Literature DB >> 28296259

Taxonomy-free molecular diatom index for high-throughput eDNA biomonitoring.

Laure Apothéloz-Perret-Gentil1, Arielle Cordonier2, François Straub3, Jennifer Iseli3, Philippe Esling4, Jan Pawlowski1.   

Abstract

Current biodiversity assessment and biomonitoring are largely based on the morphological identification of selected bioindicator taxa. Recently, several attempts have been made to use eDNA metabarcoding as an alternative tool. However, until now, most applied metabarcoding studies have been based on the taxonomic assignment of sequences that provides reference to morphospecies ecology. Usually, only a small portion of metabarcoding data can be used due to a limited reference database and a lack of phylogenetic resolution. Here, we investigate the possibility to overcome these limitations using a taxonomy-free approach that allows the computing of a molecular index directly from eDNA data without any reference to morphotaxonomy. As a case study, we use the benthic diatoms index, commonly used for monitoring the biological quality of rivers and streams. We analysed 87 epilithic samples from Swiss rivers, the ecological status of which was established based on the microscopic identification of diatom species. We compared the diatom index derived from eDNA data obtained with or without taxonomic assignment. Our taxonomy-free approach yields promising results by providing a correct assessment for 77% of examined sites. The main advantage of this method is that almost 95% of OTUs could be used for index calculation, compared to 35% in the case of the taxonomic assignment approach. Its main limitations are under-sampling and the need to calibrate the index based on the microscopic assessment of diatoms communities. However, once calibrated, the taxonomy-free molecular index can be easily standardized and applied in routine biomonitoring, as a complementary tool allowing fast and cost-effective assessment of the biological quality of watercourses.
© 2017 John Wiley & Sons Ltd.

Keywords:  bioindication; environmental DNA; metabarcoding; water quality

Mesh:

Year:  2017        PMID: 28296259     DOI: 10.1111/1755-0998.12668

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  13 in total

1.  Development and implementation of eco-genomic tools for aquatic ecosystem biomonitoring: the SYNAQUA French-Swiss program.

Authors:  Estelle Lefrançois; Laure Apothéloz-Perret-Gentil; Philippe Blancher; Samuel Botreau; Cécile Chardon; Laura Crepin; Tristan Cordier; Arielle Cordonier; Isabelle Domaizon; Benoit J D Ferrari; Julie Guéguen; Jean-Christophe Hustache; Louis Jacas; Stephan Jacquet; Sonia Lacroix; Anne-Laurence Mazenq; Alina Pawlowska; Pascal Perney; Jan Pawlowski; Frédéric Rimet; Jean-François Rubin; Dominique Trevisan; Régis Vivien; Agnès Bouchez
Journal:  Environ Sci Pollut Res Int       Date:  2018-05-07       Impact factor: 4.223

2.  Characterizing temporal variability in streams supports nutrient indicator development using diatom and bacterial DNA metabarcoding.

Authors:  Nathan J Smucker; Erik M Pilgrim; Huiyun Wu; Christopher T Nietch; John A Darling; Marirosa Molina; Brent R Johnson; Lester L Yuan
Journal:  Sci Total Environ       Date:  2022-04-01       Impact factor: 10.753

Review 3.  Strategies for sample labelling and library preparation in DNA metabarcoding studies.

Authors:  Kristine Bohmann; Vasco Elbrecht; Christian Carøe; Iliana Bista; Florian Leese; Michael Bunce; Douglas W Yu; Mathew Seymour; Alex J Dumbrell; Simon Creer
Journal:  Mol Ecol Resour       Date:  2021-10-13       Impact factor: 8.678

4.  Metabarcoding quantifies differences in accumulation of ballast water borne biodiversity among three port systems in the United States.

Authors:  John A Darling; John Martinson; Katrina M Pagenkopp Lohan; Katharine J Carney; Erik Pilgrim; Aabir Banerji; Kimberly K Holzer; Gregory M Ruiz
Journal:  Sci Total Environ       Date:  2020-08-03       Impact factor: 7.963

5.  DNA metabarcoding and microscopic analyses of sea turtles biofilms: Complementary to understand turtle behavior.

Authors:  Sinziana F Rivera; Valentin Vasselon; Katia Ballorain; Alice Carpentier; Carlos E Wetzel; Luc Ector; Agnès Bouchez; Frédéric Rimet
Journal:  PLoS One       Date:  2018-04-16       Impact factor: 3.240

6.  High-throughput environmental DNA analysis informs a biological assessment of an urban stream.

Authors:  Mark Bagley; Erik Pilgrim; Martin Knapp; Chris Yoder; Jorge Santo Domingo; Aabir Banerji
Journal:  Ecol Indic       Date:  2019       Impact factor: 4.958

7.  Meta-analysis shows both congruence and complementarity of DNA and eDNA metabarcoding to traditional methods for biological community assessment.

Authors:  François Keck; Rosetta C Blackman; Raphael Bossart; Jeanine Brantschen; Marjorie Couton; Samuel Hürlemann; Dominik Kirschner; Nadine Locher; Heng Zhang; Florian Altermatt
Journal:  Mol Ecol       Date:  2022-02-02       Impact factor: 6.622

8.  Environmental DNA metabarcoding reveals comparable responses to agricultural stressors on different trophic levels of a freshwater community.

Authors:  Kevin K Beentjes; S Henrik Barmentlo; Ellen Cieraad; Menno Schilthuizen; Berry B van der Hoorn; Arjen G C L Speksnijder; Krijn B Trimbos
Journal:  Mol Ecol       Date:  2022-01-06       Impact factor: 6.622

9.  Dumpster diving for diatom plastid 16S rRNA genes.

Authors:  Krista L Bonfantine; Stacey M Trevathan-Tackett; Ty G Matthews; Ana Neckovic; Han Ming Gan
Journal:  PeerJ       Date:  2021-07-01       Impact factor: 2.984

10.  DNA metabarcoding effectively quantifies diatom responses to nutrients in streams.

Authors:  Nathan J Smucker; Erik M Pilgrim; Christopher T Nietch; John A Darling; Brent R Johnson
Journal:  Ecol Appl       Date:  2020-08-18       Impact factor: 6.105

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