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

Is it worthy to use environmental DNA instead of scientific trawling or video survey to monitor taxa in soft-bottom habitats?

Non-extractive techniques such as video analysis are increasingly used by scientists to study marine communities instead of extractive methods such as trawling. Currently, environmental DNA (eDNA) analysis is seen as a revolutionary tool to study taxonomic diversity. We aimed to determine which method is the most appropriate to describe fish and commercial invertebrate diversity comparing bottom trawl hauls, video transects and seawater eDNA. Our results reveal that video detected the lowest number of taxa and trawling the highest. eDNA analysis is powerful to describe marine bony fish communities, but some taxa of importance for the ecosystem such as elasmobranchs, crustaceans or molluscs are poorly detected. This may be due to several factors such as marker specificity, incomplete reference gene databases or low DNA release in the environment. For now, the various methods provide different information and none is exhaustive enough to be used alone for biodiversity characterisation.

Increasing marine trophic web knowledge through DNA analyses of fish stomach content: a step towards an ecosystem-based approach to fisheries research

Multispecies and ecosystem models, which are key for the implementation of ecosystem-based approaches to fisheries management, require extensive data on the trophic interactions between marine organisms, including changes over time. DNA metabarcoding, by allowing the simultaneous taxonomic identification of the community present in hundreds of samples, could be used for speeding up large-scale stomach content data collection. Yet, for DNA metabarcoding to be routinely implemented, technical challenges should be addressed, such as the potentially complicated sampling logistics, the detection of a high proportion of predator DNA, and the inability to provide reliable abundance estimations. Here, we present a DNA metabarcoding assay developed to examine the diet of five commercially important fish, which can be feasibly incorporated into routinary samplings. The method is devised to speed up the analysis process by avoiding the stomach dissection and content extraction steps, while preventing the amplification of predator DNA by using blocking primers. Tested in mock samples and in real stomach samples, the method has proven effective and shows great effectiveness discerning diet variations due to predator ecology or prey availability. Additionally, by applying our protocol to mackerel stomachs previously analyzed by visual inspection, we showcase how DNA metabarcoding could complement visually based data by detecting overlooked prey by the visual approach. We finally discuss how DNA metabarcoding-based data can contribute to trophic data collection. Our work reinforces the potential of DNA metabarcoding for the study and monitoring of fish trophic interactions and provides a basis for its incorporation into routine monitoring programs, which will be critical for the implementation of ecosystem-based approaches to fisheries management.

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.

Sediment DNA metabarcoding and morphology provide complementary insight into macrofauna and meiobenthos response to environmental gradients in an Arctic glacial fjord

Arctic fjords ecosystems are highly dynamic, with organisms exposed to various natural stressors along with productivity clines driven by advection of water masses from shelves. The benthic response to these environmental clines has been extensively studied using traditional, morphology-based approaches mostly focusing on macroinvertebrates. In this study we analyse the effects of glacially mediated disturbance on the biodiversity of benthic macrofauna and meiobenthos (meiofauna and Foraminifera) in a Svalbard fjord by comparing morphology and eDNA metabarcoding. Three genetic markers targeting metazoans (COI), meiofauna (18S V1V2) and Foraminifera (18S 37f) were analyzed. Univariate measures of alpha diversity and multivariate compositional dissimilarities were calculated and tested for similarities in response to environmental gradients using correlation analysis. Our study showed different taxonomic composition of morphological and molecular datasets for both macrofauna and meiobenthos. Some taxonomic groups while abundant in metabarcoding data were almost absent in morphology-based inventory and vice versa. In general, species richness and diversity measures in macrofauna morphological data were higher than in metabarcoding, and similar for the meiofauna. Both methodological approaches showed different patterns of response to the glacially mediated disturbance for the macrofauna and the meiobenthos. Macrofauna showed an evident distinction in taxonomic composition and a dramatic cline in alpha diversity indices between the outer and inner parts of fjord, while the meiobenthos showed a gradual change and more subtle responses to environmental changes along the fjord axis. The two methods can be seen as complementing rather than replacing each other. Morphological approach provides more accurate inventory of larger size species and more reliable quantitative data, while metabarcoding allows identification of inconspicuous taxa that are overlooked in morphology-based studies. As different taxa may show different sensitivities to environmental changes, both methods shall be used to monitor marine biodiversity in Arctic ecosystems and its response to dramatically changing environmental conditions.

Deciphering the impact of decabromodiphenyl ether (BDE-209) on benthic foraminiferal communities: Insights from Cell-Tracker Green staining and eDNA metabarcoding

This study investigates the ecotoxicological effects of BDE-209, a persistent organic pollutant (POP) prevalent in Kuwait's coastal-industrial areas, on benthic foraminiferal communities. We conducted a mesocosm experiment in which we exposed benthic foraminiferal communities sampled from the coastal-industrial areas of Kuwait to a gradient of BDE-209 concentrations (0.01 to 20 mg/kg). The impact of exposure was assessed using live-staining and metabarcoding techniques. Despite the significantly different taxonomic compositions detected by the two techniques, our results show that BDE-209 significantly affects foraminiferal communities, with moderately high concentrations leading to reduced α-diversity and considerable taxonomic shifts in both molecular and morphological assemblages. At concentrations of 10 and 20 mg/kg, no living foraminifera were detected after 8 weeks, suggesting a threshold for their survival under BDE-209 exposure. The parallel responses of molecular and morphological communities confirm the reliability of both assessment methods. This study is the first to investigate the reaction of eukaryotic communities, specifically foraminifera, to POPs such as BDE-209, generating valuable insights that have the potential to enhance field studies and aid the refinement of sediment quality guidelines.

