Eukaryotic biodiversity and spatial patterns in the Clarion-Clipperton Zone and other Abyssal regions: Insights from sediment DNA and RNA metabarcoding

The abyssal seafloor is a mosaic of highly diverse habitats that represent the least known marine ecosystems on Earth. Some regions enriched in natural resources, such as polymetallic nodules in the Clarion-Clipperton Zone (CCZ), attract much interest because of their huge commercial potential. Since nodule mining will be destructive, baseline data are necessary to measure its impact on benthic communities. Hence, we conducted an environmental DNA and RNA metabarcoding survey of CCZ biodiversity targeting microbial and meiofaunal eukaryotes that are the least known component of the deep-sea benthos. We analyzed two 18S rRNA gene regions targeting eukaryotes with a focus on Foraminifera (37F) and metazoans (V1V2), sequenced from 310 surface-sediment samples from the CCZ and other abyssal regions. Our results confirm huge unknown deep-sea biodiversity. Over 60% of benthic foraminiferal and almost a third of eukaryotic operational taxonomic units (OTUs) could not be assigned to a known taxon. Benthic Foraminifera are more common in CCZ samples than metazoans and dominated by clades that are only known from environmental surveys. The most striking results are the uniqueness of CCZ areas, both datasets being characterized by a high number of OTUs exclusive to the CCZ, as well as greater beta diversity compared to other abyssal regions. The alpha diversity in the CCZ is high and correlated with water depth and terrain complexity. Topography was important at a local scale, with communities at CCZ stations located in depressions more diverse and heterogeneous than those located on slopes. This could result from eDNA accumulation, justifying the interim use of eRNA for more accurate biomonitoring surveys. Our descriptions not only support previous findings and consolidate our general understanding of deep-sea ecosystems, but also provide a data resource inviting further taxon-specific and large-scale modeling studies. We foresee that metabarcoding will be useful for deep-sea biomonitoring efforts to consider the diversity of small taxa, but it must be validated based on ground truthing data or experimental studies

Climate change considerations are fundamental to management of deep‐sea resource extraction

Climate change manifestation in the ocean, through warming, oxygen loss, increasing acidification, and changing particulate organic carbon flux (one metric of altered food supply), is projected to affect most deep‐ocean ecosystems concomitantly with increasing direct human disturbance. Climate drivers will alter deep‐sea biodiversity and associated ecosystem services, and may interact with disturbance from resource extraction activities or even climate geoengineering. We suggest that to ensure the effective management of increasing use of the deep ocean (e.g., for bottom fishing, oil and gas extraction, and deep‐seabed mining), environmental management and developing regulations must consider climate change. Strategic planning, impact assessment and monitoring, spatial management, application of the precautionary approach, and full‐cost accounting of extraction activities should embrace climate consciousness. Coupled climate and biological modeling approaches applied in the water and on the seafloor can help accomplish this goal. For example, Earth‐System Model projections of climate‐change parameters at the seafloor reveal heterogeneity in projected climate hazard and time of emergence (beyond natural variability) in regions targeted for deep‐seabed mining. Models that combine climate‐induced changes in ocean circulation with particle tracking predict altered transport of early life stages (larvae) under climate change. Habitat suitability models can help assess the consequences of altered larval dispersal, predict climate refugia, and identify vulnerable regions for multiple species under climate change. Engaging the deep observing community can support the necessary data provisioning to mainstream climate into the development of environmental management plans. To illustrate this approach, we focus on deep‐seabed mining and the International Seabed Authority, whose mandates include regulation of all mineral‐related activities in international waters and protecting the marine environment from the harmful effects of mining. However, achieving deep‐ocean sustainability under the UN Sustainable Development Goals will require integration of climate consideration across all policy sectors.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors. Global Change Biology published by John Wiley & Sons Lt

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.Peer reviewe

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies.IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.</p

Towards comprehensive surveys of environmental eukaryotic diversity using high-throughput sequencing

La description rapide, exhaustive et précise de la diversité des communautés biologiques reste un challenge majeur en écologie. L'approche de séquençage à haut-débit d'ADN ribosomiques extraits de l'environnement et amplifiés par PCR (métabarcoding) est prometteuse car elle permet d'identifier de nombreuses espèces dans de nombreux échantillons, mais reste affectée par de nombreux biais techniques et biologiques. Ma thèse sur articles est basée sur les modèles biotique eucaryote (notamment foraminifère) et abiotique marin benthique (notamment abyssal) afin (i) de documenter certains biais et de caractériser les signaux écologiques dans les données de métabarcoding et (ii) d'appliquer le métabarcoding pour reconstruire et surveiller des écosystèmes passés et modernes, respectivement. J'identifie la diversité moléculaire des organismes vivants en ciblant l'ARN environnemental, celle des organismes non-fossiles en ciblant de petits fragments d'ADN ancien et celle de potentiels bioindicateurs de pollution en comparaison avec l'approche traditionnelle. La grande diversité des approches de métabarcoding reste inexplorée

Algal pigments in Southern Ocean abyssal foraminiferans indicate pelagobenthic coupling.

