Measuring the state of aquatic environments using eDNA-upscaling spatial resolution of biotic indices.

Aquatic macroinvertebrates, including many aquatic insect orders, are a diverse and ecologically relevant organismal group yet they are strongly affected by anthropogenic activities. As many of these taxa are highly sensitive to environmental change, they offer a particularly good early warning system for human-induced change, thus leading to their intense monitoring. In aquatic ecosystems there is a plethora of biotic monitoring or biomonitoring approaches, with more than 300 assessment methods reported for freshwater taxa alone. Ultimately, monitoring of aquatic macroinvertebrates is used to calculate ecological indices describing the state of aquatic systems. Many of the methods and indices used are not only hard to compare, but especially difficult to scale in time and space. Novel DNA-based approaches to measure the state and change of aquatic environments now offer unprecedented opportunities, also for possible integration towards commonly applicable indices. Here, we first give a perspective on DNA-based approaches in the monitoring of aquatic organisms, with a focus on aquatic insects, and how to move beyond traditional point-based biotic indices. Second, we demonstrate a proof-of-concept for spatially upscaling ecological indices based on environmental DNA, demonstrating how integration of these novel molecular approaches with hydrological models allows an accurate evaluation at the catchment scale. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Environmental DNA: The next chapter.

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well-studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land-mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer-reviewed literature with a survey of eDNA users including academics, end-users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever-increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward.

A combination of machine-learning and eDNA reveals the genetic signature of environmental change at the landscape levels.

The current advances of environmental DNA (eDNA) bring profound changes to ecological monitoring and provide unique insights on the biological diversity of ecosystems. The very nature of eDNA data is challenging yet also revolutionizing how biological monitoring information is analysed. In particular, new metrics and approaches should take full advantage of the extent and detail of molecular data produced by genetic methods. In this perspective, machine learning algorithms are particularly promising as they can capture complex relationships between the multiple environmental pressures and the diversity of biological communities. We investigated the potential of a new generation of biomonitoring tools that implement machine-learning techniques to fully exploit eDNA datasets. We trained a machine learning model to discriminate between reference and impacted communities of freshwater macroinvertebrates and assessed its performances using a large eDNA dataset collected at 64 standard federal monitoring sites across Switzerland. We show that a model trained on eDNA is significantly better than a naive model and performs similarly to a model trained on traditional data. Our proof-of-concept shows that such a combination of eDNA and machine learning approaches has the potential to complement or even replace traditional environmental monitoring, and could be scaled along temporal or spatial dimensions.

Management of DNA reference libraries for barcoding and metabarcoding studies with the R package refdb.

DNA barcoding and metabarcoding are revolutionizing the study and survey of biodiversity. In order to assign taxonomic labels to the DNA sequence data retrieved, these methods are strongly dependent on comprehensive and accurate reference databases. Producing reliable databases linking biological sequences and taxonomic data can be-and often has been-done using mainstream tools such as spreadsheet software. However, spreadsheets quickly become insufficient when the amount of data increases to thousands of taxa and sequences to be matched, and validation operations become more complex and are error prone if done in a manual way. Thus, there is a clear need for providing scientists with user-friendly, reliable and powerful tools to manipulate and manage DNA reference databases in tractable, sound and efficient ways. Here, we introduce the R package refdb as an environment for semi-automatic and assisted construction of DNA reference libraries. The refdb package is a reference database manager offering a set of powerful functions to import, organize, clean, filter, audit and export the data. It is broadly applicable in metabarcoding data generally obtained in biodiversity and biomonitoring studies. We present the main features of the package and outline how refdb can speed up reference database generation, management and handling, and thus contribute to standardization and repeatability in barcoding and metabarcoding studies.

Navigating the seven challenges of taxonomic reference databases in metabarcoding analyses.

