Assessing the relevance of DNA metabarcoding compared to morphological identification for lake phytoplankton monitoring.

Phytoplankton is a key biological group used to assess the ecological status of lakes. The classical monitoring approach relies on microscopic identification and counting of phytoplankton species, which is time-consuming and requires high taxonomic expertise. High-throughput sequencing, combined with metabarcoding, has recently demonstrated its potential as an alternative approach for plankton surveys. Several studies have confirmed the relevance of the diatom metabarcoding approach to calculate biotic indices based on species ecology. However, phytoplankton communities have not yet benefited from such validation. Here, by comparing the results obtained with the two methods (molecular and microscopic counting), we evaluated the relevance of metabarcoding approach for phytoplankton monitoring by considering different metrics: alpha diversity, taxonomic composition, community structure and a phytoplankton biotic index used to assess the trophic level of lakes. For this purpose, 55 samples were collected in four large alpine lakes (Aiguebelette, Annecy, Bourget, Geneva) during the year 2021. For each sample, a metabarcoding analysis based on two genetic markers (16S and 23S rRNA) was performed, in addition to the microscopic count. Regarding the trophic level of lakes, significant differences were found between index values obtained with the two approaches. The main hypothesis to explain these differences comes from the incompleteness, particularly at the species level, of the barcode reference library for the two genetic markers. It is therefore necessary to complete reference libraries for using such species-based biotic indices with metabarcoding data. Besides this, species richness and diversity were higher in the molecular inventories than in the microscopic ones. Moreover, despite differences in taxonomic composition of the floristic lists obtained by the two approaches, their community structures were similar. These results support the possibility of using metabarcoding for phytoplankton monitoring but in a different way. We suggest exploring alternative approaches to index development, such as a taxonomy-free approach.

Physico-chemical and high frequency monitoring dataset from mesocosm experiments simulating extreme climate events in lakes.

We present two datasets composed of high frequency sensors data, vertical in situ profiles and laboratory chemical analysis data, acquired during two different aquatic mesocosm experiments performed at the OLA ("Long-term observation and experimentation for lake ecosystems") facility at the UMR CARRTEL in Thonon les Bains, on the French shore of Lake Geneva. The DOMLAC experiment lasted 3 weeks (4-21 October 2021) and aimed to simulate predicted climate scenarios (i.e. extreme events such as storms and floods) by reproducing changes in quality and composition of lake subsidies and runoff by increased inputs of terrestrial organic matter. The PARLAC experiment lasted 3 weeks (5-23 September 2022) and aimed to simulate turbid storms by light reduction. The experimental setup consisted of nine inland polyester laminated tanks (2.1 m length, 2.1 m width and 1.1 m depth) with a total volume of approximately 4000 L and filled with water directly supplied from the lake at 4m depth. Both experimental design included three treatments each replicated three times. The DOMLAC experiment involved a control treatment (no treatment applied) and two treatments simulating allochthonous inputs from two different dissolved organic matter (DOM) extract from peat moss Sphagnum sp. (Peat-Moss treatment) and Phragmites australis (Phragmite treatment). The PARLAC experiment involved a control treatment (no treatment applied) and two treatments simulating two different intensity of light reduction. In the Medium treatment transmitted light was reduced to 70% and in the High treatment transmitted light was reduced to 15%. The datasets are composed of: 1. In situ measures from automated data loggers of temperature, conductivity, dissolved oxygen and CO2 acquired every 5 minutes at 0.1, 0.5 and 1 m depth (DOMLAC) and 0.5m (PARLAC) for the entire period of the experiment. 2. In situ profiles (0-1 m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation) acquired twice a week during the experiment. 3. In situ measures of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken in the air and at 0, 0.5 and 1 m twice a week on the same day of the profiles at point 2. 4. Laboratory chemical analysis of integrated samples taken twice a week on the same day of the in situ profiles at point 2 and 3 of conductivity, pH, total alkalinity, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total and particulate organic carbon (TOC, POC), Ca, K, Mg, Na, Cl, SO4 and SiO2. Only for DOMLAC also analyses of NH4, NO2 and dissolved organic carbon (DOC). 5. Laboratory analysis of pigments (Chla, Chlc, carotenoids, phaeopigments) extracted from samples collected at point 4. 6. Only for DOMLAC, specific absorbance on the range 600-200nm of DOM (i.e. <0.7 µm) measured on samples collected at point 4. This dataset aims to contribute our understanding of how extreme climate events can alter lake subsidies and affect the regulation of ecosystem processes such as production, respiration, nutrient uptake and pigment composition. The data can be used for a wide range of applications as being included in meta-analysis aiming at generalising the effect of climate change on large lakes including simulating future scenarios in a broad range of geographical areas as we used different inputs of DOM leached from litters reproducing catchments characteristics typical of different latitudes, such as mostly dominated by large leaf forests and phragmites at middle latitude, and coniferous forests rich of peat mosses that spread along the water surface typical of Northern regions.