The cytoplasm of four species of abyssal benthic foraminiferans from the Southern Ocean (around 51°S; 12°W and 50°S; 39°W) was analysed by High Performance Liquid Chromatography (HPLC) and found to contain large concentrations of algal pigments and their degradation products. The composition of the algal pigments in the foraminiferan cytoplasm reflected the plankton community at the surface. Some foraminiferans contained high ratios of chlorophyll a/degraded pigments because they were feeding on fresher phytodetritus. Other foraminiferans contained only degraded pigments which shows that they utilized degraded phytodetritus. The concentration of algal pigment and corresponding degradation products in the foraminiferan cytoplasm is much higher than in the surrounding sediment. It shows that the foraminiferans collect a diluted and sparse food resource and concentrate it as they build up their cytoplasm. This ability contributes to the understanding of the great quantitative success of foraminiferans in the deep sea. Benthic foraminiferans are a food source for many abyssal metazoans. They form a link between the degraded food resources, phytodetritus, back to the active metazoan food chains

Next-Generation Environmental Diversity Surveys of Foraminifera: Preparing the Future

International audienceForaminifera are commonly defined as marine testate protists, and their diversity is mainly assessed on the basis of the morphology of their agglutinated or mineralized tests. Diversity surveys based on environmental DNA (eDNA) have dramatically changed this view by revealing an unexpected diversity of naked and organic-walled lineages as well as detecting foraminiferal lineages in soil and freshwater environments. Moreover, single-cell analyses have allowed discrimination among genetically distinctive types within almost every described morphospecies. In view of these studies, the foraminiferal diversity appeared to be largely underestimated, but its accurate estimation was impeded by the low speed and coverage of a cloning-based eDNA approach. With the advent of high-throughput sequencing (HTS) technologies, these limitations disappeared in favor of exhaustive descriptions of foraminiferal diversity in numerous samples. Yet, the biases and errors identified in early HTS studies raised some questions about the accuracy of HTS data and their biological interpretation. Among the most controversial issues affecting the reliability of HTS diversity estimates are (1) the impact of technical and biological biases, (2) the sensitivity and specificity of taxonomic sequence assignment, (3) the ability to distinguish rare species, and (4) the quantitative interpretation of HTS data. Here, we document the lessons learned from previous HTS surveys and present the current advances and applications focusing on foraminiferal eDNA. We discuss the problems associated with HTS approaches and predict the future trends and avenues that hold promises for surveying foraminiferal diversity accurately and efficiently

Next-Generation Sequencing of Aquatic Oligochaetes: Comparison of Experimental Communities

Aquatic oligochaetes are a common group of freshwater benthic invertebrates known to be very sensitive to environmental changes and currently used as bioindicators in some countries. However, more extensive application of oligochaetes for assessing the ecological quality of sediments in watercourses and lakes would require overcoming the difficulties related to morphology-based identification of oligochaetes species. This study tested the Next-Generation Sequencing (NGS) of a standard cytochrome c oxydase I (COI) barcode as a tool for the rapid assessment of oligochaete diversity in environmental samples, based on mixed specimen samples. To know the composition of each sample we Sanger sequenced every specimen present in these samples. Our study showed that a large majority of OTUs (Operational Taxonomic Unit) could be detected by NGS analyses. We also observed congruence between the NGS and specimen abundance data for several but not all OTUs. Because the differences in sequence abundance data were consistent across samples, we exploited these variations to empirically design correction factors. We showed that such factors increased the congruence between the values of oligochaetes-based indices inferred from the NGS and the Sanger-sequenced specimen data. The validation of these correction factors by further experimental studies will be needed for the adaptation and use of NGS technology in biomonitoring studies based on oligochaete communities

Molecular evidence for widespread occurrence of Foraminifera in soils

International audienceEnvironmental SSU rDNA-based surveys are contributing to the dramatic revision of eukaryotic high-level diversity and phylogeny as the number of sequence data increases. This ongoing revolution gives the opportunity to test for the presence of some eukaryotic taxa in environments where they have not been found using classical microscopic observations. Here, we test whether the foraminifera, a group of single-celled eukaryotes, considered generally as typical for the marine ecosystems are present in soil. We performed foraminiferal-specific nested PCR on 20 soil DNA samples collected in contrasted environments. Unexpectedly, we found that the majority of the samples contain foraminiferal SSU rDNA sequences. In total, we obtained 49 sequences from 17 localities. Phylogenetic analysis clusters them in four groups branching among the radiation of early foraminiferal lineages. Three of these groups also include sequences originated from previous freshwater surveys, suggesting that there were up to four independent colonization events of terrestrial and/or freshwater ecosystems by ancestral foraminifera. As shown by our data, foraminifera are a widespread and diverse component of soil microbial communities. Yet, identification of terrestrial foraminiferal species and understanding of their ecological role represent an exciting challenge for future research