Assessment of biodiversity using metabarcoding data, such as from bulk or environmental DNA sampling, is becoming increasingly relevant in ecology, biodiversity sciences and monitoring. Thereby, the taxonomic identification of species from their DNA sequences relies strongly on reference databases that link genetic sequences to taxonomic names. These databases vary in completeness and availability, depending on the taxonomic group studied and the genetic region targeted. The incompleteness of reference databases is an important argument to explain the nondetection by metabarcoding of species supposedly present. However, there exist further and generally overlooked problems with reference databases that can lead to false or inaccurate inferences of taxonomic assignment. Here, we synthesize all possible problems inherent to reference databases. In particular, we identify a complete, mutually nonexclusive list of seven classes of challenges when it comes to selecting, developing and using a reference database for taxonomic assignment. These are: (i) mislabelling, (ii) sequencing errors, (iii) sequence conflict, (iv) taxonomic conflict, (v) low taxonomic resolution, (vi) missing taxa and (vii) missing intraspecific variants. For each problem identified, we provide a description of possible consequences on the taxonomic assignment process. We illustrate the respective problem with examples taken from the literature or obtained by quantitative analyses of public databases, such as GenBank or BOLD. Finally, we discuss possible solutions to the identified problems and how to navigate them. Only by raising users' awareness of the limitations of metabarcoding data and DNA reference databases will adequate interpretations of these data be achieved.

Paleoreconstructions of ciliate communities reveal long-term ecological changes in temperate lakes.

Ciliates are unicellular heterotrophic organisms that play a key role in aquatic planktonic and benthic food webs. Advances in sedimentary DNA (sed-DNA) analysis offer the possibility to integrate these bioindicators in paleoenvironmental reconstructions. In this study, we used the top-bottom paleolimnological approach and metabarcoding techniques applied to sed-DNA to compare the recent and past (i.e. prior to major anthropogenic impacts) ciliate communities of 48 lakes located along an elevation gradient. Our results show an overall decline in the ß-diversity in recent time, especially in lowland lakes, which are more strongly exposed to local human pressures. Analyses of the functional groups indicate important restructuration of the food web, including the recent increase in mixotrophs. Moreover, changes in the benthic ciliates were consistent with the widespread increase in deep water anoxia. Our results provided evidence that sed-DNA can uncover information about past ciliate communities on a wide variety of lakes. Overall, our study demonstrates the potential of using ciliates as new paleoindicators, integrating information from the pelagic to the benthic zones, and providing valuable insights into ecosystem functioning through a trait-based functional community approach. As paleoindicator, they thus offer a more holistic view on the long-term changes of aquatic ecosystems.

Meta-analysis shows both congruence and complementarity of DNA and eDNA metabarcoding to traditional methods for biological community assessment.

DNA metabarcoding is increasingly used for the assessment of aquatic communities, and numerous studies have investigated the consistency of this technique with traditional morpho-taxonomic approaches. These individual studies have used DNA metabarcoding to assess diversity and community structure of aquatic organisms both in marine and freshwater systems globally over the last decade. However, a systematic analysis of the comparability and effectiveness of DNA-based community assessment across all of these studies has hitherto been lacking. Here, we performed the first meta-analysis of available studies comparing traditional methods and DNA metabarcoding to measure and assess biological diversity of key aquatic groups, including plankton, microphytobentos, macroinvertebrates, and fish. Across 215 data sets, we found that DNA metabarcoding provides richness estimates that are globally consistent to those obtained using traditional methods, both at local and regional scale. DNA metabarcoding also generates species inventories that are highly congruent with traditional methods for fish. Contrastingly, species inventories of plankton, microphytobenthos and macroinvertebrates obtained by DNA metabarcoding showed pronounced differences to traditional methods, missing some taxa but at the same time detecting otherwise overseen diversity. The method is generally sufficiently advanced to study the composition of fish communities and replace more invasive traditional methods. For smaller organisms, like macroinvertebrates, plankton and microphytobenthos, DNA metabarcoding may continue to give complementary rather than identical estimates compared to traditional approaches. Systematic and comparable data collection will increase the understanding of different aspects of this complementarity, and increase the effectiveness of the method and adequate interpretation of the results.

DNA metabarcoding reveals differences in distribution patterns and ecological preferences among genetic variants within some key freshwater diatom species.

