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Little is still known about the low dose effects of radiation on the microbial communities in the environment. Mineral springs are ecosystems than can be affected by natural radioactivity. These extreme environments are, therefore, observatories for studying the influence of chronic radioactivity on the natural biota. In these ecosystems we find diatoms, unicellular microalgae, playing an essential role in the food chain. The present study aimed to investigate, using DNA metabarcoding, the effect of natural radioactivity in two environmental compartments (i.e. spring sediments and water) on the genetic richness, diversity and structure of diatom communities in 16 mineral springs in the Massif Central, France. Diatom biofilms were collected during October 2019, and a 312 bp region of the chloroplast gene rbcL (coding for the Ribulose Bisphosphate Carboxylase) used as a barcode for taxonomic assignation. A total of 565 amplicon sequence variants (ASV) were found. The dominant ASV were associated with Navicula sanctamargaritae, Gedaniella sp., Planothidium frequentissimum, Navicula veneta, Diploneis vacillans, Amphora copulata, Pinnularia brebissonii, Halamphora coffeaeformis, Gomphonema saprophilum, and Nitzschia vitrea, but some of the ASVs could not be assigned at the species level. Pearson correlation failed to show a correlation between ASV' richness and radioactivity parameters. Non-parametric MANOVA analysis based on ASVs occurrence or abundances revealed that geographical location was the main factor influencing ASVs distribution. Interestingly, 238 U was the second factor that explained diatom ASV structure. Among the ASVs in the mineral springs monitored, ASV associated with one of the genetic variants of Planothidium frequentissimum was well represented in the springs and with higher levels of 238 U, suggesting its high tolerance to this particular radionuclide. This diatom species may therefore represent a bio-indicator of high natural levels of uranium., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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., (© 2020 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

