65 research outputs found

    ACLAME: A CLAssification of Mobile genetic Elements, update 2010

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    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

    Disentangling environmental effects in microbial association networks

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    Background Ecological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not. Results We present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges—87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors. Conclusions To reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses. Video abstrac

    Mainstreams of horizontal gene exchange in enterobacteria : consideration of the outbreak of enterohemorrhagic E. coli O104:H4 in Germany in 2011

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    BACKGROUND: Escherichia coli O104:H4 caused a severe outbreak in Europe in 2011. The strain TY-2482 sequenced from this outbreak allowed the discovery of its closest relatives but failed to resolve ways in which it originated and evolved. On account of the previous statement, may we expect similar upcoming outbreaks to occur recurrently or spontaneously in the future? The inability to answer these questions shows limitations of the current comparative and evolutionary genomics methods. PRINCIPAL FINDINGS: The study revealed oscillations of gene exchange in enterobacteria, which originated from marine c- Proteobacteria. These mobile genetic elements have become recombination hotspots and effective ‘vehicles’ ensuring a wide distribution of successful combinations of fitness and virulence genes among enterobacteria. Two remarkable peculiarities of the strain TY-2482 and its relatives were observed: i) retaining the genetic primitiveness by these strains as they somehow avoided the main fluxes of horizontal gene transfer which effectively penetrated other enetrobacteria; ii) acquisition of antibiotic resistance genes in a plasmid genomic island of b-Proteobacteria origin which ontologically is unrelated to the predominant genomic islands of enterobacteria. CONCLUSIONS: Oscillations of horizontal gene exchange activity were reported which result from a counterbalance between the acquired resistance of bacteria towards existing mobile vectors and the generation of new vectors in the environmental microflora. We hypothesized that TY-2482 may originate from a genetically primitive lineage of E. coli that has evolved in confined geographical areas and brought by human migration or cattle trade onto an intersection of several independent streams of horizontal gene exchange. Development of a system for monitoring the new and most active gene exchange events was proposed.This work was funded by the National Research Foundation (South Africa) grant #71261 for National Bioinformatics and Functional Genomics Programme.http://www.plosone.or

    Mainstreams of Horizontal Gene Exchange in Enterobacteria: Consideration of the Outbreak of Enterohemorrhagic E. coli O104:H4 in Germany in 2011

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    Escherichia coli O104:H4 caused a severe outbreak in Europe in 2011. The strain TY-2482 sequenced from this outbreak allowed the discovery of its closest relatives but failed to resolve ways in which it originated and evolved. On account of the previous statement, may we expect similar upcoming outbreaks to occur recurrently or spontaneously in the future? The inability to answer these questions shows limitations of the current comparative and evolutionary genomics methods.status: publishe

    Community-Level Responses to Iron Availability in Open Ocean Plankton Ecosystems

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    Predicting responses of plankton to variations in essential nutrients is hampered by limited in situ measurements, a poor understanding of community composition, and the lack of reference gene catalogs for key taxa. Iron is a key driver of plankton dynamics and, therefore, of global biogeochemical cycles and climate. To assess the impact of iron availability on plankton communities, we explored the comprehensive bio-oceanographic and bio-omics data sets from Tara Oceans in the context of the iron products from two state-of-the-art global scale biogeochemical models. We obtained novel information about adaptation and acclimation toward iron in a range of phytoplankton, including picocyanobacteria and diatoms, and identified whole subcommunities covarying with iron. Many of the observed global patterns were recapitulated in the Marquesas archipelago, where frequent plankton blooms are believed to be caused by natural iron fertilization, although they are not captured in large-scale biogeochemical models. This work provides a proof of concept that integrative analyses, spanning from genes to ecosystems and viruses to zooplankton, can disentangle the complexity of plankton communities and can lead to more accurate formulations of resource bioavailability in biogeochemical models, thus improving our understanding of plankton resilience in a changing environment

    Towards in silico detection and classification of prokaryotic Mobile Genetic Elements

