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      Comparative analysis of morphological and molecular approaches integrated into the study of the dinoflagellate biodiversity within the recently deposited Black Sea sediments – benefits and drawbacks

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          Abstract

          One of the assets, assigned to the phytoplankton resting stages, is that of serving as the “memory” of the aquatic ecosystems and preserved biodiversity in the course of time. However, an accurate cyst identification proves to be a more difficult and extremely challenging process, even today. In order to gain a better taxonomic coverage of cyst assemblages in the Black Sea, an integrated approach of the classical morphological identification with metabarcoding methods (MySeq sequencing of V7-V9 regions of the 18S rDNA) was applied on thirteen surface sediment samples collected from different sites. A total number of 112 dinoflagellate taxa was detected at the species level and ascribed to 51 genera. In general, it is the molecular analysis that yields a higher number of taxa as compared to those obtained through the morphological taxonomy (66 taxa based on the DNA sequences versus 56 morphologically-identified taxa). Besides, it should be pointed out that the integrated dataset includes 14 potentially toxic dinoflagellate species. Discerned, subsequently, was a good dataset consistency for ten species, followed by some discrepancies as to a number of taxa, identified with one of the methods only, due to specific methodological biases. On the whole, it could be concluded that the combination of morphological and molecular methods is likely to increase the potential for a more reliable taxonomic assessment of phytoplankton diversity in marine sediments which, in turn, proves conclusively the utmost importance of the integrated approach.

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          Diversity predicts stability and resource use efficiency in natural phytoplankton communities.

          The relationship between species diversity and ecosystem functioning has been debated for decades, especially in relation to the "macroscopic" realm (higher plants and metazoans). Although there is emerging consensus that diversity enhances productivity and stability in communities of higher organisms; however, we still do not know whether these relationships apply also for communities of unicellular organisms, such as phytoplankton, which contribute approximately 50% to the global primary production. We show here that phytoplankton resource use, and thus carbon fixation, is directly linked to the diversity of phytoplankton communities. Datasets from freshwater and brackish habitats show that diversity is the best predictor for resource use efficiency of phytoplankton communities across considerable environmental gradients. Furthermore, we show that the diversity requirement for stable ecosystem functioning scales with the nutrient level (total phosphorus), as evidenced by the opposing effects of diversity (negative) and resource level (positive) on the variability of both resource use and community composition. Our analyses of large-scale observational data are consistent with experimental and model studies demonstrating causal effects of microbial diversity on functional properties at the system level. Our findings point at potential linkages between eutrophication and pollution-mediated loss of phytoplankton diversity. Factors reducing phytoplankton diversity may have direct detrimental effects on the amount and predictability of aquatic primary production.
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            Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies.

            Diatoms are frequently used for water quality assessments; however, identification to species level is difficult, time-consuming and needs in-depth knowledge of the organisms under investigation, as nonhomoplastic species-specific morphological characters are scarce. We here investigate how identification methods based on DNA (metabarcoding using NGS platforms) perform in comparison to morphological diatom identification and propose a workflow to optimize diatom fresh water quality assessments. Diatom diversity at seven different sites along the course of the river system Odra and Lusatian Neisse from the source to the mouth is analysed with DNA and morphological methods, which are compared. The NGS technology almost always leads to a higher number of identified taxa (270 via NGS vs. 103 by light microscopy LM), whose presence could subsequently be verified by LM. The sequence-based approach allows for a much more graduated insight into the taxonomic diversity of the environmental samples. Taxa retrieval varies considerably throughout the river system, depending on species occurrences and the taxonomic depth of the reference databases. Mostly rare taxa from oligotrophic parts of the river systems are less well represented in the reference database used. A workflow for DNA-based NGS diatom identification is presented. 28 000 diatom sequences were evaluated. Our findings provide evidence that metabarcoding of diatoms via NGS sequencing of the V4 region (18S) has a great potential for water quality assessments and could complement and maybe even improve the identification via light microscopy.
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              Unveiling Distribution Patterns of Freshwater Phytoplankton by a Next Generation Sequencing Based Approach