Assessment of the ecological quality status of the Sepetiba Bay (SE Brazil): When metabarcoding meets morphology on foraminifera

In recent years, the region surrounding Sepetiba Bay (SB; SE Brazil) has become a hub of intense urban expansion and economic exploitation in response to ore transport and industrial and port activities. As a result, contaminants have been introduced into the bay, leading to an overall worsening of the environmental quality. The present work applies for the first time a foraminiferal morphology-based approach (M) and eDNA-based metabarcoding sequencing (G), along with geochemical data to assess the ecological quality status (EcoQS) in the SB. Principal component analysis shows that the eDNA and morphospecies diversity as well as most of the taxa relative abundance decline in response to the environmental stress (ES) gradient related to total organic carbon (TOC) and metal pollution. Based on ecological indices, Exp(H'bc) (G), Exp(H'bc) (M), foraminifera ATZI marine biotic index (Foram-AMBI), Foram Stress Index (FSI), and geochemical indices (TOC and Potential Ecological Risk Index), the lowest values of EcoQS (i.e., bad to moderate) are inferred in the innermost part of the SB. Despite minor discrepancies among the six EcoQS indices, an agreement has been found for 63% of the stations. To improve the agreement between the ecological indices, it is necessary to fill the gap in species ecology; information on the ecology of many species is still unknown. This work reinforces the importance of molecular analysis and morphological methods in environmental impact studies and confirms the reliability of foraminiferal metabarcoding in EcoQS assessment. This is the first study evaluating the EcoQS in the South Atlantic by using combined foraminiferal eDNA metabarcoding with morphological data.

Assigning the unassigned: A signature-based classification of rDNA metabarcodes reveals new deep-sea diversity

Environmental DNA metabarcoding reveals a vast genetic diversity of marine eukaryotes. Yet, most of the metabarcoding data remain unassigned due to the paucity of reference databases. This is particularly true for the deep-sea meiofauna and eukaryotic microbiota, whose hidden diversity is largely unexplored. Here, we tackle this issue by using unique DNA signatures to classify unknown metabarcodes assigned to deep-sea foraminifera. We analyzed metabarcoding data obtained from 311 deep-sea sediment samples collected in the Clarion-Clipperton Fracture Zone, an area of potential polymetallic nodule exploitation in the Eastern Pacific Ocean. Using the signatures designed in the 37F hypervariable region of the 18S rRNA gene, we were able to classify 802 unassigned metabarcodes into 61 novel lineages, which have been placed in 27 phylogenetic clades. The comparison of new lineages with other foraminiferal datasets shows that most novel lineages are widely distributed in the deep sea. Five lineages are also present in the shallow-water datasets; however, phylogenetic analysis of these lineages separates deep-sea and shallow-water metabarcodes except in one case. While the signature-based classification does not solve the problem of gaps in reference databases, this taxonomy-free approach provides insight into the distribution and ecology of deep-sea species represented by unassigned metabarcodes, which could be useful in future applications of metabarcoding for environmental monitoring.

Assessing without harvesting: Pros and cons of environmental DNA sampling and image analysis for marine biodiversity evaluation

Marine stock assessments or biodiversity monitoring studies, which historically relied on extractive techniques (e.g., trawl or grab surveys), are being progressively replaced by non-extractive approaches. For instance, species abundance indices can be calculated using data obtained from high-definition underwater cameras that enable to identify taxa at low taxonomical level. In biodiversity studies, environmental DNA (eDNA) has proven to be a useful tool for characterising fish species richness. However, several marine phyla remain poorly represented in reference gene databases or release limited amounts of DNA, restricting their detection. The absence of amplification of some invertebrate taxa might also reflect primer bias. We here explore and compare the performance of eDNA and image data in describing the marine communities of several sites in the Bay of Biscay. This was achieved by deploying a remotely operated vehicle to both record images and collect seawater samples. A total of 88 taxa were identified from the eDNA samples and 121 taxa from the images. For both methods, the best characterised phylum was Chordata, with 29 and 27 Actinopterygii species detected using image versus eDNA, respectively. Neither Bryozoa nor Cnidaria was detected in the eDNA samples while the phyla were easily identifiable by imagery. Similarly, Asteroidea (Echinodermata) and Cephalopoda (Mollusca) were scarcely detected in the eDNA samples but present on the images, while Annelida were mostly identified by eDNA (18 taxa vs 7 taxa from imagery). The complementary community descriptions we highlight from these two methods therefore advocate for using both eDNA and imagery in tandem in order to capture the macroscopic biodiversity of bentho-demersal marine communities.

Encapsulated in sediments: eDNA deciphers the ecosystem history of one of the most polluted European marine sites

The Anthropocene is characterized by dramatic ecosystem changes driven by human activities. The impact of these activities can be assessed by different geochemical and paleontological proxies. However, each of these proxies provides only a fragmentary insight into the effects of anthropogenic impacts. It is highly challenging to reconstruct, with a holistic view, the state of the ecosystems from the preindustrial period to the present day, covering all biological components, from prokaryotes to multicellular eukaryotes. Here, we used sedimentary ancient DNA (sedaDNA) archives encompassing all trophic levels of biodiversity to reconstruct the two century-natural history in Bagnoli-Coroglio (Gulf of Pozzuoli, Tyrrhenian Sea), one of the most polluted marine-coastal sites in Europe. The site was characterized by seagrass meadows and high eukaryotic diversity until the beginning of the 20th century. Then, the ecosystem completely changed, with seagrasses and associated fauna as well as diverse groups of planktonic and benthic protists being replaced by low diversity biota dominated by dinophyceans and infaunal metazoan species. The sedaDNA analysis revealed a five-phase evolution of the area, where changes appear as the result of a multi-level cascade effect of impacts associated with industrial activities, urbanization, water circulation and land-use changes. The sedaDNA allowed to infer reference conditions that must be considered when restoration actions are to be implemented.

