Investigating eDNA/eRNA metabarcoding methods for assessing impacts of offshore oil and gas activities on benthic ecosystems

Abstract

Increased offshore mining activities are putting pressure on benthic ecosystems. There is a growing need for effective benthic monitoring techniques to assess environmental changes. Current benthic survey approaches are based on the collection, identification and enumeration of macrofaunal assemblages using microscopy, which is laborious, costly, and solely relies on expert taxonomic knowledge. Recent advancements in high-throughput sequencing (HTS) technologies allow for species diversity – from bacteria to metazoa – to be estimated rapidly from small amounts of sediment using a technique known as environmental DNA (eDNA) metabarcoding. Because of its costefficiency, metabarcoding could represent an appealing option to meet the increasing need of largescale environmental surveys and allow for more comprehensive monitoring programs. The research presented in this thesis aimed to compare metabarcoding and traditional (microscopy-based) approaches for monitoring the impact of offshore oil and gas (O&G) drilling and production activities. Different HTS data pre-treatment techniques and the benefits of using both eDNA and eRNA were evaluated, in concert with community changes across different taxonomic groups (bacteria [16S ribosomal RNA], foraminifera [18S ribosomal RNA] and other meio-infaunal taxa [18S ribosomal RNA]). Alternative ways for analyzing metabarcoding data that could provide additional information to habitat assessment, such as inferred metabolic pathways and co-occurrence network topologies, were also explored. The results showed that eRNA data provided stronger correlations between alpha-diversity metrics and environmental data, while read abundance information from eDNA may represent a better proxy for beta-diversity assessments. Using co-extracted eRNA to trim concomitant eDNA data proved to be particularly useful to discard sequence read originating from legacy DNA and or PCR/sequencing artefacts, and for improving the overall sensitivity of the metabarcoding approach. All taxonomic groups assessed were significantly impacted by O&G activities, with bacteria expressing the strongest response, followed by foraminifera, macrofauna (assessed by morphology) and meiofauna. Phylogenetic methods predicting the genomic and functional traits of organisms improved microbial diversity estimates by adjusting 16S rRNA copy numbers. A specific community network ‘signature’ could be associated with impacted sites where the ratio of positive interactions was reduced, and the cohesion among community members increased. The findings presented in this thesis contribute to the field of marine benthic monitoring and demonstrate the considerable value of incorporating metabarcoding methods for effective impact assessment of offshore mining activities. These data extend our general knowledge on metabarcoding tools, in particular the intrinsic differences between eDNA and eRNA data and the advantages of analysing them simultaneously. This work also highlights the benefits of using predictive genomic and co-occurrence network information to complement traditional taxonomic composition analysis. These results suggest that when assessing the impact of O&G activities on eDNA and eRNA signals, metabarcoding is at least as effective as traditional morphological surveys, represents a more encompassing approach, and increases the ability to identify and characterize environmental changes.