Using eRNA/eDNA metabarcoding to detect community-level impacts of nanoplastic exposure to benthic estuarine ecosystems

Plastic particles are ubiquitous in marine systems and fragment into smaller pieces, such as nanoplastics (NPs). The effects of NPs on marine organisms are of growing concern but are not well understood. Marine sediments act as a sink for many contaminants, like microplastics, and are rich habitats for benthic micro- and meiofauna which are ecologically-important components of marine food webs; however, little is known about the sensitivities of specific organisms to NPs or the effects on community diversity and composition. Utilizing molecular methods, such as metabarcoding of environmental DNA/RNA, allows for the rapid and comprehensive detection of microscopic organisms via high-throughput sequencing to assess adverse effects at the community level. The objective of this study was to use a metabarcoding approach to investigate the effects of NPs on benthic microand meiofaunal community diversity. Mesocosms were created with sediment cores collected from the Narrow River estuary (Rhode Island, USA) and exposed to 900 nm diameter weathered polystyrene beads at concentrations of 0.1, 1, 10, or 100 mg/kg dry weight in sediment for two weeks. Following exposure, RNA and DNA were co-extracted from the sediment, RNA was reverse-transcribed, 18S and COI markers were PCR-amplified, and amplicons were sequenced on an Illumina MiSeq. Using the 18S marker and eRNA template, increases to a-diversity and significant differences to 13-diversity were observed in the highest NP exposures relative to the control. Observed differences in community composition were driven by the differential abundance of several types of protists and arthropods. Significant dose-dependent shifts in composition were observed in 13-diversity Jaccard and Unweighted-Unifrac metrics with the 18S marker using the RNA template. To our knowledge, this is the first demonstration of a dose-response relationship for NPs at a community level, and it highlights the value of using community-level endpoints to assess environmental impacts of nanoparticles.