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.

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Freshwaters worldwide face serious threats, making their protection increasingly important. Freshwater monitoring has historically produced valuable data and continues to develop. Rapid improvements to biomolecular techniques are revolutionizing the way scientists describe biological communities and are bringing about major changes in biomonitoring. Combined with high‐throughput sequencing, DNA metabarcoding is fast and cost‐effective, generating massive amounts of data. In a world with numerous ecological threats, “big data” constitute a tremendous opportunity to improve the efficiency of biological monitoring. These fundamental changes in biomonitoring will require freshwater ecologists and environmental managers to reconsider how they handle large amounts of data.

Current freshwater biomonitoring with diatoms is based on microscopic examination of the morphology of their silica skeleton. This standardized approach is time consuming and requires a high degree of taxonomic expertise. Metabarcoding combined with high-throughput sequencing (HTS) has great potential for next-generation biomonitoring applications but requires standardization. Molecular inventories are strongly influenced by the DNA extraction method used, but the effect of extraction protocols has not been tested to enable selection of the best DNA extraction method for HTS metabarcoding. We used 5 DNA extraction methods combining various types of cell lysis and DNA purification to extract DNA from 8 pure diatom cultures and 8 samples from streams and lakes with differing water quality. We compared the methods based on: 1) quality and purity of the extracted DNA, 2) community inventories obtained from HTS targeting the ribulose-1, 5-bisphosphate carboxylase (rbcL) barcode, and 3) similarity between molecular and microscopy-based inventories of community composition and the Specific Pollutionsensitivity Index [SPI]. A method based on GenElute ™ -LPA had higher extraction efficiency than the 4 commercial kits but had the highest polymerase chain reaction inhibition level. All 5 methods were efficient for HTS, and method did not affect operational taxonomic unit richness. We observed variations in the relative abundance of some taxa within Nitzschia, Amphora, Encyonema, Gomphonema, and Navicula between 2 of the 5 methods, but method did not affect global diatom community composition or SPI values. SPI values calculated from microscopy-based inventories and molecular inventories based on all 5 extraction methods were strongly correlated. For convenience purposes (high DNA quantity and low cost), we encourage standardization of HTS diatom biomonitoring based on the SA-Gen method.

In recent years, remarkable progress has been made in developing environmental DNA metabarcoding. However, its ability to quantify species relative abundance remains uncertain, limiting its application for biomonitoring. In diatoms, although the rbcL gene appears to be a suitable barcode for diatoms, providing relevant qualitative data to describe taxonomic composition, improvement of species quantification is still required. Here, we hypothesized that rbcL copy number is correlated with diatom cell biovolume (as previously described for the 18S gene) and that a correction factor (CF) based on cell biovolume should be applied to improve taxa quantification. We carried out a laboratory experiment using pure cultures of eight diatom species with contrasted cell biovolumes in order to (1) verify the relationship between rbcL copy numbers (estimated by qPCR) and diatom cell biovolumes and (2) define a potential CF. In order to evaluate CF efficiency, five mock communities were created by mixing different amounts of DNA from the eight species, and were sequenced using HTS and targeting the same rbcL barcode. As expected, the correction of DNA reads proportions by the CF improved the congruence between morphological and molecular inventories. Final validation of the CF was obtained on environmental samples (metabarcoding data from 80 benthic biofilms) for which the application of CF allowed differences between molecular and morphological water quality indices to be reduced by 47%. Overall, our results highlight the usefulness of applying a CF factor, which is effective in reducing over‐estimation of high biovolume species, correcting quantitative biases in diatom metabarcoding studies and improving final water quality assessment.

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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_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_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/