Our study evaluates differences in the distribution and ecology of genetic variants within several ecologically important diatom species that are also key for Water Framework Directive monitoring of European rivers: Fistulifera saprophila (FSAP), Achnanthidium minutissimum (ADMI), Nitzschia inconspicua (NINC) and Nitzschia soratensis (NSTS). We used DADA2 to infer amplicon sequence variants (ASVs) of a short rbcL barcode in 531 environmental samples from biomonitoring campaigns in Catalonia and France. ASVs within each species showed different distribution patterns. Threshold Indicator Taxa ANalysis revealed three ecological groupings of ASVs in both ADMI and FSAP. Two of these in each species were separated by opposite responses to calcium and conductivity. Boosted regression trees additionally showed that both variables greatly influenced the occurrence of these groupings. A third grouping in FSAP was characterized by a negative response to total organic carbon and hence was better represented in waters with higher ecological status than the other FSAP ASVs, contrasting with what is generally assumed for the species. In the two Nitzschia species, our analyses confirmed earlier studies: NINC preferred higher levels of calcium and conductivity. Our findings suggest that the broad ecological tolerance of some diatom species results from overlapping preferences among genetic variants, which individually show much more restricted preferences and distributions. This work shows the importance of studying the ecological preferences of genetic variants within species complexes, now possible with DNA metabarcoding. The results will help reveal and understand biogeographical distributions and facilitate the development of more accurate biological indexes for biomonitoring programmes.

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.

Assessing the response of micro-eukaryotic diversity to the Great Acceleration using lake sedimentary DNA.

Long-term time series have provided evidence that anthropogenic pressures can threaten lakes. Yet it remains unclear how and the extent to which lake biodiversity has changed during the Anthropocene, in particular for microbes. Here, we used DNA preserved in sediments to compare modern micro-eukaryotic communities with those from the end of the 19th century, i.e., before acceleration of the human imprint on ecosystems. Our results obtained for 48 lakes indicate drastic changes in the composition of microbial communities, coupled with a homogenization of their diversity between lakes. Remote high elevation lakes were globally less impacted than lowland lakes affected by local human activity. All functional groups (micro-algae, parasites, saprotrophs and consumers) underwent significant changes in diversity. However, we show that the effects of anthropogenic changes have benefited in particular phototrophic and mixotrophic species, which is consistent with the hypothesis of a global increase of primary productivity in lakes.

Community phylogenetic structure reveals the imprint of dispersal-related dynamics and environmental filtering by nutrient availability in freshwater diatoms.

Despite important progress, uncertainty persists regarding the ecological forces driving microbial community assembly. Here, we present the first study to use phylogenetic information to interpret the structure and diversity of diatom communities. We examined local phylogenetic divergence and beta- phylogenetic diversity in a large dataset of 595 freshwater benthic diatom communities and we investigated how this diversity is influenced by gradients in nutrients, pH, organic matter and catchment size. Overall, we found that diatom communities were phylogenetically clustered, i.e. species within communities were more closely related than expected by chance. Phylogenetic clustering was stronger in nutrient-poor environments and in sites with a small catchment area. The variation of the phylogenetic beta-diversity index was much better explained by space and environment than the variation of the taxonomic index was. Both approaches detected a significant effect of environment and space on diatom community turnover. Our results support the view that diatom communities are primarily shaped by environmental filtering, in particular by nutrient availability. Moreover, they highlight the importance of considering dispersal-related processes and the depth of phylogenetic signal in functional traits when interpreting patterns of diversity.

Connecting the morphological and molecular species concepts to facilitate species identification within the genus Fragilaria (Bacillariophyta).

This paper explores the diversity and taxonomy of species within Fragilaria sensu stricto, an abundant and ecologically important diatom genus, taking advantage of cultured and DNA-barcoded material. The goal is to facilitate the identification of European taxa within this complex, providing a unified view on morphological and molecular diversity. There is a general agreement that the separation of species within the group of Fragilaria is difficult because morphological descriptions of species are not consistent between authorities, ongoing taxonomic revisions have resulted in species described with standards of the late 20th and 21st centuries alongside descriptions based on 19th century (light microscopical) criteria, and because not all diagnostic characters can be seen in all specimens encountered in routine analyses. Consequent confusion could blur potentially important ecological distinctions between species. Our study demonstrated that some species defined on morphological criteria could be confirmed using the rbcL chloroplast gene as a genetic marker, for example, Fragilaria gracilis, Fragilaria tenera, Fragilaria perminuta, and Fragilaria subconstricta. However, even for those species, preliminary identifications based on morphology often differed from identifications based on phylogenetic clustering combined with detailed morphological study. Clades were well-defined by rbcL, but based on morphology, the terminal taxa of these clades did not match the currently described Fragilaria species. To clarify recognition of these taxa, we describe three new species: Fragilaria agnesiae, Fragilaria heatherae, and Fragilaria joachimii.