Spatio-temporal variability of eDNA signal and its implication for fish monitoring in lakes.

Environmental DNA (eDNA) metabarcoding is revolutionizing the monitoring of aquatic biodiversity. The use of eDNA has the potential to enable non-invasive, cost-effective, time-efficient and high-sensitivity monitoring of fish assemblages. Although the capacity of eDNA metabarcoding to describe fish assemblages is recognised, research efforts are still needed to better assess the spatial and temporal variability of the eDNA signal and to ultimately design an optimal sampling strategy for eDNA monitoring. In this context, we sampled three different lakes (a dam reservoir, a shallow eutrophic lake and a deep oligotrophic lake) every 6 weeks for 1 year. We performed four types of sampling for each lake (integrative sampling of sub-surface water along transects on the left shore, the right shore and above the deepest zone, and point sampling in deeper layers near the lake bottom) to explore the spatial variability of the eDNA signal at the lake scale over a period of 1 year. A metabarcoding approach was applied to analyse the 92 eDNA samples in order to obtain fish species inventories which were compared with traditional fish monitoring methods (standardized gillnet samplings). Several species known to be present in these lakes were only detected by eDNA, confirming the higher sensitivity of this technique in comparison with gillnetting. The eDNA signal varied spatially, with shoreline samples being richer in species than the other samples. Furthermore, deep-water samplings appeared to be non-relevant for regularly mixed lakes, where the eDNA signal was homogeneously distributed. These results also demonstrate a clear temporal variability of the eDNA signal that seems to be related to species phenology, with most of the species detected in spring during the spawning period on shores, but also a peak of detection in winter for salmonid and coregonid species during their reproduction period. These results contribute to our understanding of the spatio-temporal distribution of eDNA in lakes and allow us to provide methodological recommendations regarding where and when to sample eDNA for fish monitoring in lakes.

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.

DNA sequence and taxonomic gap analyses to quantify the coverage of aquatic cyanobacteria and eukaryotic microalgae in reference databases: Results of a survey in the Alpine region.

The taxonomic identification of organisms based on the amplification of specific genetic markers (metabarcoding) implicitly requires adequate discriminatory information and taxonomic coverage of environmental DNA sequences in taxonomic databases. These requirements were quantitatively examined by comparing the determination of cyanobacteria and microalgae obtained by metabarcoding and light microscopy. We used planktic and biofilm samples collected in 37 lakes and 22 rivers across the Alpine region. We focused on two of the most used and best represented genetic markers in the reference databases, namely the 16S rRNA and 18S rRNA genes. A sequence gap analysis using blastn showed that, in the identity range of 99-100%, approximately 30% (plankton) and 60% (biofilm) of the sequences did not find any close counterpart in the reference databases (NCBI GenBank). Similarly, a taxonomic gap analysis showed that approximately 50% of the cyanobacterial and eukaryotic microalgal species identified by light microscopy were not represented in the reference databases. In both cases, the magnitude of the gaps differed between the major taxonomic groups. Even considering the species determined under the microscope and represented in the reference databases, 22% and 26% were still not included in the results obtained by the blastn at percentage levels of identity ≥95% and ≥97%, respectively. The main causes were the absence of matching sequences due to amplification and/or sequencing failure and potential misidentification in the microscopy step. Our results quantitatively demonstrated that in metabarcoding the main obstacles in the classification of 16S rRNA and 18S rRNA sequences and interpretation of high-throughput sequencing biomonitoring data were due to the existence of important gaps in the taxonomic completeness of the reference databases and the short length of reads. The study focused on the Alpine region, but the extent of the gaps could be much greater in other less investigated geographic areas.