              The recognition and discrimination of phytoplankton species is one of the foundations of freshwater biodiversity research and environmental monitoring. This step is frequently a bottleneck in the analytical chain from sampling to data analysis and subsequent environmental status evaluation. Here we present phytoplankton diversity data from 49 lakes including three seasonal surveys assessed by next generation sequencing (NGS) of 16S ribosomal RNA chloroplast and cyanobacterial gene amplicons and also compare part of these datasets with identification based on morphology. Direct comparison of NGS to microscopic data from three time-series showed that NGS was able to capture the seasonality in phytoplankton succession as observed by microscopy. Still, the PCR-based approach was only semi-quantitative, and detailed NGS and microscopy taxa lists had only low taxonomic correspondence. This is probably due to, both, methodological constraints and current discrepancies in taxonomic frameworks. Discrepancies included Euglenophyta and Heterokonta that were scarce in the NGS but frequently detected by microscopy and Cyanobacteria that were in general more abundant and classified with high resolution by NGS. A deep-branching taxonomically unclassified cluster was frequently detected by NGS but could not be linked to any group identified by microscopy. NGS derived phytoplankton composition differed significantly among lakes with different trophic status, showing that our approach can resolve phytoplankton communities at a level relevant for ecosystem management. The high reproducibility and potential for standardization and parallelization makes our NGS approach an excellent candidate for simultaneous monitoring of prokaryotic and eukaryotic phytoplankton in inland waters.
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                Author and article information

                Contributors
                Journal
                Biodivers Data J
                Biodivers Data J
                1
                urn:lsid:arphahub.com:pub:F9B2E808-C883-5F47-B276-6D62129E4FF4
                urn:lsid:zoobank.org:pub:245B00E9-BFE5-4B4F-B76E-15C30BA74C02
                Biodiversity Data Journal
                Pensoft Publishers
                1314-2836
                1314-2828
                2020
                18 August 2020
                : 8
                : e55172
                Affiliations
                [1 ] Institute of Oceanology “Fridtjof Nansen”, Marine Biology and Ecology Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology “Fridtjof Nansen”, Marine Biology and Ecology Department, Bulgarian Academy of Sciences Varna Bulgaria
                [2 ] Water Research Institute, Unit Talassografico “A. Cerruti”, National Research Council CNR-IRSA, Taranto, Italy Water Research Institute, Unit Talassografico “A. Cerruti”, National Research Council CNR-IRSA Taranto Italy
                [3 ] National Research Institute of Fisheries Science, Research Center for Aquatic Genomics, Fisheries Research and Education Agency, Yokohama Kanagawa, Japan National Research Institute of Fisheries Science, Research Center for Aquatic Genomics, Fisheries Research and Education Agency Yokohama Kanagawa Japan
                [4 ] Institute of Oceanology “Fridtjof Nansen”, Ocean Technologies Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology “Fridtjof Nansen”, Ocean Technologies Department, Bulgarian Academy of Sciences Varna Bulgaria
                Author notes
                Corresponding author: Snejana Moncheva ( snejanam@ 123456abv.bg ).

                Academic editor: Anne Thessen

                Author information
                https://orcid.org/0000-0001-9620-6422
                Article
                55172 14166
                10.3897/BDJ.8.e55172
                7447646
                5ff20224-6ac9-4048-acd5-780fcb6cdbc6
                Nina Dzhembekova, Fernando Rubino, Satoshi Nagai, Ivelina Zlateva, Nataliya Slabakova, Petya Ivanova, Violeta Slabakova, Snejana Moncheva

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 06 June 2020
                : 27 July 2020
                Page count
                Figures: 5, Tables: 3, References: 49
                Categories
                Research Article

                black sea,phytoplankton,cyst,morphology,metabarcoding
                black sea, phytoplankton, cyst, morphology, metabarcoding

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