Benthic Diatom Communities in an Alpine River Impacted by Waste Water Treatment Effluents as Revealed Using DNA Metabarcoding.

Freshwater ecosystems are continuously affected by anthropogenic pressure. One of the main sources of contamination comes from wastewater treatment plant (WWTP) effluents that contain wide range of micro- and macropollutants. Chemical composition, toxicity levels and impact of treated effluents (TEs) on the recipient aquatic ecosystems may strongly differ depending on the wastewater origin. Compared to urban TEs, hospital ones may contain more active pharmaceutical substances. Benthic diatoms are relevant ecological indicators because of their high species and ecological diversity and rapid response to human pressure. They are routinely used for water quality monitoring. However, there is a knowledge gap on diatom communities' development and behavior in treated wastewater in relation to prevailing micro- and macropollutants. In this study, we aim to (1) investigate the response of diatom communities to urban and hospital TEs, and (2) evaluate TEs effect on communities in the recipient river. Environmental biofilms were colonized in TEs and the recipient river up- and downstream from the WWTP output to study benthic diatoms using DNA metabarcoding combined with high-throughput sequencing (HTS). In parallel, concentrations of nutrients, pharmaceuticals and seasonal conditions were recorded. Diatom metabarcoding showed that benthic communities differed strongly in their diversity and structure depending on the habitat. TE sites were generally dominated by few genera with polysaprobic preferences belonging to the motile guild, while river sites favored diverse communities from oligotrophic and oligosaprobic groups. Seasonal changes were visible to lower extent. To categorize parameters important for diatom changes we performed redundancy analysis which suggested that communities within TE sites were associated to higher concentrations of beta-blockers and non-steroidal anti-inflammatory drugs in urban effluents vs. antibiotics and orthophosphate in hospital effluents. Furthermore, indicator species analysis showed that 27% of OTUs detected in river downstream communities were indicator for urban or hospital TE sites and were absent in the river upstream. Finally, biological diatom index (BDI) calculated to evaluate the ecological status of the recipient river suggested water quality decrease linked to the release of TEs. Thus, in-depth assessment of diatom community composition using DNA metabarcoding is proposed as a promising technique to highlight the disturbing effect of pollutants in Alpine rivers.

Boosting DNA metabarcoding for biomonitoring with phylogenetic estimation of operational taxonomic units' ecological profiles.

DNA metabarcoding has been introduced as a revolutionary way to identify organisms and monitor ecosystems. However, the potential of this approach for biomonitoring remains partially unfulfilled because a significant part of the sampled DNA cannot be affiliated to species due to incomplete reference libraries. Thus, biotic indices, which are based on the estimated abundances of species in a community and their ecological profiles, can be inaccurate. We propose to compute biotic indices using phylogenetic imputation of operational taxonomic units (OTUs') ecological profiles (OTU-PITI approach). First, OTUs sequences are inserted within a reference phylogeny. Second, OTUs' ecological profiles are estimated on the basis of their phylogenetic relationships with reference species whose ecology is known. Based on these ecological profiles, biotic indices can be computed using all available OTUs. Using freshwater diatoms as a case study, we show that short DNA barcodes can be placed accurately within a phylogeny and their ecological preferences estimated with a satisfactory level of precision. In the light of these results, we tested the approach with a data set of 139 environmental samples of benthic river diatoms for which the same biotic index (specific sensitivity index) was calculated using (a) traditional microscopy, (b) OTUs with taxonomic assignment approach, (c) OTUs with phylogenetic estimation of ecological profiles (OTU-PITI) and (d) OTU with taxonomic assignment completed by the phylogenetic approach (OTU-PITI) for unclassified OTUs. Using traditional microscopy as a reference, we found that the combination of the OTUs' taxonomic assignment completed by the phylogenetic method performed satisfactorily and substantially better than the other methods tested.

River biofilm community changes related to pharmaceutical loads emitted by a wastewater treatment plant.