VTAM: A robust pipeline for validating metabarcoding data using controls

To obtain accurate estimates for biodiversity and ecological studies, metabarcoding studies should be carefully designed to minimize both false positive (FP) and false negative (FN) occurrences. Internal controls (mock samples and negative controls), replicates, and overlapping markers allow controlling metabarcoding errors but current metabarcoding software packages do not explicitly integrate these additional experimental data to optimize filtering. We have developed the metabarcoding analysis software VTAM, which uses explicitly these elements of the experimental design to find optimal parameter settings that minimize FP and FN occurrences. VTAM showed similar sensitivity, but a higher precision compared to two other pipelines using three datasets and two different markers (COI, 16S). The stringent filtering procedure implemented in VTAM aims to produce robust metabarcoding data to obtain accurate ecological estimates and represents an important step towards a non-arbitrary and standardized validation of metabarcoding data for conducting ecological studies. VTAM is implemented in Python and available from: https://github.com/aitgon/vtam. The VTAM benchmark code is available from: https://github.com/aitgon/vtam_benchmark.

Vertical organization of microbial communities in Salineta hypersaline wetland, Spain

Microbial communities inhabiting hypersaline wetlands, well adapted to the environmental fluctuations due to flooding and desiccation events, play a key role in the biogeochemical cycles, ensuring ecosystem service. To better understand the ecosystem functioning, we studied soil microbial communities of Salineta wetland (NE Spain) in dry and wet seasons in three different landscape stations representing situations characteristic of ephemeral saline lakes: S1 soil usually submerged, S2 soil intermittently flooded, and S3 soil with halophytes. Microbial community composition was determined according to different redox layers by 16S rRNA gene barcoding. We observed reversed redox gradient, negative at the surface and positive in depth, which was identified by PERMANOVA as the main factor explaining microbial distribution. The Pseudomonadota, Gemmatimonadota, Bacteroidota, Desulfobacterota, and Halobacteriota phyla were dominant in all stations. Linear discriminant analysis effect size (LEfSe) revealed that the upper soil surface layer was characterized by the predominance of operational taxonomic units (OTUs) affiliated to strictly or facultative anaerobic halophilic bacteria and archaea while the subsurface soil layer was dominated by an OTU affiliated to Roseibaca, an aerobic alkali-tolerant bacterium. In addition, the potential functional capabilities, inferred by PICRUSt2 analysis, involved in carbon, nitrogen, and sulfur cycles were similar in all samples, irrespective of the redox stratification, suggesting functional redundancy. Our findings show microbial community changes according to water flooding conditions, which represent useful information for biomonitoring and management of these wetlands whose extreme aridity and salinity conditions are exposed to irreversible changes due to human activities.

Metabarcoding reveals high diversity of benthic foraminifera linked to water masses circulation at coastal Svalbard

Arctic marine biodiversity is undergoing rapid changes due to global warming and modifications of oceanic water masses circulation. These changes have been demonstrated in the case of mega- and macrofauna, but much less is known about their impact on the biodiversity of smaller size organisms, such as foraminifera that represent a main component of meiofauna in the Arctic. Several studies analyzed the distribution and diversity of Arctic foraminifera. However, all these studies are based exclusively on the morphological identification of specimens sorted from sediment samples. Here, we present the first assessment of Arctic foraminifera diversity based on metabarcoding of sediment DNA samples collected in fjords and open sea areas in the Svalbard Archipelago. We obtained a total of 5,968,786 reads that represented 1384 amplicon sequence variants (ASVs). More than half of the ASVs (51.7%) could not be assigned to any group in the reference database suggesting a high genetic novelty of Svalbard foraminifera. The sieved and unsieved samples resolved comparable communities, sharing 1023 ASVs, comprising over 97% of reads. Our analyses show that the foraminiferal assemblage differs between the localities, with communities distinctly separated between fjord and open sea stations. Each locality was characterized by a specific assemblage, with only a small overlap in the case of open sea areas. Our study demonstrates a clear pattern of the influence of water masses on the structure of foraminiferal communities. The stations situated on the western coast of Svalbard that are strongly influenced by warm and salty Atlantic water (AW) are characterized by much higher diversity than stations in the northern and eastern part, where the impact of AW is less pronounced. This high diversity and specificity of Svalbard foraminifera associated with water mass distribution indicate that the foraminiferal metabarcoding data can be very useful for inferring present and past environmental conditions in the Arctic.

Shared and contrasting associations in the dynamic nano- and picoplankton communities of two close but contrasting sites from the Bay of Biscay

Pico- and nanoplankton are key players in the marine ecosystems due to their implication in the biogeochemical cycles, nutrient recycling and the pelagic food webs. However, the specific dynamics and niches of most bacterial, archaeal and eukaryotic plankton remain unknown, as well as the interactions between them. Better characterization of these is critical for understanding and predicting ecosystem functioning under anthropogenic pressures. We used environmental DNA metabarcoding across a 6-year time series to explore the structure and seasonality of pico- and nanoplankton communities in two sites of the Bay of Biscay, one coastal and one offshore, and construct association networks to reveal potential keystone and connector taxa. Temporal trends in alpha diversity were similar between the two sites, and concurrent communities more similar than within the same site at different times. However, we found differences between the network topologies of the two sites, with both shared and site-specific keystones and connectors. For example, Micromonas, with lower abundance in the offshore site is a keystone here, indicating a stronger effect of associations such as resource competition. This study provides an example of how time series and association network analysis can reveal how similar communities may function differently despite being geographically close.