Environmental paleomicrobiology: using DNA preserved in aquatic sediments to its full potential.

In-depth knowledge about spatial and temporal variation in microbial diversity and function is needed for a better understanding of ecological and evolutionary responses to global change. In particular, the study of microbial ancient DNA preserved in sediment archives from lakes and oceans can help us to evaluate the responses of aquatic microbes in the past and make predictions about future biodiversity change in those ecosystems. Recent advances in molecular genetic methods applied to the analysis of historically deposited DNA in sediments have not only allowed the taxonomic identification of past aquatic microbial communities but also enabled tracing their evolution and adaptation to episodic disturbances and gradual environmental change. Nevertheless, some challenges remain for scientists to take full advantage of the rapidly developing field of paleo-genetics, including the limited ability to detect rare taxa and reconstruct complete genomes for evolutionary studies. Here, we provide a brief review of some of the recent advances in the field of environmental paleomicrobiology and discuss remaining challenges related to the application of molecular genetic methods to study microbial diversity, ecology, and evolution in sediment archives. We anticipate that, in the near future, environmental paleomicrobiology will shed new light on the processes of microbial genome evolution and microbial ecosystem responses to quaternary environmental changes at an unprecedented level of detail. This information can, for example, aid geological reconstructions of biogeochemical cycles and predict ecosystem responses to environmental perturbations, including in the context of human-induced global changes.

Fish eDNA metabarcoding from aquatic biofilm samples: Methodological aspects.

Fish eDNA metabarcoding is usually performed from filtered water samples. The volume of filtered water depends on the study scope and can rapidly become time consuming according to the number of samples that have to be processed. To avoid time allocated to filtration, passive DNA samplers have been used to recover fish eDNA from marine environments faster. In freshwater ecosystems, aquatic biofilms were used to catch eDNA from macroinvertebrates. Here, we test the capacity of aquatic biofilms to entrap fish eDNA in a large lake and, therefore, the possibility to perform fish eDNA metabarcoding from this matrix compared to the traditional fish eDNA approach from filtered water samples. Methodological aspects of the use of aquatic biofilms for fish eDNA metabarcoding (e.g. PCR replicates, biological replicates, bioinformatics pipeline, reference database and taxonomic assignment) were validated against a mock community. When using biofilms from habitats sheltered from wind and waves, biofilm and water approach provided similar inventories. Richness and diversity were comparable between both approaches. Approaches differed only for rare taxa. Our results illustrate the capacity of aquatic biofilms to act as passive eDNA samplers of fish eDNA and, therefore, the possibility to use biofilms to monitor fish communities efficiently from biofilms. Furthermore, our results open up avenues of research to study a diversity of biological groups (among which bioindicators as diatoms, macroinvertebrates and fish) from eDNA isolated from a single environmental matrix reducing sampling efforts, analysis time and costs.

Physico-chemical dataset from an in situ mesocosm experiment simulating extreme climate events in Lake Geneva (MESOLAC).

