First evaluation of foraminiferal metabarcoding for monitoring environmental impact from an offshore oil drilling site

Abstract

At present, environmental impacts from offshore oil and gas activities are partly determined by measuring changes in macrofauna diversity. Morphological identification of macrofauna is time-consuming, expensive and dependent on taxonomic expertise. In this study, we evaluated the applicability of using foraminiferal-specific metabarcoding for routine monitoring. Sediment samples were collected along distance gradients from two oil platforms off Taranaki (New Zealand) and their physico-chemical properties, foraminiferal environmental DNA/RNA, and macrofaunal composition analyzed. Macrofaunal and foraminiferal assemblages showed similar shifts along impact gradients, but responded differently to environmental perturbations. Macrofauna were affected by hypoxia, whereas sediment grain size appeared to drive shifts in foraminifera. We identified eight foraminiferal molecular operational taxonomic units that have potential to be used as bioindicator taxa. Our results show that metabarcoding represents an effective tool for assessing foraminiferal communities near offshore oil and gas platforms, and that it can be used to complement current monitoring techniques.

Methods for the extraction, storage, amplification and sequencing of DNA from environmental samples

“…Several protist taxa (diatoms, foraminifera, ciliates and testate amoebae) are already under investigation, or in use as ecological indicators. For example, foraminiferal metabarcoding has been used to assess the impact of activities as diverse as salmon farming (Pochon et al 2015a) and oil and gas exploration (Laroche et al 2016) on the health of aquatic environments. Such studies could greatly improve our ability to assess environmental impacts .…”

Metabarcoding monitoring analysis: the pros and cons of using co-extracted environmental DNA and RNA data to assess offshore oil production impacts on benthic communities

“…A limited number have also evaluated data from co-extracted eRNA products (e.g., Pawlowski et al, 2014; Pawlowski et al, 2016a; Visco et al, 2015; Dowle et al, 2015; Pochon et al, 2015; Laroche et al, 2016). Because RNA deteriorates rapidly after cell death, eRNA likely provides a more accurate representation of viable communities (Mengoni et al, 2005).…”

“…Blazewicz et al (2013) suggested that the relative concentration of RNA in the environment provides a robust indication of the growth and adaptation potential of microbial communities. In general, when environmental metabarcoding studies have used both eDNA and eRNA they have found slightly stronger correlations between community data generated from eRNA and environmental conditions (Pawlowski et al, 2014; Pawlowski et al, 2016a; Visco et al, 2015; Dowle et al, 2015; Pochon et al, 2015; Laroche et al, 2016). However, working with eRNA adds additional complexities and expenses related to sampling and laboratory analysis including extra precaution during sampling, transport and storage to avoid degradation.…”

“…Greater taxon richness derived from eDNA data can be explained through the detection of DNA from dead organisms as well as extracellular DNA (free-floating or legacy DNA) that has bound to sediment or other particles. However, many studies report an important number of taxa only detected from eRNA (e.g., Pawlowski et al, 2014; Pawlowski et al, 2016a; Pochon et al, 2015; Laroche et al, 2016; Hu et al, 2016). These OTUs may be the result of PCR/sequencing artefacts or the detection of rare but very active taxa.…”

“…These OTUs may be the result of PCR/sequencing artefacts or the detection of rare but very active taxa. To date, most studies, have dealt with this by only retaining the data of taxa present in both eDNA/eRNA datasets across the entire sample set (Pawlowski et al, 2014; Pawlowski et al, 2016a; Dowle et al, 2015; Pochon et al, 2015; Laroche et al, 2016), or within the same sites (Hu et al, 2016). …”