APSCALE: advanced pipeline for simple yet comprehensive analyses of DNA Meta-barcoding data

Summary

DNA metabarcoding is an emerging approach to assess and monitor biodiversity worldwide and consequently the number and size of data sets increases exponentially. To date, no published DNA metabarcoding data processing pipeline exists that is (i) platform independent, (ii) easy to use [incl. graphical user interface (GUI)], (iii) fast (does scale well with dataset size) and (iv) complies with data protection regulations of e.g. environmental agencies. The presented pipeline APSCALE meets these requirements and handles the most common tasks of sequence data processing, such as paired-end merging, primer trimming, quality filtering, clustering and denoising of any popular metabarcoding marker, such as internal transcribed spacer, 16S or cytochrome c oxidase subunit I. APSCALE comes in a command line and a GUI version. The latter provides the user with additional summary statistics options and links to GUI-based downstream applications.

Availability and implementation

APSCALE is written in Python, a platform-independent language, and integrates functions of the open-source tools, VSEARCH (Rognes et al., 2016), cutadapt (Martin, 2011) and LULU (Frøslev et al., 2017). All modules support multithreading to allow fast processing of larger DNA metabarcoding datasets. Further information and troubleshooting are provided on the respective GitHub pages for the command-line version (https://github.com/DominikBuchner/apscale) and the GUI-based version (https://github.com/TillMacher/apscale_gui), including a detailed tutorial.

Supplementary information

Supplementary data are available at Bioinformatics online.

Benthic foraminifera as proxies for the environmental quality assessment of the Kuwait Bay (Kuwait, Arabian Gulf): Morphological and metabarcoding approaches

The rapid urbanization and industrialization of Kuwait and the consequent effluent discharges into marine environments have resulted in a degradation of water and sediment quality in the coastal marine ecosystems such as in the Kuwait Bay. This study investigates the ecological response of benthic foraminifera (protists) to environmental stress in the Kuwait Bay. The traditional morphological approach was compared to the innovative environmental DNA (eDNA) metabarcoding to evaluate the ecological quality status (EcoQS). Forty-six surface sediment samples were collected from selected stations in the Kuwait Bay. To detect the pollution gradient, environmental parameters from water (e.g., salinity, pH, dissolved oxygen) and sediment (e.g., grain-size, trace metals, total organic carbon, total petroleum hydrocarbons) were measured at each station. Although the foraminiferal assemblages were different in the morphological and molecular datasets, the species turnover was congruent and statistically significant. Diversity-based biotic indices derived from both morphological and metabarcoding approaches, reflect the environmental stress gradient (i.e., organic and metal contaminations) in the Kuwait Bay. The lowest values of EcoQS (i.e., bad to poor) are found in the innermost part (i.e., Sulaibikhat Bay and Ras Kazmah), while higher EcoQS values occur in the outer part of the bay. This study constitutes the first attempt to apply the foraminiferal metabarcoding to assess the EcoQS within the Arabian Gulf and presents its advantages compared to the conventional morphological approach.

Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem

High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA.

Patterns of eukaryotic diversity from the surface to the deep-ocean sediment

Remote deep-ocean sediment (DOS) ecosystems are among the least explored biomes on Earth. Genomic assessments of their biodiversity have failed to separate indigenous benthic organisms from sinking plankton. Here, we compare global-scale eukaryotic DNA metabarcoding datasets (18S-V9) from abyssal and lower bathyal surficial sediments and euphotic and aphotic ocean pelagic layers to distinguish plankton from benthic diversity in sediment material. Based on 1685 samples collected throughout the world ocean, we show that DOS diversity is at least threefold that in pelagic realms, with nearly two-thirds represented by abundant yet unknown eukaryotes. These benthic communities are spatially structured by ocean basins and particulate organic carbon (POC) flux from the upper ocean. Plankton DNA reaching the DOS originates from abundant species, with maximal deposition at high latitudes. Its seafloor DNA signature predicts variations in POC export from the surface and reveals previously overlooked taxa that may drive the biological carbon pump.

Microbial diversity alteration reveals biomarkers of contamination in soil-river-lake continuum

Microbial communities inhabiting soil-water-sediment continuum in coastal areas provide important ecosystem services. Their adaptation in response to environmental stressors, particularly mitigating the impact of pollutants discharged from human activities, has been considered for the development of microbial biomonitoring tools, but their use is still in the infancy. Here, chemical and molecular (16S rRNA gene metabarcoding) approaches were combined in order to determine the impact of pollutants on microbial assemblages inhabiting the aquatic network of a soil-water-sediment continuum around the Ichkeul Lake (Tunisia), an area highly impacted by human activities. Samples were collected within the soil-river-lake continuum at three stations in dry (summer) and wet (winter) seasons. The contaminant pressure index (PI), which integrates Polycyclic aromatic hydrocarbons (PAHs), alkanes, Organochlorine pesticides (OCPs) and metal contents, and the microbial pressure index microgAMBI, based on bacterial community structure, showed significant correlation with contamination level and differences between seasons. The comparison of prokaryotic communities further revealed specific assemblages for soil, river and lake sediments. Correlation analyses identified potential "specialist" genera for the different compartments, whose abundances were correlated with the pollutant type found. Additionally, PICRUSt analysis revealed the metabolic potential for pollutant transformation or degradation of the identified "specialist" species, providing information to estimate the recovery capacity of the ecosystem. Such findings offer the possibility to define a relevant set of microbial indicators for assessing the effects of human activities on aquatic ecosystems. Microbial indicators, including the detection of "specialist" and sensitive taxa, and their functional capacity, might be useful, in combination with integrative microbial indices, to constitute accurate biomonitoring tools for the management and restoration of complex coastal aquatic systems.