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    Bacteriophage genomes show pervasive mosaicism, indicating that horizontal gene exchange plays a crucial role in their evolution. Phage genomes represent unique combinations of modules, each of them with a different phylogenetic history. Thus, a web-like, rather than a hierarchical scheme is needed for an appropriate representation of phage evolutionary relationships. Part of the virology community has long recognized this fact and calls for changing the traditional taxonomy that classifies tailed phages according to the type of genetic materials and phage tail and head/capsid morphologies. Moreover, based on morphological features, the current system depends on inspection of phage virions under the electron microscope and cannot directly classify prophages. With the genomic era, many phages have been sequenced that are not classified, calling for development of an automatic classification procedure that can cope with the sequencing pace. The ACLAME database provides a classification of phage proteins into families and assigns the families with at least 3 members to one or several functions.In the first contribution of this work, the relative contribution of those different protein families to the similarities between the phages is assessed using pair-wise similarity matrices. The modular character of phage genomes is readily visualized using heatmaps, which differ depending on the function of the proteins used to measure the similarity. Next, I propose a framework that allows for a reticulate classification of phages based on gene content (with statistical assessment of the significance of number of shared genes). Starting from gene/protein families, we built a weighted graph, where nodes represent phages and edges represent phage-phage similarities in terms of shared families. The topology of the network shows that most dsDNA phages form an interconnected group, confirming that dsDNA phages share a common gene pool, as proposed earlier. Differences are observed between temperate and virulent phages in the values of several centrality measures, which may correlate with different constraints to rampant recombination dictated by the phage lifestyle, and thus with a distinct evolutionary role in the phage population. To this graph I applied a two-step clustering method to generate a fuzzy classification of phages. Using this methodology, each phage is associated with a membership vector, which quantitatively characterizes the membership of the phage to the clusters. Alternatively, genes were clustered based on their ‘phylogenetic profiles’ to define ‘evolutionary cohesive modules’. Phages can then be described as composite of a set of modules from the collection of modules of the whole phage population. The relationships between phages define a network based on module sharing. Unlike the first network built from statistical significant number of shared genes, this second network allows for a direct exploration of the nature of the functions shared between the connected phages. This functionality of the module-based network runs at the expense of missing links due to genes that are not part of modules, but which are encoded in the first network. These approaches can easily focus on pre-defined modules for tracing one or several traits across the population. They provide an automatic and dynamic way to study relationships within the phage population. Moreover, they can be extended to the representation of populations of other mobile genetic elements or even to the entire mobilome.Finally, to enrich the phage sequence space, which in turn allows for a better assessment of phage diversity and evolution, I devise a prophage prediction tool. With this methodology, approximately 800 prophages are predicted in 266 among 800 replicons screened. The comparison of a subset of these predictions with a manually annotated set shows a sensitivity of 79% and a positive predictive value of 91%, this later value suggesting that the procedure makes few false predictions. The preliminary analysis of the predicted prophages indicates that many may constitute novel phage types.This work allows tracing guidelines for the classification and analysis of other mobile genetic elements. One can foresee that a pool of putative mobile genetic elements sequences can be extracted from the prokaryotic genomes and be further broken down in groups of related elements and evolutionary conserved modules. This would allow widening the picture of the evolutionary and functional relationships between these elements.Doctorat en Sciencesinfo:eu-repo/semantics/nonPublishe

    Towards in silico detection and classification of prokaryotic Mobile Genetic Elements

    No full text
    Bacteriophage genomes show pervasive mosaicism, indicating that horizontal gene exchange plays a crucial role in their evolution. Phage genomes represent unique combinations of modules, each of them with a different phylogenetic history. Thus, a web-like, rather than a hierarchical scheme is needed for an appropriate representation of phage evolutionary relationships. Part of the virology community has long recognized this fact and calls for changing the traditional taxonomy that classifies tailed phages according to the type of genetic materials and phage tail and head/capsid morphologies. Moreover, based on morphological features, the current system depends on inspection of phage virions under the electron microscope and cannot directly classify prophages. With the genomic era, many phages have been sequenced that are not classified, calling for development of an automatic classification procedure that can cope with the sequencing pace. The ACLAME database provides a classification of phage proteins into families and assigns the families with at least 3 members to one or several functions.In the first contribution of this work, the relative contribution of those different protein families to the similarities between the phages is assessed using pair-wise similarity matrices. The modular character of phage genomes is readily visualized using heatmaps, which differ depending on the function of the proteins used to measure the similarity. Next, I propose a framework that allows for a reticulate classification of phages based on gene content (with statistical assessment of the significance of number of shared genes). Starting from gene/protein families, we built a weighted graph, where nodes represent phages and edges represent phage-phage similarities in terms of shared families. The topology of the network shows that most dsDNA phages form an interconnected group, confirming that dsDNA phages share a common gene pool, as proposed earlier. Differences are observed between temperate and virulent phages in the values of several centrality measures, which may correlate with different constraints to rampant recombination dictated by the phage lifestyle, and thus with a distinct evolutionary role in the phage population. To this graph I applied a two-step clustering method to generate a fuzzy classification of phages. Using this methodology, each phage is associated with a membership vector, which quantitatively characterizes the membership of the phage to the clusters. Alternatively, genes were clustered based on their ‘phylogenetic profiles’ to define ‘evolutionary cohesive modules’. Phages can then be described as composite of a set of modules from the collection of modules of the whole phage population. The relationships between phages define a network based on module sharing. Unlike the first network built from statistical significant number of shared genes, this second network allows for a direct exploration of the nature of the functions shared between the connected phages. This functionality of the module-based network runs at the expense of missing links due to genes that are not part of modules, but which are encoded in the first network. These approaches can easily focus on pre-defined modules for tracing one or several traits across the population. They provide an automatic and dynamic way to study relationships within the phage population. Moreover, they can be extended to the representation of populations of other mobile genetic elements or even to the entire mobilome.Finally, to enrich the phage sequence space, which in turn allows for a better assessment of phage diversity and evolution, I devise a prophage prediction tool. With this methodology, approximately 800 prophages are predicted in 266 among 800 replicons screened. The comparison of a subset of these predictions with a manually annotated set shows a sensitivity of 79% and a positive predictive value of 91%, this later value suggesting that the procedure makes few false predictions. The preliminary analysis of the predicted prophages indicates that many may constitute novel phage types.This work allows tracing guidelines for the classification and analysis of other mobile genetic elements. One can foresee that a pool of putative mobile genetic elements sequences can be extracted from the prokaryotic genomes and be further broken down in groups of related elements and evolutionary conserved modules. This would allow widening the picture of the evolutionary and functional relationships between these elements.Doctorat en Sciencesinfo:eu-repo/semantics/nonPublishe