This dataset complement a previously published dataset [1] and corresponds to the physico-chemical parameters data series produced during the MESOLAC experimental project [2]. The presented dataset is composed of: 1. In situ profiles (0-3m) of temperature, conductivity, pH, dissolved oxygen (concentration and saturation). 2. In situ measurements of light spectral UV/VIS/IR irradiance (300-950 nm wavelength range) taken at 0, 0.25, 0.5, 1, 1.5, 2 and 2.5m. 3. Laboratory chemical analysis of samples collected at 0 and 2 m (conductivity, pH, total alkalinity, NH4, NO2, NO3, total and particulate nitrogen (Ntot, Npart), PO4, total and particulate phosphorus (Ptot, Ppart), total, organic particulate and total particulate carbon (Ctot, Cpart-org, Cpart-tot), Cl, SO4, SiO2. 4. Laboratory analysis of pigments extracted from samples collected at 0 and 2 m (Chla, Chlc, carotenoids, phaeopigments). The experimental design is the same as in Tran-Khac et al [1]. Briefly, it consisted of nine pelagic mesocosms (about 3000 L, 3m depth) deployed in July 2019 in Lake Geneva near the shore of Thonon les Bains (France) aiming to simulate predicted climate scenarios (i.e. extreme events) and assess the response of planktonic communities, ecosystem functioning and resilience. During the experiment, physical parameters were measured twice a week. At the same time, samples were collected at 0 and 2m of depth for subsequent chemical laboratory analyses. These data are presented in the dataset file, ordered by sampling event (numbered from S1 to S8), treatment (Control-C, High-H and Medium-M) and replicates (1 to 3). For each sampling point the measured parameters are listed in columns, missing data and values below the detection limit are marked as NA (not available). This data set aims to contribute to the understanding of the effect of environmental forcing on lake physico-chemical characteristics (such as temperature, oxygen and nutrient concentration) under simulated intense weather events. To a broader extent, the presented data can be used for a wide variety of applications, including monitoring of a large peri-alpine lake functioning under environmental stress and being included in further meta-analysis to generalise the effect of climate change on large lakes. The two complementary dataset differ in the acquired data and methods, temporal and spatial resolution. They complete each other in terms of physico-chemical characterization of the experimental treatments and together can allow comparison of the two different monitoring strategies (continuous vs punctual) during in situ experimental manipulations.

Landscape Setting Drives the Microbial Eukaryotic Community Structure in Four Swedish Mountain Lakes over the Holocene.

On the annual and interannual scales, lake microbial communities are known to be heavily influenced by environmental conditions both in the lake and in its terrestrial surroundings. However, the influence of landscape setting and environmental change on shaping these communities over a longer (millennial) timescale is rarely studied. Here, we applied an 18S metabarcoding approach to DNA preserved in Holocene sediment records from two pairs of co-located Swedish mountain lakes. Our data revealed that the microbial eukaryotic communities were strongly influenced by catchment characteristics rather than location. More precisely, the microbial communities from the two bedrock lakes were largely dominated by unclassified Alveolata, while the peatland lakes showed a more diverse microbial community, with Ciliophora, Chlorophyta and Chytrids among the more predominant groups. Furthermore, for the two bedrock-dominated lakes-where the oldest DNA samples are dated to only a few hundred years after the lake formation-certain Alveolata, Chlorophytes, Stramenopiles and Rhizaria taxa were found prevalent throughout all the sediment profiles. Our work highlights the importance of species sorting due to landscape setting and the persistence of microbial eukaryotic diversity over millennial timescales in shaping modern lake microbial communities.

Seasonal Dynamics of Abundance, Structure, and Diversity of Methanogens and Methanotrophs in Lake Sediments.