Monitoring newt communities in urban area using eDNA metabarcoding

Newts are amphibians commonly present in small ponds or garden pools in urban areas. They are protected in many countries and their presence is monitored through visual observation and/or trapping. However, newts are not easy to spot as they are small, elusive and often hidden at the bottom of water bodies. In recent years, environmental DNA (eDNA) has become a popular tool for detecting newts, with a focus on individual species using qPCR assays. Here, we assess the effectiveness of eDNA metabarcoding compared to conventional visual surveys of newt diversity in 45 ponds within urban areas of Geneva canton, Switzerland. We designed newt-specific mitochondrial 16S rRNA primers, which assign the majority of amplicons to newts, and were able to detect four species known to be present in the region, including the invasive subspecies Lissotriton vulgaris meridionalis, native to the Italian peninsula, that has been introduced in the Geneva area recently. The obtained eDNA results were congruent overall with conventional surveys, confirming the morphological observations in the majority of cases (67%). In 25% of cases, a species was only detected genetically, while in 8% of cases, the observations were not supported by eDNA metabarcoding. Our study confirms the usefulness of eDNA metabarcoding as a tool for the effective and non-invasive monitoring of newt community and suggests its broader use for the survey of newt diversity in urban area at larger scales.

Assessing the ecological quality status of the highly polluted Bagnoli area (Tyrrhenian Sea, Italy) using foraminiferal eDNA metabarcoding

Morphology-based benthic foraminifera indices are increasingly used worldwide for biomonitoring the ecological quality of marine sediments. The recent development of foraminiferal eDNA metabarcoding offers a reliable, time-, and cost-effective alternative to morphology-based foraminiferal biomonitoring. However, the practical applications of these new tools are still highly limited. In the present study, we evaluate the response of benthic foraminifera and define the ecological quality status (EcoQS) in the Bagnoli area (Tyrrhenian Sea, Italy) based on a traditional morphology-based approach and eDNA metabarcoding. The geochemical data show that several sites in front of the former industrial plant contain higher concentrations of potentially toxic elements than the effect range median and are characterized by the highest total organic carbon (TOC) content, whereas the distantly located sites can be considered relatively low- to unpolluted. Significant differences (i.e., diversity and assemblage composition) in both morphological and molecular datasets were found between the relatively low- to unpolluted and the most polluted areas. Similarly, the selected ecological indices of both morphological and molecular datasets strikingly and congruently resulted in a clear separation following the environmental stress gradient. The molecular indices (i.e., g-exp(H'_bc), g-Foram AMBI, and g-Foram AMBI-MOTUs) reliably identified poor-to-bad EcoQS in the polluted area in front of the former industrial plant. On the other hand, the Foram-AMBI based on morphology well identified an overall trend but seemed to overestimate the EcoQS if the traditional class boundaries were considered. The congruent and complementary trends between morphological and metabarcoding data observed in the case of the Bagnoli site further support the application of foraminiferal metabarcoding in routine biomonitoring to assess the environmental impacts of heavily polluted marine areas.

Microbial community diversity and composition in river sediments contaminated with tetrabromobisphenol A and copper

The microbial community composition in aquatic ecosystems have received increased attention. However, the knowledge gap relative to the responses of bacterial, archaeal and fungal communities in co-contaminated river sediments remain poorly studied. Here, we investigated the changes of tetrabromobisphenol A (TBBPA) and copper (Cu) concentrations and the responses of microbial communities in co-contaminated sediments during long-term incubation. TBBPA concentrations significantly decreased over time, whereas Cu concentrations remained relatively stable over the 60-day incubation. Abundances of the bacterial 16S rRNA, archaeal 16S rRNA and fungal ITS genes ranged from 6.53 × 10⁶ to 1.26 × 10⁹ copies g^-1, 1.12 × 10⁶ to 5.47 × 10⁶ copies g^-1 and 5.33 × 10³ to 7.51 × 10⁴ copies g^-1 in the samples, respectively. A total of 11, 6 and 5 bacterial, archaeal and fungal phyla were identified across all samples. Bacterial, archaeal and fungal communities mainly consisted of members from the phyla Proteobacteria and Acidobacteria, Methanomicrobia and Woesearchaeia as well as Agaricales and Helotiales, respectively. Fungal communities showed a stronger response to pollutant addition after a long incubation compared with bacterial and archaeal communities. The variance analysis results revealed that the bacterial, archaeal and fungal microbial communities of all treatments were distinctly distributed into two separated clusters according to incubation time. However, the three microbial communities did not significantly change in response to pollutant types, which was consistent with variation in relative abundances of the three microbial communities. These findings improve our understanding of the ecotoxicological effects of co-exposure on sediment microbial communities.

Bioinformatic pipelines combining denoising and clustering tools allow for more comprehensive prokaryotic and eukaryotic metabarcoding

Environmental DNA metabarcoding is a powerful tool for studying biodiversity. However, bioinformatic approaches need to adjust to the diversity of taxonomic compartments targeted as well as to each barcode gene specificities. We built and tested a pipeline based on read correction with DADA2 allowing analysing metabarcoding data from prokaryotic (16S) and eukaryotic (18S, COI) life compartments. We implemented the option to cluster amplicon sequence variants (ASVs) into operational taxonomic units (OTUs) with swarm, a network-based clustering algorithm, and the option to curate ASVs/OTUs using LULU. Finally, taxonomic assignment was implemented via the Ribosomal Database Project Bayesian classifier (RDP) and BLAST. We validated this pipeline with ribosomal and mitochondrial markers using metazoan mock communities and 42 deep-sea sediment samples. The results show that ASVs and OTUs describe different levels of biotic diversity, the choice of which depends on the research questions. They underline the advantages and complementarity of clustering and LULU-curation for producing metazoan biodiversity inventories at a level approaching the one obtained using morphological criteria. While clustering removes intraspecific variation, LULU effectively removes spurious clusters, originating from errors or intragenomic variability. Swarm clustering affected alpha and beta diversity differently depending on genetic marker. Specifically, d-values > 1 appeared to be less appropriate with 18S for metazoans. Similarly, increasing LULU's minimum ratio level proved essential to avoid losing species in sample-poor data sets. Comparing BLAST and RDP underlined that accurate assignments of deep-sea species can be obtained with RDP, but highlighted the need for a concerted effort to build comprehensive, ecosystem-specific databases.

