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High-throughput amplicon sequencing of environmental DNA and/or RNA proved to be a powerful tool to describe protist diversity. This new approach called also the metabarcoding has totally transformed our view of protist diversity, revealing a large number of novel lineages and expanding the range of protist phylogenetic diversity at almost every taxonomic level. However, until now the objectives of the vast majority of metabarcoding studies were purely academic. Practical applications of protist metabarcoding are surprisingly scarce, despite the fact that several groups of protists are commonly used as bioindicators of environmental impacts in freshwater or marine ecosystems. Here, we are reviewing studies that examine the ecological applications of metabarcoding for two groups of well-known protist bioindicators: diatoms and foraminifera. The results of these studies show that despite some biological and technical biases, molecular data quite faithfully reflect the morphology-based biotic indices and provide a similar assessment of ecosystem status. In view of these results, protist metabarcoding appears as a rapid and accurate tool for the evaluation of the quality of aquatic ecosystems. Hence, we plead for integration of protist metabarcoding in future biomonitoring projects as a complement of traditional methods and a source of new biosensors for environmental impact assessment. [ABSTRACT FROM AUTHOR]

Assessing the environmental impact of salmon farms on benthic systems is traditionally undertaken using biotic indices derived from microscopic analyses of macrobenthic infaunal (MI) communities. In this study, we tested the applicability of using foraminiferal-specific high-throughput sequencing (HTS) metabarcoding for monitoring these habitats. Sediment samples and physico-chemical data were collected along an enrichment gradient radiating out from three Chinook salmon ( Oncorhynchus tshawytscha ) farms in New Zealand. HTS of environmental DNA and RNA (eDNA/eRNA) resulted in 1,875,300 sequences that clustered into 349 Operational Taxonomic Units. Strong correlations were observed among various biotic indices calculated from MI data and normalized fourth-root transformed HTS data. Correlations were stronger using eRNA compared to eDNA data. Quantile regression spline analyses identified 12 key foraminiferal taxa that have potential to be used as bioindicator species. This study demonstrates the huge potential for using this method for biomonitoring of fish-farming and other marine industrial activities. [ABSTRACT FROM AUTHOR]