Diatom DNA Metabarcoding for Biomonitoring: Strategies to Avoid Major Taxonomical and Bioinformatical Biases Limiting Molecular Indices Capacities - Tapolczai, Kálmán; Keck, François; Bouchez, Agnès; Rimet, Frédéric; Kahlert, Maria; Vasselon, Valentin (Frontiers in Ecology and Evolution, 2019)
Recent years provided an intense progression in the implementation of molecular techniques in a wide variety of research fields in ecology. Biomonitoring and bioassessment can greatly benefit from DNA metabarcoding and High-Throughput Sequencing (HTS) methods that potentially provide reliable, high quantity and quality standardised data in a cost- and time-efficient way. However, DNA metabarcoding has its drawbacks, introducing biases at all the steps of the process, in particular during the bioinformatics treatments used to prepare HTS data for ecological analyses. The high diversity of bioinformatics methods (e.g. OTU clustering, chimera detection, taxonomic assignment) and parameters (e.g. percentage similarity threshold used to define OTU) make inter-studies comparison difficult, limiting the development of standardised and easy-accessible bioassessment procedures for routine freshwater monitoring survey. In order to study and overcome these drawbacks, we constructed three de novo indices to assess river ecological status based on the same biological samples of diatoms analysed with morphological and molecular methods. The biological inventories produced are (i) morphospecies identified by light microscopy, (ii) OTUs provided via metabarcoding and hierarchical clustering of sequences using a 95% sequence similarity threshold and (iii) individual sequence units (ISUs) via metabarcoding and only minimal bioinformatics of quality filtering. In the case of molecular data, no taxonomic assignment was performed, the indices operated directly with the ecological values of OTUs/ ISUs. Our study used an approach of bypassing taxonomic assignment, so bias related to unclassified sequences due to incomplete reference libraries could be handled and no information on ecology of sequences is lost. Additionally, we showed that the index based on ISUs outperformed the OTU-based one in terms of predictive power and accuracy by revealing the hidden ecological information of sequences that are otherwise clustered in the same OTU (intra-species/intra-population variability). Furthermore, ISUs and morphospecies indices provided similar estimation of site ecological status, validating that limited bioinformatics treatments may be used for DNA freshwater monitoring. Our study is a proof of concept where taxonomy- and clustering-free approach is presented, that we believe is a step forward a standardised and comparable DNA bioassessment, complementary to morphological methods.