Understanding temporal and spatial microbial community abundance and diversity variations is necessary to assess the functional roles played by microbial actors in the environment. In this study, we investigated spatial variability and temporal dynamics of two functional microbial sediment communities, methanogenic Archaea and methanotrophic bacteria, in Lake Bourget, France. Microbial communities were studied from 3 sites sampled 4 times over a year, with one core sampled at each site and date, and 5 sediment layers per core were considered. Microbial abundance in the sediment were determined using flow cytometry. Methanogens and methanotrophs community structures, diversity, and abundance were assessed using T-RFLP, sequencing, and real-time PCR targeting mcrA and pmoA genes, respectively. Changes both in structure and abundance were detected mainly at the water-sediment interface in relation to the lake seasonal oxygenation dynamics. Methanogen diversity was dominated by Methanomicrobiales (mainly Methanoregula) members, followed by Methanosarcinales and Methanobacteriales. For methanotrophs, diversity was dominated by Methylobacter in the deeper area and by Methylococcus in the shallow area. Organic matter appeared to be the main environmental parameter controlling methanogens, while oxygen availability influenced both the structure and abundance of the methanotrophic community.

Protist taxonomic and functional diversity in soil, freshwater and marine ecosystems.

Protists dominate eukaryotic diversity and play key functional roles in all ecosystems, particularly by catalyzing carbon and nutrient cycling. To date, however, a comparative analysis of their taxonomic and functional diversity that compares the major ecosystems on Earth (soil, freshwater and marine systems) is missing. Here, we present a comparison of protist diversity based on standardized high throughput 18S rRNA gene sequencing of soil, freshwater and marine environmental DNA. Soil and freshwater protist communities were more similar to each other than to marine protist communities, with virtually no overlap of Operational Taxonomic Units (OTUs) between terrestrial and marine habitats. Soil protists showed higher γ diversity than aquatic samples. Differences in taxonomic composition of the communities led to changes in a functional diversity among ecosystems, as expressed in relative abundance of consumers, phototrophs and parasites. Phototrophs (eukaryotic algae) dominated freshwater systems (49% of the sequences) and consumers soil and marine ecosystems (59% and 48%, respectively). The individual functional groups were composed of ecosystem- specific taxonomic groups. Parasites were equally common in all ecosystems, yet, terrestrial systems hosted more OTUs assigned to parasites of macro-organisms while aquatic systems contained mostly microbial parasitoids. Together, we show biogeographic patterns of protist diversity across major ecosystems on Earth, preparing the way for more focused studies that will help understanding the multiple roles of protists in the biosphere.

In situ pelagic dataset from continuous monitoring: A mesocosm experiment in Lake Geneva (MESOLAC).

This dataset corresponds to a data series produced from automated data loggers during the MESOLAC experimental project. Nine pelagic mesocosms (about 3000 L, 3 m depth) were deployed in July 2019 in Lake Geneva near the shore of Thonon les Bains (France), simulating predicted climate scenarios (i.e. intense weather events) by applying a combination of forcing. The design consisted of three treatments each replicated three times: a control treatment (named C - no treatment applied) and two different treatments simulating different intensities of weather events. The high intensity treatment (named H) aimed to reproduce short and intense weather events such as violent storms. It consisted of a short-term stress applied during the first week, with high pulse of dissolved organic carbon (5x increased concentration, i.e. total DOC ∼ 6 mg L-1), transmitted light reduced to 15% and water column manual mixing. The medium intensity treatment (named M) simulated less intense and more prolonged exposures such as during flood events. It was maintained during the 4 weeks of the experiment and consisted of 1.5x increased concentration of dissolved organic carbon (i.e. total DOC ∼ 2 mg L-1), 70% transmitted light and water column manual mixing. Automated data loggers were placed for the entire period of the experiment in the mesocosms and in the lake for comparison with natural conditions. Temperature, conductivity, dissolved oxygen and CO2 were monitored every 15 min at different depths (0.15, 0.25, 1 and 2 m). This data set aims to contribute our understanding of the effect of environmental forcing on lake ecosystem processes (such as production, respiration and CO2 exchange) under simulated intense weather events and the ability of the planktonic community to recover after perturbation. To a broader extent, the presented data can be used for a wide variety of applications, including monitoring of lake community functioning during a period of high productivity on a large peri-alpine lake and being included in further meta-analysis aiming at generalising the effect of climate change on large lakes.