Wastewater treatment plants (WWTP) are the main sources of a broad spectrum of pharmaceuticals found in freshwater ecosystems. These pollutants raise environmental health concerns because of their highly bioactive nature and their chronic releases. Despite this, pharmaceuticals' effects on aquatic environments are poorly defined. Biofilms represent a major part of the microbial life in rivers and streams. They can drive key metabolic cycles and their organizations reflect exposures to changing chemical, physical, and biological constraints. This study estimated the concentrations, over a 3-year period, of ten pharmaceuticals and five nutrients in a river contaminated by a conventional WWTP fed by urban and hospital wastewaters. Variations in these concentrations were related to biofilm bacterial community dynamics. Rock biofilms had developed over defined periods and were harvested at four locations in the river from the up- and downstream WWTP discharge point. Pharmaceuticals were found in all locations in concentrations ranging from not being detected to 192 ng L-1. Despite the high dilution factor of the WWTP effluents by the receiving river, pharmaceuticals were found more concentrated downstream than upstream the WWTP. Shifts in bacterial community structures linked to the environmental emission of pharmaceuticals were superior to seasonal community changes. A community structure from a site located downstream but close to the WWTP was more strongly associated with high pharmaceutical loads and different from those of biofilm samples from the WWTP upstream or far downstream sites. These latter sites were more strongly associated with high nutrient contents. Low environmental concentrations of pharmaceuticals can thus be transferred from WWTP effluents to a connected stream and induce bacterial aquatic community changes over time.

Can we predict diatoms herbicide sensitivities with phylogeny? Influence of intraspecific and interspecific variability.

Diatoms are used as indicators of freshwater ecosystems integrity. Developing diatom-based tools to assess impact of herbicide pollution is expected by water managers. But, defining sensitivities of all species to multiple herbicides would be unattainable. The existence of a phylogenetic signal of herbicide sensitivity was shown among diatoms and should enable prediction of new species sensitivity. However, diatoms present a cryptic diversity that may lead to variation in their sensitivity to herbicides that would need to be taken into account. Using bioassays, the sensitivity to four herbicides (Atrazine, Terbutryn, Diuron, Isoproturon) was evaluated for 11 freshwater diatom taxa and intraspecific variability was assessed for two of them (Nitzschia palea and Achnanthidium spp.). Intraspecific variability of herbicide sensitivity was always smaller than interspecific variability, but intraspecific variability was more important in N. palea than in Achnanthidium spp. Indeed, one species showed no intraspecific phylogenetic signal (N. palea) whereas the other did (Achnanthidium spp.). On one hand, species boundaries are not set properly for Achnanthidium spp. which encompass several taxa. On the other hand, there is a higher phenotypic plasticity for N. palea. Finally, a phylogenetic signal of herbicide sensitivity was measured at the interspecific level, opening up prospects for setting up reliable biomonitoring tools based on sensitivity prediction, insofar as species boundaries are correctly defined.

Phylogenetic signal in diatom ecology: perspectives for aquatic ecosystems biomonitoring.

Diatoms include a great diversity of taxa and are recognized as powerful bioindicators in rivers. However using diatoms for monitoring programs is costly and time consuming because most of the methodologies necessitate species-level identification. This raises the question of the optimal trade-off between taxonomic resolution and bioassessment quality. Phylogenetic tools may form the bases of new, more efficient approaches for biomonitoring if relationships between ecology and phylogeny can be demonstrated. We estimated the ecological optima of 127 diatom species for 19 environmental parameters using count data from 2119 diatom communities sampled during eight years in eastern France. Using uni- and multivariate analyses, we explored the relationships between freshwater diatom phylogeny and ecology (i.e., the phylogenetic signal). We found a significant phylogenetic signal for many of the ecological optima that were tested, but the strength of the signal varied significantly from one trait to another. Multivariate analysis also showed that the multidimensional ecological niche of diatoms can be strongly related to phylogeny. The presence of clades containing species that exhibit homogeneous ecology suggests that phylogenetic information can be useful for aquatic biomonitoring. This study highlights the presence of significant patterns of ecological optima for freshwater diatoms in relation to their phylogeny. These results suggest the presence of a signal above the species level, which is encouraging for the development of simplified methods for biomonitoring survey.

phylosignal: an R package to measure, test, and explore the phylogenetic signal.

Phylogenetic signal is the tendency for closely related species to display similar trait values as a consequence of their phylogenetic proximity. Ecologists and evolutionary biologists are becoming increasingly interested in studying the phylogenetic signal and the processes which drive patterns of trait values in the phylogeny. Here, we present a new R package, phylosignal which provides a collection of tools to explore the phylogenetic signal for continuous biological traits. These tools are mainly based on the concept of autocorrelation and have been first developed in the field of spatial statistics. To illustrate the use of the package, we analyze the phylogenetic signal in pollution sensitivity for 17 species of diatoms.

