Assessing the potential of nematode metabarcoding for benthic monitoring of offshore oil platforms

J Pawlowski; K Cermakova; T Cordier; F Frontalini; L Apothéloz-Perret-Gentil; T Merzi

doi:10.1016/j.scitotenv.2024.173092

Assessing the potential of nematode metabarcoding for benthic monitoring of offshore oil platforms

Sci Total Environ. 2024 May 8:933:173092. doi: 10.1016/j.scitotenv.2024.173092. Online ahead of print.

Authors

J Pawlowski¹, K Cermakova², T Cordier³, F Frontalini⁴, L Apothéloz-Perret-Gentil², T Merzi⁵

Affiliations

¹ Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland; ID-Gene ecodiagnostics, Plan-les-Ouates, Switzerland. Electronic address: jan.pawlowski@unige.ch.
² ID-Gene ecodiagnostics, Plan-les-Ouates, Switzerland.
³ NORCE Climate and Environment, NORCE Norwegian Research Centre AS, Norway.
⁴ Department of Pure and Applied Sciences, University of Urbino "Carlo Bo", Urbino, Italy.
⁵ TotalEnergies OneTech, Centre Scientifique et Technique Jean Feger, Pau, France.

PMID: 38729369
DOI: 10.1016/j.scitotenv.2024.173092

Abstract

Environmental DNA metabarcoding is gaining momentum as a time and cost-effective tool for biomonitoring and environmental impact assessment. Yet, its use as a replacement for the conventional marine benthic monitoring based on morphological analysis of macrofauna is still challenging. Here we propose to study the meiofauna, which is much better represented in sediment DNA samples. We focus on nematodes, which are the most numerous and diverse group of meiofauna. Our aim is to assess the potential of nematode metabarcoding to monitor impacts associated with offshore oil platform activities. To achieve this goal, we used nematode-optimized marker (18S V1V2-Nema) and universal eukaryotic marker (18S V9) region to analyse 252 sediment DNA samples collected near three offshore oil platforms in the North Sea. For both markers, we analysed changes in alpha and beta diversity in relation to distance from the platforms and environmental variables. We also defined three impact classes based on selected environmental variables that are associated with oil extraction activities and used random forest classifiers to compare the predictive performance of both datasets. Our results show that alpha- and beta-diversity of nematodes varies with the increasing distance from the platforms. The variables directly related to platform activity, such as Ba and THC, strongly influence the nematode community. The nematode metabarcoding data provide more robust predictive models than eukaryotic data. Furthermore, the nematode community appears more stable in time and space, as illustrated by the overlap of nematode datasets obtained from the same platform three years apart. A significative negative correlation between distance and Shannon diversity also advocates for higher performance of the V1V2-Nema over the V9. Overall, these results suggest that the sensitivity of nematodes is higher compared to the eukaryotic community. Hence, nematode metabarcoding has the potential to become an effective tool for benthic monitoring in marine environment.

Keywords: 18S rRNA gene; Environmental impact assessment; Meiofauna; Sediment; eDNA.