An Assessment of Environmental Metabarcoding Protocols Aiming at Favoring Contemporary Biodiversity in Inventories of Deep-Sea Communities

The abyssal seafloor covers more than 50% of planet Earth and is a large reservoir of
still mostly undescribed biodiversity. It is increasingly targeted by resource-extraction
industries and yet is drastically understudied. In such remote and hard-to-access
ecosystems, environmental DNA (eDNA) metabarcoding is a useful and efficient tool
for studying biodiversity and implementing environmental impact assessments. Yet,
eDNA analysis outcomes may be biased toward describing past rather than present
communities as sediments contain both contemporary and ancient DNA. Using
commercially available kits, we investigated the impacts of five molecular processing
methods on eDNA metabarcoding biodiversity inventories targeting prokaryotes (16S),
unicellular eukaryotes (18S-V4), and metazoans (18S-V1, COI). As the size distribution
of ancient DNA is skewed toward small fragments, we evaluated the effect of removing
short DNA fragments via size selection and ethanol reconcentration using eDNA
extracted from 10 g of sediment at five deep-sea sites. We also compare communities
revealed by eDNA and environmental RNA (eRNA) co-extracted from 2 g of sediment
at the same sites. Results show that removing short DNA fragments does not affect
alpha and beta diversity estimates in any of the biological compartments investigated.
Results also confirm doubts regarding the possibility to better describe live communities
using eRNA. With ribosomal loci, eRNA, while resolving similar spatial patterns than
co-extracted eDNA, resulted in significantly higher richness estimates, supporting
hypotheses of increased persistence of ribosomal RNA (rRNA) in the environment
and unmeasured bias due to overabundance of rRNA and RNA release. With the
mitochondrial locus, eRNA detected lower metazoan richness and resolved fewer spatial
patterns than co-extracted eDNA, reflecting high messenger RNA lability. Results also
highlight the importance of using large amounts of sediment (10 g) for accurately
surveying eukaryotic diversity. We conclude that eDNA should be favored over eRNA for logistically realistic, repeatable, and reliable surveys and confirm that large sediment samples (10 g) deliver more complete and accurate assessments of benthic eukaryotic
biodiversity and that increasing the number of biological rather than technical replicates
is important to infer robust ecological patterns.