Environmental metabarcoding reveals heterogeneous drivers of microbial eukaryote diversity in contrasting estuarine ecosystems

Abstract

Assessing how natural environmental drivers affect biodiversity underpins our understanding of the relationships between complex biotic and ecological factors in natural ecosystems. Of all ecosystems, anthropogenically important estuaries represent a ‘melting pot' of environmental stressors, typified by extreme salinity variations and associated biological complexity. Although existing models attempt to predict macroorganismal diversity over estuarine salinity gradients, attempts to model microbial biodiversity are limited for eukaryotes. Although diatoms commonly feature as bioindicator species, additional microbial eukaryotes represent a huge resource for assessing ecosystem health. Of these, meiofaunal communities may represent the optimal compromise between functional diversity that can be assessed using morphology and phenotype–environment interactions as compared with smaller life fractions. Here, using 454 Roche sequencing of the 18S nSSU barcode we investigate which of the local natural drivers are most strongly associated with microbial metazoan and sampled protist diversity across the full salinity gradient of the estuarine ecosystem. In order to investigate potential variation at the ecosystem scale, we compare two geographically proximate estuaries (Thames and Mersey, UK) with contrasting histories of anthropogenic stress. The data show that although community turnover is likely to be predictable, taxa are likely to respond to different environmental drivers and, in particular, hydrodynamics, salinity range and granulometry, according to varied life-history characteristics. At the ecosystem level, communities exhibited patterns of estuary-specific similarity within different salinity range habitats, highlighting the environmental sequencing biomonitoring potential of meiofauna, dispersal effects or both.

Worldwide Analysis of Sedimentary DNA Reveals Major Gaps in Taxonomic Knowledge of Deep-Sea Benthos

“…These uncertainties should not undermine the potential of metabarcoding to better understand the diversity of poorly known communities. Indeed, the total information obtained from a large number of taxa in parallel provides a good estimator of environmental community diversity that has many practical applications for ecosystem assessment and monitoring (Chariton et al, 2010(Chariton et al, , 2014Czernik et al, 2013;Stephenson et al, 2013;Lallias et al, 2014;Pawlowski et al, 2014;Willerslev et al, 2014;Guardiola et al, 2015;Lejzerowicz et al, 2015;Pochon et al, 2015;Boschen et al, 2016).…”

“…Data accessed 17.10.2014. tremendous diversity of eukaryotic organisms, metabarcoding is particularly useful because of its potential to explore the biodiversity of all taxa in parallel (Bik et al, 2012b). Such an approach has revealed novel biodiversity in various coastal environments (e.g., Chariton et al, 2010;Fonseca et al, 2010;Bik et al, 2012a;Lallias et al, 2014;Pawlowski et al, 2014;Cowart et al, 2015). However, despite the dynamic expansion of eDNA studies, little metabarcoding information is available for benthic diversity at bathyal and abyssal depths (Pawlowski et al, 2011).…”

Technological advancements and their importance for nematode identification

“…Most NGS-based nematode community studies have used the pyrosequencing method of the Roche 454 platform (Porazinska et al, 2009Creer et al, 2010;Bik et al, 2012;Lallias et al, 2015). The relatively longer read lengths generated with this platform made it more suitable for metabarcoding analysis.…”

“…Using metabarcoding, Lallias et al (2015) examined the variation in diversities of protists and microbial metazoans, including nematodes across two distinct estuaries in the UK. They utilised the same small subunit nuclear rRNA gene marker as the one used by Fonseca et al (2010) in a similar study on marine microbial eukaryotes.…”

DNA-based identification of aquatic invertebrates useful in the South African context?

“…In addition to successful detection, the authors report that this approach is less costly, both economically and in terms of effort (person-hours). 19 DNA metabarcoding is an approach which uses bulk DNA collections (such as faeces 20 , sediment meiofaunal communities 21 and eDNA 2 ) coupled with next generation sequencing to obtain an overview of the organisms which are present in an environment as a whole. Instead of targeting one or a few species, this approach aims to give a more holistic view of ecosystem composition.…”