessment of benthic metazoan and non-metazoan eukaryotic community composition. Accordingly, DNA was extracted from five different cumulative sediment volumes comprising 100% of the top 2 cm of five benthic sampling cores, and used as template for Ilumina MiSeq sequencing of 18 S rRNA amplicons. Sample volumes strongly impacted diversity metrics for both metazoans and non-metazoan eukaryotes. Beta-diversity of treatments using smaller sample volumes was significantly different from the beta-diversity of the 100% sampled area. Overall our findings indicate that sample volumes of 0.2 g (1% of the sampled area) are insufficient to account for spatial heterogeneity at small spatial scales, and that relatively large percentages of sediment core samples are needed for obtaining robust diversity measurement of both metazoan and non-metazoan eukaryotes.

Can non-destructive DNA extraction of bulk invertebrate samples be used for metabarcoding?

Background

High throughput DNA sequencing of bulk invertebrate samples or metabarcoding is becoming increasingly used to provide profiles of biological communities for environmental monitoring. As metabarcoding becomes more widely applied, new reference DNA barcodes linked to individual specimens identified by taxonomists are needed. This can be achieved through using DNA extraction methods that are not only suitable for metabarcoding but also for building reference DNA barcode libraries.

Methods

In this study, we test the suitability of a rapid non-destructive DNA extraction method for metabarcoding of freshwater invertebrate samples.

Results

This method resulted in detection of taxa from many taxonomic groups, comparable to results obtained with two other tissue-based extraction methods. Most taxa could also be successfully used for subsequent individual-based DNA barcoding and taxonomic identification. The method was successfully applied to field-collected invertebrate samples stored for taxonomic studies in 70% ethanol at room temperature, a commonly used storage method for freshwater samples.

Discussion

With further refinement and testing, non-destructive extraction has the potential to rapidly characterise species biodiversity in invertebrate samples, while preserving specimens for taxonomic investigation.

A cross-taxa study using environmental DNA/RNA metabarcoding to measure biological impacts of offshore oil and gas drilling and production operations

Standardized ecosystem-based monitoring surveys are critical for providing information on marine ecosystem health. Environmental DNA/RNA (eDNA/eRNA) metabarcoding may facilitate such surveys by quickly and effectively characterizing multi-trophic levels. In this study, we assessed the suitability of eDNA/eRNA metabarcoding to evaluate changes in benthic assemblages of bacteria, Foraminifera and other eukaryotes along transects at three offshore oil and gas (O&G) drilling and production sites, and compared these to morphologically characterized macro-faunal assemblages. Bacterial communities were the most responsive to O&G activities, followed by Foraminifera, and macro-fauna (the latter assessed by morphology). The molecular approach enabled detection of hydrocarbon degrading taxa such as the bacteria Alcanivorax and Microbulbifer at petroleum impacted stations. Most identified indicator taxa, notably among macro-fauna, were highly specific to site conditions. Based on our results we suggest that eDNA/eRNA metabarcoding can be used as a stand-alone method for biodiversity assessment or as a complement to morphology-based monitoring approaches.

A from-benchtop-to-desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding studies

The main objective of this work was to develop and validate a robust and reliable "from-benchtop-to-desktop" metabarcoding workflow to investigate the diet of invertebrate-eaters. We applied our workflow to faecal DNA samples of an invertebrate-eating fish species. A fragment of the cytochrome c oxidase I (COI) gene was amplified by combining two minibarcoding primer sets to maximize the taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq platform. We developed a filtering approach based on a series of nonarbitrary thresholds established from control samples and from molecular replicates to address the elimination of cross-contamination, PCR/sequencing errors and mistagging artefacts. This resulted in a conservative and informative metabarcoding data set. We developed a taxonomic assignment procedure that combines different approaches and that allowed the identification of ~75% of invertebrate COI variants to the species level. Moreover, based on the diversity of the variants, we introduced a semiquantitative statistic in our diet study, the minimum number of individuals, which is based on the number of distinct variants in each sample. The metabarcoding approach described in this article may guide future diet studies that aim to produce robust data sets associated with a fine and accurate identification of prey items.

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning

Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which is time-consuming and taxonomic-expertise demanding. High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) represents a promising alternative for benthic monitoring. However, an important fraction of eDNA sequences remains unassigned or belong to taxa of unknown ecology, which prevent their use for assessing the ecological quality status. Here, we show that supervised machine learning (SML) can be used to build robust predictive models for benthic monitoring, regardless of the taxonomic assignment of eDNA sequences. We tested three SML approaches to assess the environmental impact of marine aquaculture using benthic foraminifera eDNA, a group of unicellular eukaryotes known to be good bioindicators, as features to infer macro-invertebrates based biotic indices. We found similar ecological status as obtained from macro-invertebrates inventories. We argue that SML approaches could overcome and even bypass the cost and time-demanding morpho-taxonomic approaches in future biomonitoring.