Search

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., (© 2018 John Wiley & Sons Ltd.)

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., (Copyright © 2018 Elsevier B.V. All rights reserved.)

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/., (© The Author(s) 2016. Published by Oxford University Press.)