Environmental monitoring through protist next‐generation sequencing metabarcoding: assessing the impact of fish farming on benthic foraminifera communities

Abstract

The measurement of species diversity represents a powerful tool for assessing the impacts of human activities on marine ecosystems. Traditionally, the impact of fish farming on the coastal environment is evaluated by monitoring the dynamics of macrobenthic infaunal populations. However, taxonomic sorting and morphology-based identification of the macrobenthos demand highly trained specialists and are extremely time-consuming and costly, making it unsuitable for large-scale biomonitoring efforts involving numerous samples. Here, we propose to alleviate this laborious task by developing protist metabarcoding tools based on next-generation sequencing (NGS) of environmental DNA and RNA extracted from sediment samples. In this study, we analysed the response of benthic foraminiferal communities to the variation of environmental gradients associated with salmon farms in Scotland. We investigated the foraminiferal diversity based on ribosomal minibarcode sequences generated by the Illumina NGS technology. We compared the molecular data with morphospecies counts and with environmental gradients, including distance to cages and redox used as a proxy for sediment oxygenation. Our study revealed high variations between foraminiferal communities collected in the vicinity of fish farms and at distant locations. We found evidence for species richness decrease in impacted sites, especially visible in the RNA data. We also detected some candidate bioindicator foraminiferal species. Based on this proof-of-concept study, we conclude that NGS metabarcoding using foraminifera and other protists has potential to become a new tool for surveying the impact of aquaculture and other industrial activities in the marine environment.

Parasites dominate hyperdiverse soil protist communities in Neotropical rainforests

“…DNA was isolated using the PowerSoil DNA Elution Accessory Kit (Mo Bio). Like other large-scale sequencing studies 11,49 , only DNA was used in this study, not RNA, which can also be retained in sediments, even ancient ones 50,51 . See Supplementary Fig.…”

Worldwide Analysis of Sedimentary DNA Reveals Major Gaps in Taxonomic Knowledge of Deep-Sea Benthos

“…These uncertainties should not undermine the potential of metabarcoding to better understand the diversity of poorly known communities. Indeed, the total information obtained from a large number of taxa in parallel provides a good estimator of environmental community diversity that has many practical applications for ecosystem assessment and monitoring (Chariton et al, 2010(Chariton et al, , 2014Czernik et al, 2013;Stephenson et al, 2013;Lallias et al, 2014;Pawlowski et al, 2014;Willerslev et al, 2014;Guardiola et al, 2015;Lejzerowicz et al, 2015;Pochon et al, 2015;Boschen et al, 2016).…”

“…Data accessed 17.10.2014. tremendous diversity of eukaryotic organisms, metabarcoding is particularly useful because of its potential to explore the biodiversity of all taxa in parallel (Bik et al, 2012b). Such an approach has revealed novel biodiversity in various coastal environments (e.g., Chariton et al, 2010;Fonseca et al, 2010;Bik et al, 2012a;Lallias et al, 2014;Pawlowski et al, 2014;Cowart et al, 2015). However, despite the dynamic expansion of eDNA studies, little metabarcoding information is available for benthic diversity at bathyal and abyssal depths (Pawlowski et al, 2011).…”

Is the meiofauna a good indicator for climate change and anthropogenic impacts?

“…These dense populations are dominated by species typical of organically enriched habitats. Recently, Pawlowski et al (2014) used a next-generation metabarcoding approach (DNA and RNA) to evaluate foraminiferal diversity responses to organic enrichment associated with fish farms. This study revealed high variation among foraminiferal communities collected in the vicinity of fish farms and at distant locations, with evidence for species richness decreasing at impacted sites, especially visible in the RNA data.…”