R-Syst::diatom: an open-access and curated barcode database for diatoms and freshwater monitoring.

Diatoms are micro-algal indicators of freshwater pollution. Current standardized methodologies are based on microscopic determinations, which is time consuming and prone to identification uncertainties. The use of DNA-barcoding has been proposed as a way to avoid these flaws. Combining barcoding with next-generation sequencing enables collection of a large quantity of barcodes from natural samples. These barcodes are identified as certain diatom taxa by comparing the sequences to a reference barcoding library using algorithms. Proof of concept was recently demonstrated for synthetic and natural communities and underlined the importance of the quality of this reference library. We present an open-access and curated reference barcoding database for diatoms, called R-Syst::diatom, developed in the framework of R-Syst, the network of systematic supported by INRA (French National Institute for Agricultural Research), see http://www.rsyst.inra.fr/en. R-Syst::diatom links DNA-barcodes to their taxonomical identifications, and is dedicated to identify barcodes from natural samples. The data come from two sources, a culture collection of freshwater algae maintained in INRA in which new strains are regularly deposited and barcoded and from the NCBI (National Center for Biotechnology Information) nucleotide database. Two kinds of barcodes were chosen to support the database: 18S (18S ribosomal RNA) and rbcL (Ribulose-1,5-bisphosphate carboxylase/oxygenase), because of their efficiency. Data are curated using innovative (Declic) and classical bioinformatic tools (Blast, classical phylogenies) and up-to-date taxonomy (Catalogues and peer reviewed papers). Every 6 months R-Syst::diatom is updated. The database is available through the R-Syst microalgae website (http://www.rsyst.inra.fr/) and a platform dedicated to next-generation sequencing data analysis, virtual_BiodiversityL@b (https://galaxy-pgtp.pierroton.inra.fr/). We present here the content of the library regarding the number of barcodes and diatom taxa. In addition to these information, morphological features (e.g. biovolumes, chloroplasts…), life-forms (mobility, colony-type) or ecological features (taxa preferenda to pollution) are indicated in R-Syst::diatom. Database URL: http://www.rsyst.inra.fr/.

Separate treatment of hospital and urban wastewaters: A real scale comparison of effluents and their effect on microbial communities.

Hospital wastewaters (HWW) contain wider spectrum and higher quantity of pharmaceuticals than urban wastewaters (UWW), but they are generally discharged in sewers without pretreatment. Since traditional urban wastewater treatment plants (WWTP) are not designed to treat HWWs, treated effluents may still contain pollutants that could impair receiving aquatic environments. Hence, a better understanding of the effect of pharmaceuticals in the environment is required. Biofilms are effective "biological sensors" for assessing the environmental effects of pharmaceuticals due to their ability to respond rapidly to physical, chemical and biological fluctuations by changes in their structure and composition. This study evaluated the efficiency of biological treatment with conventional activated sludge system performed parallel on HWW and UWW. Furthermore, six successive monthly colonizations of biofilms were done on autoclaved stones, placed in grid-baskets in the hospital treated effluents (HTE) and urban treated effluents (UTE). The biomass of these biofilms as well as the structure and diversity of their bacterial communities were investigated. Results showed better treatment efficiency for phosphate and nitrite/nitrate during the treatment of UWW. Pharmaceuticals from all investigated therapeutic classes (beta-blockers, nonsteroidal anti-inflammatory drugs, antibiotics, analgesics and anticonvulsants) were efficiently removed, except for carbamazepine. The removal efficiency of the antibiotics, NSAIDs and beta-blockers was higher during the treatment of HWW. HTE and UTE shaped the bacterial communities in different ways. Higher concentrations of pharmaceuticals in the HTE caused adapted development of the microbial community, leading to less developed biomass and lower bacterial diversity. Seasonal changes in solar irradiance and temperature, caused changes in the community composition of biofilms in both effluents. According to the removal efficiency of pharmaceuticals, the separate treatment was beneficial. However, their high concentrations in the HTE and the following adaptations of biofilm communities identify the importance of adapting wastewater treatment to specific hospital pollutants.