    Reticulate classification of mosaic microbial genomes using NeAT website

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    The tree of life is the classical representation of the evolutionary relationships between existent species. A tree is appropriate to display the divergence of species through mutation, i.e. by vertical descent. However, lateral gene transfer (LGT) is excluded from such representations. When LGT contribution to genome evolution cannot be neglected (e.g. for prokaryotes and mobile genetic elements), the tree becomes misleading. Networks appear as an intuitive way to represent both vertical and horizontal relationships, while overlapping groups within such graphs are more suitable for their classification. Here, we describe a method to represent both vertical and horizontal relationships. We start with a set of genomes whose coded proteins have been grouped into families based on sequence similarity. Next, all pairs of genomes are compared, counting the number of proteins classified into the same family. From this comparison, we derive a weighted graph where genomes with a significant number of similar proteins are linked. Finally, we apply a two-step clustering of this graph to produce a classification where nodes can be assigned to multiple clusters. The procedure can be performed using the Network Analysis Tools (NeAT) website. © 2012 Springer Science+Business Media, LLC.SCOPUS: ar.kinfo:eu-repo/semantics/publishe

    A global ocean atlas of eukaryotic genes

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    While our knowledge about the roles of microbes and viruses in the ocean has increased tremendously due to recent advances in genomics and metagenomics, research on marine microbial eukaryotes and zooplankton has benefited much less from these new technologies because of their larger genomes, their enormous diversity, and largely unexplored physiologies. Here, we use a metatranscriptomics approach to capture expressed genes in open ocean Tara Oceans stations across four organismal size fractions. The individual sequence reads cluster into 116 million unigenes representing the largest reference collection of eukaryotic transcripts from any single biome. The catalog is used to unveil functions expressed by eukaryotic marine plankton, and to assess their functional biogeography. Almost half of the sequences have no similarity with known proteins, and a great number belong to new gene families with a restricted distribution in the ocean. Overall, the resource provides the foundations for exploring the roles of marine eukaryotes in ocean ecology and biogeochemistry.0SCOPUS: ar.jinfo:eu-repo/semantics/publishe

    A first global analysis of plasmid encoded proteins in the ACLAME database

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    Many plasmids are mobile genetic elements (MGEs) and, as other members of that group of DNA entities, their genomes display a mosaic and combinatorial structure, making their classification extremely difficult. As other MGEs, plasmids play a major role in horizontal transfer of genetic materials and genome reorganization. Yet, the full impact of such phenomenon on major properties of the host cell, such as pathogenicity, the ability to use new carbon sources or resistance to antibiotics, remains to be fully assessed. More and more complete plasmid genome sequences are available. However, in the absence of standards for storing plasmid sequence data and annotating genes and gene products on sequenced plasmid genomes, the resulting information remains rather limited. Using 503 sequenced plasmids organized in the ACLAME database, we discuss how, by structuring information on the genomes, their host and the proteins they code for, one can gain access to either global or more detailed analysis of the plasmid sequence information, as illustrated by a network representation of the relationships between plasmids
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