Using a Metabarcoding Approach to Evaluate the Impacts of Nanoplastic Particles on Benthic Meiofauna Communities
Using a Metabarcoding Approach to Evaluate the Impacts of Nanoplastic Particles on Benthic Meiofauna Communities
Abstract:
Nanomaterials are formed from a wide range of substances including ubiquitous plastics. As the abundance of plastic increases in marine systems, the adverse biological and ecological effects of each form of plastic needs to be evaluated to address potential risks. Nanoplastic particles (NPs) are of growing concern and can enter marine systems through intentional releases from manufacturing plants and from fragmentation of larger plastics present in the environment. Marine sediments act as sinks for contaminants, including nanoplastics, and are rich habitats for benthic meiofauna communities that presumably interact with NPs. However, little is known about the effects of nanoplastics to individual organisms or how NPs affect community and ecosystem diversity. Conventional morphological identification of benthic organisms is often a time-consuming process; however, community diversity can be rapidly assessed using molecular methods such as metabarcoding. Metabarcoding utilizes high-throughput sequencing to assess community structure from environmental DNA/RNA. Therefore, the objective of this study is to use an RNA metabarcoding approach to investigate the effects of nanoplastic particles on benthic meiofaunal community diversity. Sediment cores (mesocosms) were collected from an estuary in Rhode Island (USA) and exposed to 900 nm polystyrene beads at concentrations of 0, 0.1, 1, 10, or 100 mg/kg dry weight in sediment for two weeks. RNA was extracted from the top sediment layer, 18S and CO1 were PCR-amplified, and then amplicons were sequenced on an Illumina platform. In this study, the value of using RNA as a genetic template to achieve a more accurate representation of meiofaunal communities was evaluated. To our knowledge, this is the first dose-response study of nanoplastic particles at a community level, and it also continues to show the utility of using community endpoints to assess the impacts of nanomaterials.