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.

Global distribution of Trebouxiophyceae diversity explored by high-throughput sequencing and phylogenetic approaches.

Trebouxiophyceae are a ubiquitous class of Chlorophyta encountered in aquatic and terrestrial environments. Most taxa are photosynthetic, and many acts as photobionts in symbiotic relationships, while others are free-living. Trebouxiophyceae have also been widely investigated for their use for biotechnological applications. In this work, we aimed at obtaining a comprehensive image of their diversity by compiling the information of 435 freshwater, soil and marine environmental DNA samples surveyed with Illumina sequencing technology in order to search for the most relevant environments for bioprospecting. Freshwater and soil were most diverse and shared more than half of all operational taxonomic units (OTUs), however, their communities were significantly distinct. Oceans hosted the highest genetic novelty, and did not share any OTUs with the other environments; also, marine samples host more diversity in warm waters. Symbiotic genera usually found in lichens such as Trebouxia, Myrmecia and Symbiochloris were also abundantly detected in the ocean, suggesting either free-living lifestyles or unknown symbiotic relationships with marine planktonic organisms. Altogether, our study opens the way to new prospection for trebouxiophycean strains, especially in understudied environments like the ocean.

Diversity, spatial distribution and activity of fungi in freshwater ecosystems.

High-throughput sequencing has given new insights into aquatic fungal community ecology over the last 10 years. Based on 18S ribosomal RNA gene sequences publicly available, we investigated fungal richness and taxonomic composition among 25 lakes and four rivers. We used a single pipeline to process the reads from raw data to the taxonomic affiliation. In addition, we studied, for a subset of lakes, the active fraction of fungi through the 18S rRNA transcripts level. These results revealed a high diversity of fungi that can be captured by 18S rRNA primers. The most OTU-rich groups were Dikarya (47%), represented by putative filamentous fungi more diverse and abundant in freshwater habitats than previous studies have suggested, followed by Cryptomycota (17.6%) and Chytridiomycota (15.4%). The active fraction of the community showed the same dominant groups as those observed at the 18S rRNA genes level. On average 13.25% of the fungal OTUs were active. The small number of OTUs shared among aquatic ecosystems may result from the low abundances of those microorganisms and/or they constitute allochthonous fungi coming from other habitats (e.g., sediment or catchment areas). The richness estimates suggest that fungi have been overlooked and undersampled in freshwater ecosystems, especially rivers, though they play key roles in ecosystem functioning as saprophytes and parasites.

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

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

Development and implementation of eco-genomic tools for aquatic ecosystem biomonitoring: the SYNAQUA French-Swiss program.

The effectiveness of environmental protection measures is based on the early identification and diagnosis of anthropogenic pressures. Similarly, restoration actions require precise monitoring of changes in the ecological quality of ecosystems, in order to highlight their effectiveness. Monitoring the ecological quality relies on bioindicators, which are organisms revealing the pressures exerted on the environment through the composition of their communities. Their implementation, based on the morphological identification of species, is expensive because it requires time and experts in taxonomy. Recent genomic tools should provide access to reliable and high-throughput environmental monitoring by directly inferring the composition of bioindicators' communities from their DNA (metabarcoding). The French-Swiss program SYNAQUA (INTERREG France-Switzerland 2017-2019) proposes to use and validate the tools of environmental genomic for biomonitoring and aims ultimately at their implementation in the regulatory bio-surveillance. SYNAQUA will test the metabarcoding approach focusing on two bioindicators, diatoms, and aquatic oligochaetes, which are used in freshwater biomonitoring in France and Switzerland. To go towards the renewal of current biomonitoring practices, SYNAQUA will (1) bring together different actors: scientists, environmental managers, consulting firms, and biotechnological companies, (2) apply this approach on a large scale to demonstrate its relevance, (3) propose robust and reliable tools, and (4) raise public awareness and train the various actors likely to use these new tools. Biomonitoring approaches based on such environmental genomic tools should address the European need for reliable, higher-throughput monitoring to improve the protection of aquatic environments under multiple pressures, guide their restoration, and follow their evolution.