TaxonTableTools: A comprehensive, platform-independent graphical user interface software to explore and visualise DNA metabarcoding data

DNA metabarcoding is increasingly used as a tool to assess biodiversity in research and environmental management. Powerful analysis software exists to process raw data. However, the translation of sequence read data into biological information and downstream analyses may be difficult for end users with limited expertise in bioinformatics. Thus, there is a growing need for easy-to-use, graphical user interface (GUI) software to analyse and visualise DNA metabarcoding data. Here, we present TaxonTableTools (TTT), a new platform-independent GUI that aims to fill this gap by providing simple, reproducible analysis and visualisation workflows. At its base, TTT uses a "TaXon table", which is a data format that can be generated easily within TTT from two input files: a read table and a taxonomy table obtained using various published metabarcoding pipelines. TTT analysis and visualisation modules include Venn diagrams to compare taxon overlap among replicates, samples, or analysis methods. TTT analyses and visualises basic statistics, such as read proportion per taxon, as well as more sophisticated visualisations, such as interactive Krona charts for taxonomic data exploration. Various ecological analyses can be produced directly, including alpha or beta diversity estimates, and rarefaction analysis ordination plots. Metabarcoding data can be converted into formats required for traditional, taxonomy-based analyses performed by regulatory bioassessment programs. In addition, TTT is able to produce html-based interactive graphics that can be analysed in any web browser. The software comes with a manual and tutorial, is free and publicly available through GitHub (https://github.com/TillMacher/TaxonTableTools) or the Python package index (https://pypi.org/project/taxontabletools/).

eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA sequences exploiting Nextflow and Singularity

Metabarcoding of environmental DNA (eDNA) when coupled with high throughput sequencing is revolutionising the way biodiversity can be monitored across a wide range of applications. However, the large number of tools deployed in downstream bioinformatic analyses often places a challenge in configuration and maintenance of a workflow, and consequently limits the research reproducibility. Furthermore, scalability needs to be considered to handle the growing amount of data due to increase in sequence output and the scale of project. Here, we describe eDNAFlow, a fully automated workflow that employs a number of state-of-the-art applications to process eDNA data from raw sequences (single-end or paired-end) to generation of curated and noncurated zero-radius operational taxonomic units (ZOTUs) and their abundance tables. This pipeline is based on Nextflow and Singularity which enable a scalable, portable and reproducible workflow using software containers on a local computer, clouds and high-performance computing (HPC) clusters. Finally, we present an in-house Python script to assign taxonomy to ZOTUs based on user specified thresholds for assigning lowest common ancestor (LCA). We demonstrate the utility and efficiency of the pipeline using an example of a published coral diversity biomonitoring study. Our results were congruent with the aforementioned study. The scalability of the pipeline is also demonstrated through analysis of a large data set containing 154 samples. To our knowledge, this is the first automated bioinformatic pipeline for eDNA analysis using two powerful tools: Nextflow and Singularity. This pipeline addresses two major challenges in the analysis of eDNA data; scalability and reproducibility.

DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions

Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.

The Foreign Oligochaete Species Quistadrilus multisetosus (Smith, 1900) in Lake Geneva: Morphological and Molecular Characterization and Environmental Influences on Its Distribution

Simple Summary

The presence of the oligochaete species Quistadrilus multisetosus (Smith, 1900), originating from North America, has been mentioned in Europe for some decades and was recently found in Swiss lakes. Here, we report its repartition and abundance in Lake Geneva based on morphological and eDNA surveys and study its ecology and invasive potential in this lake. We also provide an identification key of this species and two closely related species and describe the phylogenetic position of Q. multisetosus within several Tubificinae lineages based on the cytochrome c oxidase marker. Our results showed that this species was restricted to an area close to the outlet of a wastewater treatment plant and to a combined sewer overflow, was highly tolerant to organic matter pollution and had a limited capacity to disseminate in this lake. Even if the trophic status (oligo-mesotrophic) of Lake Geneva seems unfavorable for the development of this species, we recommend continuing monitoring its presence in this lake in the future, as the current warming of waters could contribute to its expansion.

Abstract

The presence of the oligochaete species Quistadrilus multisetosus (Smith, 1900) originating from North America has been mentioned for several decades in Europe, the Middle East and Russia. Its distribution and abundance in Europe is still unknown but it can be considered as potentially invasive. This species was recently discovered in Lake Geneva (Switzerland/France) and three other Swiss lakes. The aims of the present work are to report its repartition and abundance in Lake Geneva, to study its ecology and to determine its invasive potential in this lake. We also provide an identification key for correctly differentiating Q. multisetosus from the closely related species Spirosperma ferox Eisen, 1879 and Embolocephalus velutinus (Grube, 1879), and study the phylogenetic position of Q. multisetosus within several Tubificinae lineages based on the cytochrome c oxidase (COI) marker. Twenty-eight sites have been monitored since 2009 in Lake Geneva. In several sites, the COI sequence corresponding to this species was also searched for in sediment samples using high-throughput sequencing. In addition, we examined specimens collected in this lake before 2009 likely to belong to Q. multisetosus and to have been misidentified. We found that Q. multisetosus was only present in the lake downstream of a wastewater treatment plant and a combined sewer overflow in the Vidy Bay (near Lausanne) and at a site located nearby. These results confirmed the high tolerance of this species to organic matter pollution. Q. multisetosus was already present in this location in 1974 (misidentified as Spirosperma ferox), which suggests that Q. multisetosus has a limited capacity to disseminate in this lake. However, we recommend continuing monitoring its presence in Lake Geneva in the future, especially in the context of warming of waters that could contribute to the expansion of this species.