Human activities are the leading cause of environmental impairments. Appropriate biomonitoring of ecosystems is needed to assess these activities effectively. In freshwater ecosystems, periphytic and epilithic biofilms have diatom assemblages. These assemblages respond rapidly to environmental changes, making diatoms valuable bioindicators. For this reason, freshwater biomonitoring programs are currently using diatoms (e.g., Water Framework Directive). In the past ten years, DNA metabarcoding coupled with next-generation sequencing and bioinformatics represents a complementary approach for diatom biomonitoring. In this study, this approach is used for the first time in Cyprus by considering the association of environmental and anthropogenic pressures to diatom assemblages. Statistical analysis was then applied to identify the environmental (i.e., river types, geo-morphological) and anthropogenic (i.e., physicochemical, human land-use pressures) variables' role in the observed diatom diversity. Results indicate differences in diatom assemblages between intermittent and perennial rivers. Achnanthidium minutissimum was more abundant in intermittent rivers; whereas Amphora pediculus and Planothidium caputium in perennial ones. Additionally, we could demonstrate the correlation between nutrients (e.g., nitrogen, phosphorus), stations' local characteristics (e.g., elevation), and land use activities on the observed differences in diatom diversity. Finally, we conclude that multi-stressors and anthropogenic pressures together as multiple stressors have a significant statistical relationship to the observed diatom diversity and play a pivotal role in determining Cyprus' rivers' ecological status., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Our study of 164 diatom samples from Catalonia (NE Spain) is the first to evaluate the applicability of DNA metabarcoding, based on high throughput sequencing (HTS) using a 312-bp rbcL marker, for biomonitoring Mediterranean rivers. For this, we compared the values of a biotic index (IPS) and the ecological status classes derived from them, between light microscope-based (LM) and HTS methods. Very good correspondence between methods gives encouraging results concerning the applicability of DNA metabarcoding for Catalan rivers for the EU Water Framework Directive (WFD). However, in 10 sites, the ecological status class was downgraded from "Good"/"High" obtained by LM to "Moderate"/"Poor"/"Bad" by HTS; these "critical" sites are especially important, because the WFD requires remedial action by water managers for any river with Moderate or lower status. We investigated the contribution of each species to the IPS using a "leave-one-out" sensitivity analysis, paying special attention to critical sites. Discrepancies in IPS between LM and HTS were mainly due to the misidentification and overlooking in LM of a few species, which were better recovered by HTS. This bias was particularly important in the case of Fistulifera saprophila, whose clear underrepresentation in LM was important for explaining 8 out of the 10 critical sites and probably reflected destruction of weakly-silicified frustules during sample preparation. Differences between species in the rbcL copy number per cell affected the relative abundance obtained by HTS for Achnanthidium minutissimum, Nitzschia inconspicua and Ulnaria ulna, which were also identified by the sensitivity analysis as important for the WFD. Only minor IPS discrepancies were attributed to the incompleteness of the reference library, as most of the abundant and influential species (to the IPS) were well represented there. Finally, we propose that leave-one-out analysis is a good method for identifying priority species for isolation and barcoding., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Diatoms are a compulsory biological quality element in the ecological assessment of rivers according to the Water Framework Directive. The application of current official indices requires the identification of individuals to species or lower rank under a microscope based on the valve morphology. This is a highly time-consuming task, often susceptible of disagreements among analysts. In alternative, the use of DNA metabarcoding combined with High-Throughput Sequencing (HTS) has been proposed. The sequences obtained from environmental DNA are clustered into Operational Taxonomic Units (OTUs), which can be assigned to a taxon using reference databases, and from there calculate biotic indices. However, there is still a high percentage of unassigned OTUs to species due to the incompleteness of reference libraries. Alternatively, we tested a new taxonomy-free approach based on diatom community samples to assess rivers. A combination of three machine learning techniques is used to build models that predict diatom OTUs expected in test sites, under reference conditions, from environmental data. The Observed/Expected OTUs ratio indicates the deviation from reference condition and is converted into a quality class. This approach was never used with diatoms neither with OTUs data. To evaluate its efficiency, we built a model based on OTUs lists (HYDGEN) and another based on taxa lists from morphological identification (HYDMORPH), and also calculated a biotic index (IPS). The models were trained and tested with data from 81 sites (44 reference sites) from central Portugal. Both models were considered accurate (linear regression for Observed and Expected richness: R 2  ≈ 0.7, interception ≈ 0.8) and sensitive to global anthropogenic disturbance (Rs 2  > 0.30 p < 0.006 for global disturbance). Yet, the HYDGEN model based on molecular data was sensitive to more types of pressures (such as, changes in land use and habitat quality), which gives promising insights to its use for bioassessment of rivers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Diatoms (Bacillariophyta) are ubiquitous microalgae which produce a siliceous exoskeleton and which make a major contribution to the productivity of oceans and freshwaters. They display a huge diversity, which makes them excellent ecological indicators of aquatic ecosystems. Usually, diatoms are identified using characteristics of their exoskeleton morphology. DNA-barcoding is an alternative to this and the use of High-Throughput-Sequencing enables the rapid analysis of many environmental samples at a lower cost than analyses under microscope. However, to identify environmental sequences correctly, an expertly curated reference library is needed. Several curated libraries for protists exists; none, however are dedicated to diatoms. Diat.barcode is an open-access library dedicated to diatoms which has been maintained since 2012. Data come from two sources (1) the NCBI nucleotide database and (2) unpublished sequencing data of culture collections. Since 2017, several experts have collaborated to curate this library for rbcL, a chloroplast marker suitable for species-level identification of diatoms. For the latest version of the database (version 7), 605 of the 3482 taxonomical names originally assigned by the authors of the rbcL sequences were modified after curation. The database is accessible at https://www6.inra.fr/carrtel-collection&#95;eng/Barcoding-database .

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&#95;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/., (© The Author(s) 2016. Published by Oxford University Press.)

Benthic diatoms are relevant indicators of the ecological status of the littoral zone of lakes. Their use as bio-indicators is based on their morphological identification at species level using microscopy which is time consuming, requires taxonomic expertise, and is consequently expensive. To overcome these limitations, a molecular approach for diatom identification has been tested with success in rivers. DNA metabarcoding enables species identification from a standardized DNA barcode and high-throughput sequencing (HTS), using DNA reference library. The suitability of the morphological and molecular approaches to assess the diatom community structure and the ecological status of the littoral zone of the largest deep lake in France (Lake Bourget) was compared. 66 sites were sampled in August 2015 along the shoreline, all around the lake. The composition of diatom assemblages was similar with both morphological and molecular approaches, and diatom assemblages were structured by the same environmental factors. However, the ecological status of Lake Bourget differed significantly among approaches since floristic inventories to species level also differed significantly. The main source of this difference was the incompleteness of the DNA reference library. Nevertheless, in a near future, when this constraint will be solved, the use of DNA metabarcoding for biomonitoring purposes seems promising. [ABSTRACT FROM AUTHOR]