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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Ecol. Evol. | doi: 10.3389/fevo.2019.00409

Diatom DNA metabarcoding for biomonitoring : strategies to avoid major taxonomical and bioinformatical biases limiting molecular indices capacities

 Kálmán Tapolczai1, 2*, François Keck3, 4,  Agnès Bouchez4, Frédéric Rimet4 and  Valentin Vasselon4, 5
  • 1Department of Limnology, University of Pannonia, Hungary
  • 2Premium Postdoctoral Research Program, Hungarian Academy of Sciences (MTA), Hungary
  • 3Swedish University of Agricultural Sciences, Sweden
  • 4INRA Centre Alpin de Recherche sur les Réseaux Trophiques des Ecosystèmes Limniques, France
  • 5Other, France

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.

Keywords: bioassessment, biomonitoring, Diatoms, High-throughput sequencing (HTS), metabarcoding

Received: 14 Jun 2019; Accepted: 10 Oct 2019.

Copyright: © 2019 Tapolczai, Keck, Bouchez, Rimet and Vasselon. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Kálmán Tapolczai, Department of Limnology, University of Pannonia, Veszprém, Hungary,