Comparing species detection success between molecular markers in DNA metabarcoding of coastal macroinvertebrates

Comprehensive DNA metabarcoding-based detection of non-indigenous invertebrates in recreational marinas through a multi-substrate approach

eDNA metabarcoding has been increasingly employed in the monitoring of marine invertebrate non-indigenous species (NIS), in particular using filtered seawater. However, comprehensive detection of all NIS may require a diversity of sampling substrates. To assess the effectiveness of 5 sample types (hard and artificial substrates, water, zooplankton) on the recovery of invertebrates' diversity, two marinas were monitored over three time points, using COI and 18S rRNA genes as DNA metabarcoding markers. We detected a total of 628 species and 23 NIS, with only up to 9% species and 17% of NIS detected by all sample types. Hard and artificial substrates were similar to each other but displayed the most significant difference in invertebrate recovery when compared to water eDNA and zooplankton. Five NIS are potential first records for Portugal. No NIS were detected in all sample types and seasons, highlighting the need for varied sampling approaches, and consideration of temporal variation for comprehensive marine NIS surveillance.

Assessing the Seasonal and Spatial Dynamics of Zooplankton through DNA Metabarcoding in a Temperate Estuary

Zooplankton are key components of estuarine trophic networks. However, routine monitoring is hindered by the difficulty of morphology-based identification. DNA-based methods allow us to circumvent some of these hurdles, providing precise species identifications regardless of the taxonomic expertise of the investigator or the developmental stage of the specimens. However, the process is dependent on the completeness of the reference libraries. In this study, we sought to evaluate the potential of DNA metabarcoding to assess the seasonal (summer, autumn, and early spring) and spatial dynamics of zooplankton (four locations spanning ca. 6 km) in the Lima estuary (NW Portugal). Two genetic markers were used: the cytochrome c oxidase subunit I and the V4 hypervariable region of the ribosomal 18S rRNA genes. Overall, 327 species were recovered, and both markers displayed minute overlap (7% were detected with both markers). Species richness, composition, and taxonomic distinctness were majorly influenced by the season, with a declining tendency from summer (highest number of exclusive species, n = 74) to spring. Second to season, the taxa composition was influenced by spatial variation where the most downstream site displayed the highest number of exclusive species, n = 53. A total of 16 non-indigenous species were detected using metabarcoding, but only one (Austrominus modestus) has been documented out in the estuary. In conclusion, both the seasonal and spatial gradients influenced the recovered richness, composition, and taxonomic distinctness, confirming the great aptitude of DNA metabarcoding for providing higher density monitoring and shedding new light on the composition and dynamics of complex zooplankton communities.

DNA metabarcoding reveals impact of local recruitment, dispersal, and hydroperiod on assembly of a zooplankton metacommunity

Understanding the environmental impact on the assembly of local communities in relation to their spatial and temporal connectivity is still a challenge in metacommunity ecology. This study aims to unravel underlying metacommunity processes and environmental factors that result in observed zooplankton communities. Unlike most metacommunity studies, we jointly examine active and dormant zooplankton communities using a DNA metabarcoding approach to overcome limitations of morphological species identification. We applied two-fragment (COI and 18S) metabarcoding to monitor communities of 24 kettle holes over a two-year period to unravel (i) spatial and temporal connectivity of the communities, (ii) environmental factors influencing local communities, and (iii) dominant underlying metacommunity processes in this system. We found a strong separation of zooplankton communities from kettle holes of different hydroperiods (degree of permanency) throughout the season, while the community composition within single kettle holes did not differ between years. Species richness was primarily dependent on pH and permanency, while species diversity (Shannon Index) was influenced by kettle hole location. Community composition was impacted by kettle hole size and surrounding field crops. Environmental processes dominated temporal and spatial processes. Sediment communities showed a different composition compared to water samples but did not differ between ephemeral and permanent kettle holes. Our results suggest that communities are mainly structured by environmental filtering based on pH, kettle hole size, surrounding field crops, and permanency. Environmental filtering based on specific conditions in individual kettle holes seems to be the dominant process in community assembly in the studied zooplankton metacommunity.

The effect of metabarcoding 18S rRNA region choice on diversity of microeukaryotes including phytoplankton

Metabarcoding using high throughput sequencing of amplicons of the 18S rRNA gene is one of the widely used methods for assessing the diversity of microeukaryotes in various ecosystems. We investigated the effectiveness of the V4 and V8-V9 regions of the 18S rRNA gene by comparing the results of metabarcoding microeukaryotic communities using the DADA2 (ASV), USEARCH-UNOISE3 (ZOTU), and USEARCH-UPARSE (OTU with 97% similarity) algorithms. Both regions showed similar levels of genetic variability and taxa identification accuracy. Richness for DADA2 datasets of both regions was lower than for UNOISE3 and UPARSE datasets, which is due to more accurate error correction in amplicons. Microeukaryotic communities (autotrophs and heterotrophs) structure identified using both regions showed a significant relationship with phytoplankton (autotrophs) communities structure based on microscopy in a seasonal freshwater sample series. The strongest relationship was found between the phytoplankton species and V8-V9 ASVs produced by DADA2.

Maximizing the reliability and the number of species assignments in metabarcoding studies using a curated regional library and a public repository

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.