Diatom DNA metabarcoding for ecological assessment: Comparison among bioinformatics pipelines used in six European countries reveals the need for standardization

Ecological assessment of lakes and rivers using benthic diatom assemblages currently requires considerable taxonomic expertise to identify species using light microscopy. This traditional approach is also time-consuming. Diatom metabarcoding is a promising alternative and there is increasing interest in using this approach for routine assessment. However, until now, analysis protocols for diatom metabarcoding have been developed and optimised by research groups working in isolation. The diversity of existing bioinformatics methods highlights the need for an assessment of the performance and comparability of results of different methods. The aim of this study was to test the correspondence of outputs from six bioinformatics pipelines currently in use for diatom metabarcoding in different European countries. Raw sequence data from 29 biofilm samples were treated by each of the bioinformatics pipelines, five of them using the same curated reference database. The outputs of the pipelines were compared in terms of sequence unit assemblages, taxonomic assignment, biotic index score and ecological assessment outcomes. The three last components were also compared to outputs from traditional light microscopy, which is currently accepted for ecological assessment of phytobenthos, as required by the Water Framework Directive. We also tested the performance of the pipelines on the two DNA markers (rbcL and 18S-V4) that are currently used by the working groups participating in this study. The sequence unit assemblages produced by different pipelines showed significant differences in terms of assigned and unassigned read numbers and sequence unit numbers. When comparing the taxonomic assignments at genus and species level, correspondence of the taxonomic assemblages between pipelines was weak. Most discrepancies were linked to differential detection or quantification of taxa, despite the use of the same reference database. Subsequent calculation of biotic index scores also showed significant differences between approaches, which were reflected in the final ecological assessment. Use of the rbcL marker always resulted in better correlation among molecular datasets and also in results closer to these generated using traditional microscopy. This study shows that decisions made in pipeline design have implications for the dataset's structure and the taxonomic assemblage, which in turn may affect biotic index calculation and ecological assessment. There is a need to define best-practice bioinformatics parameters in order to ensure the best representation of diatom assemblages. Only the use of similar parameters will ensure the compatibility of data from different working groups. The future of diatom metabarcoding for ecological assessment may also lie in the development of new metrics using, for example, presence/absence instead of relative abundance data.

Planktonic foraminifera eDNA signature deposited on the seafloor remains preserved after burial in marine sediments

Environmental DNA (eDNA) metabarcoding of marine sediments has revealed large amounts of sequences assigned to planktonic taxa. How this planktonic eDNA is delivered on the seafloor and preserved in the sediment is not well understood. We address these questions by comparing metabarcoding and microfossil foraminifera assemblages in sediment cores taken off Newfoundland across a strong ecological gradient. We detected planktonic foraminifera eDNA down to 30 cm and observed that the planktonic/benthic amplicon ratio changed with depth. The relative proportion of planktonic foraminiferal amplicons remained low from the surface down to 10 cm, likely due to the presence of DNA from living benthic foraminifera. Below 10 cm, the relative proportion of planktonic foraminifera amplicons rocketed, likely reflecting the higher proportion of planktonic eDNA in the DNA burial flux. In addition, the microfossil and metabarcoding assemblages showed a congruent pattern indicating that planktonic foraminifera eDNA is deposited without substantial lateral advection and preserves regional biogeographical patterns, indicating deposition by a similar mechanism as the foraminiferal shells. Our study shows that the planktonic eDNA preserved in marine sediments has the potential to record climatic and biotic changes in the pelagic community with the same spatial and temporal resolution as microfossils.

Cascabel: A Scalable and Versatile Amplicon Sequence Data Analysis Pipeline Delivering Reproducible and Documented Results

Marker gene sequencing of the rRNA operon (16S, 18S, ITS) or cytochrome c oxidase I (CO1) is a popular means to assess microbial communities of the environment, microbiomes associated with plants and animals, as well as communities of multicellular organisms via environmental DNA sequencing. Since this technique is based on sequencing a single gene, or even only parts of a single gene rather than the entire genome, the number of reads needed per sample to assess the microbial community structure is lower than that required for metagenome sequencing. This makes marker gene sequencing affordable to nearly any laboratory. Despite the relative ease and cost-efficiency of data generation, analyzing the resulting sequence data requires computational skills that may go beyond the standard repertoire of a current molecular biologist/ecologist. We have developed Cascabel, a scalable, flexible, and easy-to-use amplicon sequence data analysis pipeline, which uses Snakemake and a combination of existing and newly developed solutions for its computational steps. Cascabel takes the raw data as input and delivers a table of operational taxonomic units (OTUs) or Amplicon Sequence Variants (ASVs) in BIOM and text format and representative sequences. Cascabel is a highly versatile software that allows users to customize several steps of the pipeline, such as selecting from a set of OTU clustering methods or performing ASV analysis. In addition, we designed Cascabel to run in any linux/unix computing environment from desktop computers to computing servers making use of parallel processing if possible. The analyses and results are fully reproducible and documented in an HTML and optional pdf report. Cascabel is freely available at Github: https://github.com/AlejandroAb/CASCABEL.

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.

PUMAA: A Platform for Accessible Microbiome Analysis in the Undergraduate Classroom

