Metabarcoding of marine nematodes - evaluation of similarity scores used in alignment-based taxonomy assignment approach

Mitochondrial cytochrome c oxidase subunit I (COI) metabarcoding of Foraminifera communities using taxon-specific primers

Foraminifera are a species-rich phylum of rhizarian protists that are highly abundant in most marine environments. Molecular methods such as metabarcoding have revealed a high, yet undescribed diversity of Foraminifera. However, so far only one molecular marker, the 18S ribosomal RNA, was available for metabarcoding studies on Foraminifera. Primers that allow amplification of foraminiferal mitochondrial cytochrome oxidase I (COI) and identification of Foraminifera species were recently published. Here we test the performance of these primers for the amplification of whole foraminiferal communities, and compare their performance to that of the highly degenerate LerayXT primers, which amplify the same COI region in a wide range of eukaryotes. We applied metabarcoding to 48 samples taken along three transects spanning a North Sea beach in the Netherlands from dunes to the low tide level, and analysed both sediment samples and meiofauna samples, which contained taxa between 42 µm and 1 mm in body size obtained by decantation from sand samples. We used single-cell metabarcoding (Girard et al., 2022) to generate a COI reference library containing 32 species of Foraminifera, and used this to taxonomically annotate our community metabarcoding data. Our analyses show that the highly degenerate LerayXT primers do not amplify Foraminifera, while the Foraminifera primers are highly Foraminifera- specific, with about 90% of reads assigned to Foraminifera and amplifying taxa from all major groups, i.e., monothalamids, Globothalamea, and Tubothalamea. We identified 176 Foraminifera ASVs and found a change in Foraminifera community composition along the beach transects from high tide to low tide level, and a dominance of single-chambered monothalamid Foraminifera. Our results highlight that COI metabarcoding can be a powerful tool for assessing Foraminiferal communities.

Sensory ecology of the frog-eating bat, Trachops cirrhosus, from DNA metabarcoding and behavior

Metabarcoding of prey DNA from fecal samples can be used to design behavioral experiments to study the foraging behavior and sensory ecology of predators. The frog-eating bat, Trachops cirrhosus, eavesdrops on the mating calls of its anuran prey. We captured wild T. cirrhosus and identified prey remains in the bats’ fecal samples using DNA metabarcoding of two gene regions (CO1 and 16S). Bats were preying on frogs previously unknown in their diet, such as species in the genus Pristimantis, which occurred in 29% of T. cirrhosus samples. Twenty-three percent of samples also contained DNA of Anolis lizards. We additionally report apparently rare predation events on hummingbirds and heterospecific bats. We used results from metabarcoding to design acoustic and 3D model stimuli to present to bats in behavioral experiments. We show predatory responses by T. cirrhosus to the calls of the frog Pristimantis taeniatus and to the rustling sounds of anoles moving through leaf-litter, as well as attacks on a stuffed hummingbird and a plastic anole model. The combination of species-specific dietary information from metabarcoding analyses with behavioral responses to prey cues provides a unique window into the foraging ecology of predators that are difficult to observe in the wild.

Comparison of morphological, DNA barcoding, and metabarcoding characterizations of freshwater nematode communities

Biomonitoring approaches and investigations of many ecological questions require assessments of the biodiversity of a given habitat. Small organisms, ranging from protozoans to metazoans, are of great ecological importance and comprise a major share of the planet's biodiversity but they are extremely difficult to identify, due to their minute body sizes and indistinct structures. Thus, most biodiversity studies that include small organisms draw on several methods for species delimitation, ranging from traditional microscopy to molecular techniques. In this study, we compared the efficiency of these methods by analyzing a community of nematodes. Specifically, we evaluated the performances of traditional morphological identification, single-specimen barcoding (Sanger sequencing), and metabarcoding in the identification of 1500 nematodes from sediment samples. The molecular approaches were based on the analysis of the 28S ribosomal large and 18S small subunits (LSU and SSU). The morphological analysis resulted in the determination of 22 nematode species. Barcoding identified a comparable number of operational taxonomic units (OTUs) based on 28S rDNA (n = 20) and fewer OTUs based on 18S rDNA (n = 12). Metabarcoding identified a higher OTU number but fewer amplicon sequence variants (AVSs) (n = 48 OTUs, n = 17 ASVs for 28S rDNA, and n = 31 OTUs, n = 6 ASVs for 18S rDNA). Between the three approaches (morphology, barcoding, and metabarcoding), only three species (13.6%) were shared. This lack of taxonomic resolution hinders reliable community identifications to the species level. Further database curation will ensure the effective use of molecular species identification.

Improved phylogenomic sampling of free-living nematodes enhances resolution of higher-level nematode phylogeny

Background

Nematodes are among the most diverse and abundant metazoans on Earth, but research on them has been biased toward parasitic taxa and model organisms. Free-living nematodes, particularly from the clades Enoplia and Dorylaimia, have been underrepresented in genome-scale phylogenetic analyses to date, leading to poor resolution of deep relationships within the phylum.

Results

We supplemented publicly available data by sequencing transcriptomes of nine free-living nematodes and two important outgroups and conducted a phylum-wide phylogenomic analysis including a total of 108 nematodes. Analysis of a dataset generated using a conservative orthology inference strategy resulted in a matrix with a high proportion of missing data and moderate to weak support for branching within and placement of Enoplia. A less conservative orthology inference approach recovered more genes and resulted in higher support for the deepest splits within Nematoda, recovering Enoplia as the sister taxon to the rest of Nematoda. Relationships within major clades were similar to those found in previously published studies based on 18S rDNA.

Conclusions

Expanded transcriptome sequencing of free-living nematodes has contributed to better resolution among deep nematode lineages, though the dataset is still strongly biased toward parasites. Inclusion of more free-living nematodes in future phylogenomic analyses will allow a clearer understanding of many interesting aspects of nematode evolution, such as morphological and molecular adaptations to parasitism and whether nematodes originated in a marine or terrestrial environment.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1444-x) contains supplementary material, which is available to authorized users.

Taxonomy assignment approach determines the efficiency of identification of OTUs in marine nematodes

Precision and reliability of barcode-based biodiversity assessment can be affected at several steps during acquisition and analysis of data. Identification of operational taxonomic units (OTUs) is one of the crucial steps in the process and can be accomplished using several different approaches, namely, alignment-based, probabilistic, tree-based and phylogeny-based. The number of identified sequences in the reference databases affects the precision of identification. This paper compares the identification of marine nematode OTUs using alignment-based, tree-based and phylogeny-based approaches. Because the nematode reference dataset is limited in its taxonomic scope, OTUs can only be assigned to higher taxonomic categories, families. The phylogeny-based approach using the evolutionary placement algorithm provided the largest number of positively assigned OTUs and was least affected by erroneous sequences and limitations of reference data, compared to alignment-based and tree-based approaches.