Homogenization of lake cyanobacterial communities over a century of climate change and eutrophication.

Human impacts on biodiversity are well recognized, but uncertainties remain regarding patterns of diversity change at different spatial and temporal scales. Changes in microbial assemblages are, in particular, not well understood, partly due to the lack of community composition data over relevant scales of space and time. Here, we investigate biodiversity patterns in cyanobacterial assemblages over one century of eutrophication and climate change by sequencing DNA preserved in the sediments of ten European peri-Alpine lakes. We found species losses and gains at the lake scale, while species richness increased at the regional scale over approximately the past 100 years. Our data show a clear signal for beta diversity loss, with the composition and phylogenetic structure of assemblages becoming more similar across sites in the most recent decades, as have the general environmental conditions in and around the lakes. We attribute patterns of change in community composition to raised temperatures affecting the strength of the thermal stratification and, as a consequence, nutrient fluctuations, which favoured cyanobacterial taxa able to regulate buoyancy. Our results reinforce previous reports of human-induced homogenization of natural communities and reveal how potentially toxic and bloom-forming cyanobacteria have widened their geographic distribution in the European temperate region.

Tracking a century of changes in microbial eukaryotic diversity in lakes driven by nutrient enrichment and climate warming.

High-throughput sequencing of sedimentary DNA (sed-DNA) was utilized to reconstruct the temporal dynamics of microbial eukaryotic communities (MECs) at a centennial scale in two re-oligotrophicated lakes that were exposed to different levels of phosphorus enrichment. The temporal changes within the MECs were expressed in terms of richness, composition and community structure to investigate their relationships with two key forcing factors (i.e., nutrient enrichment and climate warming). Various groups, including Apicomplexa, Cercozoa, Chrysophyceae, Ciliophora, Chlorophyceae and Dinophyceae, responded to phosphorus enrichment levels with either positive or negative impacts on their richness and relative abundance. For both lakes, statistical modelling demonstrated that phosphorus concentration ([P]) was a dominant contributor to MECs modifications before the 1980s; after the mid-80s, the contribution of air temperature changes increased and potentially surpassed the contribution of [P]. Co-occurrence network analysis revealed that some clusters of taxa (i.e., modules) composed mainly of Dinophyceae and unclassified Alveolata were strongly correlated to air temperature in both lakes. Overall, our data showed that sed-DNA constitutes a precious archive of information on past biodiversity changes, allowing the study of the dynamics of numerous eukaryotic groups that were not traditionally considered in paleo-reconstructions.

Overview of freshwater microbial eukaryotes diversity: a first analysis of publicly available metabarcoding data.

Although they are widespread, diverse and involved in biogeochemical cycles, microbial eukaryotes attract less attention than their prokaryotic counterparts in environmental microbiology. In this study, we used publicly available 18S barcoding data to define biases that may limit such analyses and to gain an overview of the planktonic microbial eukaryotic diversity in freshwater ecosystems. The richness of the microbial eukaryotes was estimated to 100 798 operational taxonomic units (OTUs) delineating 1267 clusters or phylogenetic units (PUs, i.e. monophyletic groups of OTUs that are phylogenetically close). By summing the richness found in aquatic environments, we can predict the microbial eukaryotic richness to be around 200 000-250 000 species. The molecular diversity of protists in freshwater environments is generally higher than that of the morphospecies and cultivated species catalogued in public databases. Amoebozoa, Viridiplantae, Ichthyosporea, and Cryptophyta are the most phylogenetically diverse taxa, and characterisation of these groups is still needed. A network analysis showed that Fungi, Stramenopiles and Viridiplantae play central role in lake ecosystems. Finally, this work provides guidance for compiling metabarcoding data and identifies missing data that should be obtained to increase our knowledge on microbial eukaryote diversity.