Improvements in high-throughput sequencing makes targeted amplicon analysis an ideal method for the study of human and environmental microbiomes by undergraduates. Multiple bioinformatics programs are available to process and interpret raw microbial diversity datasets, and the choice of programs to use in curricula is largely determined by student learning goals. Many of the most commonly used microbiome bioinformatics platforms offer end-to-end data processing and data analysis using a command line interface (CLI), but the downside for novice microbiome researchers is the steep learning curve often required. Alternatively, some sequencing providers include processing of raw data and taxonomy assignments as part of their pipelines. This, when coupled with available web-based or graphical user interface (GUI) analysis and visualization tools, eliminates the need for students or instructors to have extensive CLI experience. However, lack of universal data formats can make integration of these tools challenging. For example, tools for upstream and downstream analyses frequently use multiple different data formats which then require writing custom scripts or hours of manual work to make the files compatible. Here, we describe a microbial ecology bioinformatics curriculum that focuses on data analysis, visualization, and statistical reasoning by taking advantage of existing web-based and GUI tools. We created the Program for Unifying Microbiome Analysis Applications (PUMAA), which solves the problem of inconsistent files by formatting the output files from several raw data processing programs to seamlessly transition to a suite of GUI programs for analysis and visualization of microbiome taxonomic and inferred functional profiles. Additionally, we created a series of tutorials to accompany each of the microbiome analysis curricular modules. From pre- and post-course surveys, students in this curriculum self-reported conceptual and confidence gains in bioinformatics and data analysis skills. Students also demonstrated gains in biologically relevant statistical reasoning based on rubric-guided evaluations of open-ended survey questions and the Statistical Reasoning in Biology Concept Inventory. The PUMAA program and associated analysis tutorials enable students and researchers with no computational experience to effectively analyze real microbiome datasets to investigate real-world research questions.

Planktonic foraminifera genomic variations reflect paleoceanographic changes in the Arctic: evidence from sedimentary ancient DNA

Deciphering the evolution of marine plankton is typically based on the study of microfossil groups. Cryptic speciation is common in these groups, and large intragenomic variations occur in ribosomal RNA genes of many morphospecies. In this study, we correlated the distribution of ribosomal amplicon sequence variants (ASVs) with paleoceanographic changes by analyzing the high-throughput sequence data assigned to Neogloboquadrina pachyderma in a 140,000-year-old sediment core from the Arctic Ocean. The sedimentary ancient DNA demonstrated the occurrence of various N. pachyderma ASVs whose occurrence and dominance varied through time. Most remarkable was the striking appearance of ASV18, which was nearly absent in older sediments but became dominant during the last glacial maximum and continues to persist today. Although the molecular ecology of planktonic foraminifera is still poorly known, the analysis of their intragenomic variations through time has the potential to provide new insight into the evolution of marine biodiversity and may lead to the development of new and important paleoceanographic proxies.

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.

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems. However, traditional reliance on morphological identification generally makes it cost-prohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

Dataset of foraminiferal sedimentary DNA (sedDNA) sequences from Svalbard

Environmental DNA (eDNA) is usually defined as genetic material obtained directly from environmental samples, such as soil, water, or ice. Coupled to DNA metabarcoding, eDNA is a powerful tool in biodiversity assessments. Results from eDNA approach provided valuable insights to the studies of past and contemporary biodiversity in terrestrial and aquatic environments. However, the state and fate of eDNA are still investigated and the knowledge about the form of eDNA (i.e., extracellular vs. intracellular) or the DNA degradation under different environmental conditions is limited. Here, we tackle this issue by analyzing foraminiferal sedimentary DNA (sedDNA) from different size fractions of marine sediments: >500 µm, 500–100 µm, 100–63 µm, and < 63 µm. Surface sediment samples were collected at 15 sampling stations located in the Svalbard archipelago. Sequences of the foraminifera-specific 37f region were generated using Illumina technology. The presented data may be used as a reference for a wide range of eDNA-based studies, including biomonitoring and biodiversity assessments across time and space.

High-throughput DNA barcoding of oligochaetes for abundance-based indices to assess the biological quality of sediments in streams and lakes

Aquatic oligochaete communities are valuable indicators of the biological quality of sediments in streams and lakes, but identification of specimens to the species level based on morphological features requires solid expertise in taxonomy and is possible only for a fraction of specimens present in a sample. The identification of aquatic oligochaetes using DNA barcodes would facilitate their use in biomonitoring and allow a wider use of this taxonomic group for ecological diagnoses. Previous approaches based on DNA metabarcoding of samples composed of total sediments or pools of specimens have been proposed for assessing the biological quality of ecosystems, but such methods do not provide precise information on species abundance, which limits the value of resulting ecological diagnoses. Here, we tested how a DNA barcoding approach based on high-throughput sequencing of sorted and genetically tagged specimens performed to assess oligochaete species diversity and abundance and the biological quality of sediments in streams and lakes. We applied both molecular and morphological approaches at 13 sites in Swiss streams and at 7 sites in Lake Geneva. We genetically identified 33 or 66 specimens per site. For both approaches, we used the same index calculations. We found that the ecological diagnoses derived from the genetic approach matched well with those of the morphological approach and that the genetic identification of only 33 specimens per site provided enough ecological information for correctly estimating the biological quality of sediments in streams and lakes.

FACEPAI: a script for fast and consistent environmental DNA processing and identification

Background

The use of environmental DNA (eDNA) has become an increasing important tool in environmental surveys and taxonomic research. High throughput sequencing of samples from soil, water, sediment, trap alcohol or bulk samples generate large amount of barcode sequences that can be assigned to a known taxon with a reference sequence. This process can however be bioinformatic cumbersome and time consuming, especially for researchers without specialised bioinformatic training. A number of different software packages and pipelines are available, but require training in preparation of data, running of analysis and formatting results. Comparison of results produced by different packages are often difficult.

Results

FACEPIE is an open source script dependant on a few open source applications that provides a pipeline for rapid analysis and taxonomic assignment of environmental DNA samples. It requires an initial formatting of a reference database, using the script CaPReSe, and a configuration file and can thereafter be run to process any number of samples in succession using the same settings and references. Both configuration and executing are designed to demand as little hands on work as possible, while assuring repeatable results.

Conclusion

The demonstration using example data from real environmental samples provides results in a time span ranging from less than 3 min to just above 15 min depending on the numbers of sequences to process. The memory usage is below 2 GB on a desktop PC. FACEPAI and CaPReSe provides a pipeline for analysing a large number of eDNA samples on common equipment, with little bioinformatic skills necessary, for subsequent ecological and taxonomical studies.