Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods.

Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.

Expanding ecological assessment by integrating microorganisms into routine freshwater biomonitoring.

Bioindication has become an indispensable part of water quality monitoring in most countries of the world, with the presence and abundance of bioindicator taxa, mostly multicellular eukaryotes, used for biotic indices. In contrast, microbes (bacteria, archaea and protists) are seldom used as bioindicators in routine assessments, although they have been recognized for their importance in environmental processes. Recently, the use of molecular methods has revealed unexpected diversity within known functional groups and novel metabolic pathways that are particularly important in energy and nutrient cycling. In various habitats, microbial communities respond to eutrophication, metals, and natural or anthropogenic organic pollutants through changes in diversity and function. In this review, we evaluated the common trends in these changes, documenting that they have value as bioindicators and can be used not only for monitoring but also for improving our understanding of the major processes in lotic and lentic environments. Current knowledge provides a solid foundation for exploiting microbial taxa, community structures and diversity, as well as functional genes, in novel monitoring programs. These microbial community measures can also be combined into biotic indices, improving the resolution of individual bioindicators. Here, we assess particular molecular approaches complemented by advanced bioinformatic analysis, as these are the most promising with respect to detailed bioindication value. We conclude that microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems.

The D1-D2 region of the large subunit ribosomal DNA as barcode for ciliates.

Ciliates are a major evolutionary lineage within the alveolates, which are distributed in nearly all habitats on our planet and are an essential component for ecosystem function, processes and stability. Accurate identification of these unicellular eukaryotes through, for example, microscopy or mating type reactions is reserved to few specialists. To satisfy the demand for a DNA barcode for ciliates, which meets the standard criteria for DNA barcodes defined by the Consortium for the Barcode of Life (CBOL), we here evaluated the D1-D2 region of the ribosomal DNA large subunit (LSU-rDNA). Primer universality for the phylum Ciliophora was tested in silico with available database sequences as well as in the laboratory with 73 ciliate species, which represented nine of 12 ciliate classes. Primers tested in this study were successful for all tested classes. To test the ability of the D1-D2 region to resolve conspecific and congeneric sequence divergence, 63 Paramecium strains were sampled from 24 mating species. The average conspecific D1-D2 variation was 0.18%, whereas congeneric sequence divergence averaged 4.83%. In pairwise genetic distance analyses, we identified a D1-D2 sequence divergence of <0.6% as an ideal threshold to discriminate Paramecium species. Using this definition, only 3.8% of all conspecific and 3.9% of all congeneric sequence comparisons had the potential of false assignments. Neighbour-joining analyses inferred monophyly for all taxa but for two Paramecium octaurelia strains. Here, we present a protocol for easy DNA amplification of single cells and voucher deposition. In conclusion, the presented data pinpoint the D1-D2 region as an excellent candidate for an official CBOL barcode for ciliated protists.

Synthetic statistical approach reveals a high degree of richness of microbial eukaryotes in an anoxic water column.

Molecular surveys suggest that communities of microbial eukaryotes are remarkably rich, because even large clone libraries seem to capture only a minority of species. This provides a qualitative picture of protistan richness but does not measure its real extent either locally or globally. Statistical analysis can estimate a community's richness, but the specific methods used to date are not always well grounded in statistical theory. Here we study a large protistan molecular survey from an anoxic water column in the Cariaco Basin (Caribbean Sea). We group individual 18S rRNA gene sequences into operational taxonomic units (OTUs) using different cutoff values for sequence similarity (99 to 50%) and systematically apply parametric models and nonparametric estimators to the OTU frequency data to estimate the total protistan diversity. The parametric models provided statistically sound estimates of protistan richness, with biologically meaningful standard errors, maximal data usage, and extensive model diagnostics and were preferable to the available nonparametric tools. Our clone library exceeded 700 clones but still covered only a minority of species and less than half of the larger protistan clades. Our estimates of total protistan richness portray the target community as very rich at all OTU levels, with hundreds of different populations apparently co-occurring in the small (3-liter) volume of our sample, as well as dozens of clades of the highest taxonomic order. These estimates are among the first for microbial eukaryotes that are obtained using state-of-the-art statistical methods and can serve as benchmark numbers for the local diversity of protists.