Bioinformatic pipelines combining denoising and clustering tools allow for more comprehensive prokaryotic and eukaryotic metabarcoding.

Environmental DNA metabarcoding is a powerful tool for studying biodiversity. However, bioinformatic approaches need to adjust to the diversity of taxonomic compartments targeted as well as to each barcode gene specificities. We built and tested a pipeline based on read correction with DADA2 allowing analysing metabarcoding data from prokaryotic (16S) and eukaryotic (18S, COI) life compartments. We implemented the option to cluster amplicon sequence variants (ASVs) into operational taxonomic units (OTUs) with swarm, a network-based clustering algorithm, and the option to curate ASVs/OTUs using LULU. Finally, taxonomic assignment was implemented via the Ribosomal Database Project Bayesian classifier (RDP) and BLAST. We validated this pipeline with ribosomal and mitochondrial markers using metazoan mock communities and 42 deep-sea sediment samples. The results show that ASVs and OTUs describe different levels of biotic diversity, the choice of which depends on the research questions. They underline the advantages and complementarity of clustering and LULU-curation for producing metazoan biodiversity inventories at a level approaching the one obtained using morphological criteria. While clustering removes intraspecific variation, LULU effectively removes spurious clusters, originating from errors or intragenomic variability. Swarm clustering affected alpha and beta diversity differently depending on genetic marker. Specifically, d-values > 1 appeared to be less appropriate with 18S for metazoans. Similarly, increasing LULU's minimum ratio level proved essential to avoid losing species in sample-poor data sets. Comparing BLAST and RDP underlined that accurate assignments of deep-sea species can be obtained with RDP, but highlighted the need for a concerted effort to build comprehensive, ecosystem-specific databases.

Modelling technical and biological biases in macroinvertebrate community assessment from bulk preservative using multiple metabarcoding markers.

DNA metabarcoding from the ethanol used to store macroinvertebrate bulk samples is a convenient methodological option in molecular biodiversity assessment and biomonitoring of aquatic ecosystems, as it preserves specimens and reduces problems associated with sample sorting. However, this method may be affected by errors and biases, which need to be thoroughly quantified before it can be mainstreamed into biomonitoring programmes. Here, we used 80 unsorted macroinvertebrate samples collected in Portugal under a Water Framework Directive monitoring programme, to compare community diversity and taxonomic composition metrics estimated through morphotaxonomy versus metabarcoding from storage ethanol using three markers (COI-M19BR2, 16S-Inse01 and 18S-Euka02) and a multimarker approach. A preliminary in silico analysis showed that the three markers were adequate for the target taxa, with detection failures related primarily to the lack of adequate barcodes in public databases. Metabarcoding of ethanol samples retrieved far less taxa per site (alpha diversity) than morphotaxonomy, albeit with smaller differences for COI-M19BR2 and the multimarker approach, while estimates of taxa turnover (beta diversity) among sites were similar across methods. Using generalized linear mixed models, we found that after controlling for differences in read coverage across samples, the probability of detection of a taxon was positively related to its proportional abundance, and negatively so to the presence of heavily sclerotized exoskeleton (e.g., Coleoptera). Overall, using our experimental protocol with different template dilutions, the COI marker showed the best performance, but we recommend the use of a multimarker approach to detect a wider range of taxa in freshwater macroinvertebrate samples. Further methodological development and optimization efforts are needed to reduce biases associated with body armouring and rarity in some macroinvertebrate taxa.

Diversity and stability of coral endolithic microbial communities at a naturally high pCO2 reef.

The health and functioning of reef-building corals is dependent on a balanced association with prokaryotic and eukaryotic microbes. The coral skeleton harbours numerous endolithic microbes, but their diversity, ecological roles and responses to environmental stress, including ocean acidification (OA), are not well characterized. This study tests whether pH affects the diversity and structure of prokaryotic and eukaryotic algal communities associated with skeletons of Porites spp. using targeted amplicon (16S rRNA gene, UPA and tufA) sequencing. We found that the composition of endolithic communities in the massive coral Porites spp. inhabiting a naturally high pCO2 reef (avg. pCO2 811 µatm) is not significantly different from corals inhabiting reference sites (avg. pCO2 357 µatm), suggesting that these microbiomes are less disturbed by OA than previously thought. Possible explanations may be that the endolithic microhabitat is highly homeostatic or that the endolithic micro-organisms are well adapted to a wide pH range. Some of the microbial taxa identified include nitrogen-fixing bacteria (Rhizobiales and cyanobacteria), algicidal bacteria in the phylum Bacteroidetes, symbiotic bacteria in the family Endozoicomoniaceae, and endolithic green algae, considered the major microbial agent of reef bioerosion. Additionally, we test whether host species has an effect on the endolithic community structure. We show that the endolithic community of massive Porites spp. is substantially different and more diverse than that found in skeletons of the branching species Seriatopora hystrix and Pocillopora damicornis. This study reveals highly diverse and structured microbial communities in Porites spp. skeletons that are possibly resilient to OA.