Combining multi-marker metabarcoding and digital holography to describe eukaryotic plankton across the Newfoundland Shelf

Abstract

The planktonic diversity throughout the oceans is vital to ecosystem functioning and linked to environmental change. Plankton monitoring tools have advanced considerably with high-throughput in-situ digital cameras and genomic sequencing, opening new challenges for high-frequency observations of community composition, structure, and species discovery. Here, we combine multi-marker metabarcoding based on nuclear 18S (V4) and plastidial 16S (V4–V5) rRNA gene amplicons with a digital in-line holographic microscope to provide a synoptic diversity survey of eukaryotic plankton along the Newfoundland Shelf (Canada) during the winter transition phase of the North Atlantic bloom phenomenon. Metabarcoding revealed a rich eukaryotic diversity unidentifiable in the imaging samples, confirming the presence of ecologically important saprophytic protists which were unclassifiable in matching images, and detecting important groups unobserved or taxonomically unresolved during similar sequencing campaigns in the Northwest Atlantic Ocean. In turn, imaging analysis provided quantitative observations of widely prevalent plankton from every trophic level. Despite contrasting plankton compositions portrayed by each sampling method, both capture broad spatial differences between the northern and southern sectors of the Newfoundland Shelf and suggest complementary estimations of important features in eukaryotic assemblages. Future tasks will involve standardizing digital imaging and metabarcoding for wider use and consistent, comparable ocean observations.

Morphological and taxonomic diversity of mesozooplankton is an important driver of carbon export fluxes in the ocean

“…Each of these approaches has uncertainties (Monferrer et al, 2022) but when combined, many resolution issues are resolved. For example, metabarcoding fills in some of the limited size spectrum resolution of imaging techniques (MacNeil et al, 2022) and allows a joint study of zooplankton communities taxonomic and functional aspects.…”

“…However, it is not free of several technical biases: barcode and primers selection, DNA amplification's efficiency, bioinformatics pipelines' parameters choice, or reference database quality are known sources of biases (Harvey et al., 2017). This method produces compositional data, meaning that values inferred from counts of reads for any taxon will be influenced by the ones from other taxa (Brisbin et al., 2020; MacNeil et al., 2022). Hence, the quantitative property of these data is still controversial and hard to evaluate (Ershova et al., 2021), necessitating verification by imaging methods (Harvey et al., 2017).…”

“…Each of these approaches has uncertainties (Monferrer et al., 2022) but when combined, many resolution issues are resolved. For example, metabarcoding fills in some of the limited size spectrum resolution of imaging techniques (MacNeil et al., 2022) and allows a joint study of zooplankton communities taxonomic and functional aspects. Previous studies have tried to assess the quantitative property of metabarcoding by comparing counts of sequence reads to (relative) biomass (e.g., Djurhuus et al., 2018; Durkin et al., 2022 on particles) or to (relative) abundance (e.g., Ibarbalz et al., 2019; Rey et al., 2020) for various zooplankton taxonomic groups but results from each approach seldom agree (Harvey et al., 2017), requiring further studies.…”

Glimpse of past dynamics: A new set of phytoplankton primers for sedaDNA

“…In MacNeil et al. (2022), the detected phytoplankton species and families differed between 16S and 18S rRNA gene fragments. In our example, the detection of cyanobacteria species with potentially ecosystem‐wide effects is frequently desired for inferences about the status of ecosystems.…”

Digital in-line holographic microscopy for label-free identification and tracking of biological cells

“…Compared to other 3D imaging techniques, DIHM enables simultaneous measurement of multiple biological cells located at different depth-wise positions. It can analyze not only unicellular organisms but also multicellular organisms, including marine plankton [ 27 , 49 , 50 , 226 , 227 ], embryos [ 228 ], and stem cells [ 229 , 230 ]. Additionally, DIHM allows visualization of transparent thin tissue structures, such as human breast carcinoma [ 231 ] and human hepatocellular carcinoma tissues [ 232 ].…”