Gipsi Lima-Mendez

Eukaryotic plankton diversity in the sunlit ocean

Marine plankton support global biological and geochemical processes. Surveys of their biodiversity have hitherto been geographically restricted and have not accounted for the full range of plankton size. We assessed eukaryotic diversity from 334 size-fractionated photic-zone plankton communities collected across tropical and temperate oceans during the circumglobal Tara Oceans expedition. We analyzed 18S ribosomal DNA sequences across the intermediate plankton-size spectrum from the smallest unicellular eukaryotes (protists, >0.8 micrometers) to small animals of a few millimeters. Eukaryotic ribosomal diversity saturated at ~150,000 operational taxonomic units, about one-third of which could not be assigned to known eukaryotic groups. Diversity emerged at all taxonomic levels, both within the groups comprising the ~11,200 cataloged morphospecies of eukaryotic plankton and among twice as many other deep-branching lineages of unappreciated importance in plankton ecology studies. Most eukaryotic plankton biodiversity belonged to heterotrophic protistan groups, particularly those known to be parasites or symbiotic hosts.

Structure and function of the global ocean microbiome

Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.

Population-level analysis of gut microbiome variation

“Normal” for the gut microbiota For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities. Science, this issue pp. 560 and 565 Two large-scale studies in Western Europe establish environment-diet-microbe-host interactions. Fecal microbiome variation in the average, healthy population has remained under-investigated. Here, we analyzed two independent, extensively phenotyped cohorts: the Belgian Flemish Gut Flora Project (FGFP; discovery cohort; N = 1106) and the Dutch LifeLines-DEEP study (LLDeep; replication; N = 1135). Integration with global data sets (N combined = 3948) revealed a 14-genera core microbiota, but the 664 identified genera still underexplore total gut diversity. Sixty-nine clinical and questionnaire-based covariates were found associated to microbiota compositional variation with a 92% replication rate. Stool consistency showed the largest effect size, whereas medication explained largest total variance and interacted with other covariate-microbiota associations. Early-life events such as birth mode were not reflected in adult microbiota composition. Finally, we found that proposed disease marker genera associated to host covariates, urging inclusion of the latter in study design.

Determinants of community structure in the global plankton interactome

Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

ACLAME: A CLAssification of Mobile genetic Elements, update 2010

The ACLAME database is dedicated to the collection, analysis and classification of sequenced mobile genetic elements (MGEs, in particular phages and plasmids). In addition to providing information on the MGEs content, classifications are available at various levels of organization. At the gene/protein level, families group similar sequences that are expected to share the same function. Families of four or more proteins are manually assigned with a functional annotation using the GeneOntology and the locally developed ontology MeGO dedicated to MGEs. At the genome level, evolutionary cohesive modules group sets of protein families shared among MGEs. At the population level, networks display the reticulate evolutionary relationships among MGEs. To increase the coverage of the phage sequence space, ACLAME version 0.4 incorporates 760 high-quality predicted prophages selected from the Prophinder database. Most of the data can be downloaded from the freely accessible ACLAME web site (http://aclame.ulb.ac.be). The BLAST interface for querying the database has been extended and numerous tools for in-depth analysis of the results have been added.

Metagenomic 16S rDNA Illumina tags are a powerful alternative to amplicon sequencing to explore diversity and structure of microbial communities

Sequencing of 16S rDNA polymerase chain reaction (PCR) amplicons is the most common approach for investigating environmental prokaryotic diversity, despite the known biases introduced during PCR. Here we show that 16S rDNA fragments derived from Illumina-sequenced environmental metagenomes (mi tags) are a powerful alternative to 16S rDNA amplicons for investigating the taxonomic diversity and structure of prokaryotic communities. As part of the Tara Oceans global expedition, marine plankton was sampled in three locations, resulting in 29 subsamples for which metagenomes were produced by shotgun Illumina sequencing (ca. 700 Gb). For comparative analyses, a subset of samples was also selected for Roche-454 sequencing using both shotgun (m454 tags; 13 metagenomes, ca. 2.4 Gb) and 16S rDNA amplicon (454 tags; ca. 0.075 Gb) approaches. Our results indicate that by overcoming PCR biases related to amplification and primer mismatch, mi tags may provide more realistic estimates of community richness and evenness than amplicon 454 tags. In addition, mi tags can capture expected beta diversity patterns. Using mi tags is now economically feasible given the dramatic reduction in high-throughput sequencing costs, having the advantage of retrieving simultaneously both taxonomic (Bacteria, Archaea and Eukarya) and functional information from the same microbial community.

Prophinder: a computational tool for prophage prediction in prokaryotic genomes

UNLABELLED Prophinder is a prophage prediction tool coupled with a prediction database, a web server and web service. Predicted prophages will help to fill the gaps in the current sparse phage sequence space, which should cover an estimated 100 million species. Systematic and reliable predictions will enable further studies of prophages contribution to the bacteriophage gene pool and to better understand gene shuffling between prophages and phages infecting the same host. AVAILABILITY Softare is available at http://aclame.ulb.ac.be/prophinder

Network Analysis Tools: from biological networks to clusters and pathways

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein–protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in ∼1 h.

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

Exploring nucleo-cytoplasmic large DNA viruses in Tara Oceans microbial metagenomes.

Nucleo-cytoplasmic large DNA viruses (NCLDVs) constitute a group of eukaryotic viruses that can have crucial ecological roles in the sea by accelerating the turnover of their unicellular hosts or by causing diseases in animals. To better characterize the diversity, abundance and biogeography of marine NCLDVs, we analyzed 17 metagenomes derived from microbial samples (0.2–1.6 μm size range) collected during the Tara Oceans Expedition. The sample set includes ecosystems under-represented in previous studies, such as the Arabian Sea oxygen minimum zone (OMZ) and Indian Ocean lagoons. By combining computationally derived relative abundance and direct prokaryote cell counts, the abundance of NCLDVs was found to be in the order of 104–105 genomes ml−1 for the samples from the photic zone and 102–103 genomes ml−1 for the OMZ. The Megaviridae and Phycodnaviridae dominated the NCLDV populations in the metagenomes, although most of the reads classified in these families showed large divergence from known viral genomes. Our taxon co-occurrence analysis revealed a potential association between viruses of the Megaviridae family and eukaryotes related to oomycetes. In support of this predicted association, we identified six cases of lateral gene transfer between Megaviridae and oomycetes. Our results suggest that marine NCLDVs probably outnumber eukaryotic organisms in the photic layer (per given water mass) and that metagenomic sequence analyses promise to shed new light on the biodiversity of marine viruses and their interactions with potential hosts.