Thierry Lombardot

Complete genome sequence of the marine planctomycete Pirellula sp strain 1

Pirellula sp. strain 1 (“Rhodopirellula baltica”) is a marine representative of the globally distributed and environmentally important bacterial order Planctomycetales. Here we report the complete genome sequence of a member of this independent phylum. With 7.145 megabases, Pirellula sp. strain 1 has the largest circular bacterial genome sequenced so far. The presence of all genes required for heterolactic acid fermentation, key genes for the interconversion of C1 compounds, and 110 sulfatases were unexpected for this aerobic heterotrophic isolate. Although Pirellula sp. strain 1 has a proteinaceous cell wall, remnants of genes for peptidoglycan synthesis were found. Genes for lipid A biosynthesis and homologues to the flagellar L- and P-ring protein indicate a former Gram-negative type of cell wall. Phylogenetic analysis of all relevant markers clearly affiliates the Planctomycetales to the domain Bacteria as a distinct phylum, but a deepest branching is not supported by our analyses.

TETRA: a web-service and a stand-alone program for the analysis and comparison of tetranucleotide usage patterns in DNA sequences

AbstractBackgroundIn the emerging field of environmental genomics, direct cloning and sequencing of genomic fragments from complex microbial communities has proven to be a valuable source of new enzymes, expanding the knowledge of basic biological processes. The central problem of this so called metagenome-approach is that the cloned fragments often lack suitable phylogenetic marker genes, rendering the identification of clones that are likely to originate from the same genome difficult or impossible. In such cases, the analysis of intrinsic DNA-signatures like tetranucleotide frequencies can provide valuable hints on fragment affiliation. With this application in mind, the TETRA web-service and the TETRA stand-alone program have been developed, both of which automate the task of comparative tetranucleotide frequency analysis. Availability:http://www.megx.net/tetraResultsTETRA provides a statistical analysis of tetranucleotide usage patterns in genomic fragments, either via a web-service or a stand-alone program. With respect to discriminatory power, such an analysis outperforms the assignment of genomic fragments based on the (G+C)-content, which is a widely-used sequence-based measure for assessing fragment relatedness. While the web-service is restricted to the calculation of correlation coefficients between tetranucleotide usage patterns of submitted DNA sequences, the stand-alone program generates a much more detailed output, comprising all raw data and graphical plots. The stand-alone program is controlled via a graphical user interface and can batch-process a multitude of sequences. Furthermore, it comes with pre-computed tetranucleotide usage patterns for 166 prokaryote chromosomes, providing a useful reference dataset and source for data-mining.ConclusionsUp to now, the analysis of skewed oligonucleotide distributions within DNA sequences is not a commonly used tool within metagenomics. With the TETRA web-service and stand-alone program, the method is now accessible in an easy to use manner for a broad audience. This will hopefully facilitate the interrelation of genomic fragments from metagenome libraries, ultimately leading to new insights into the genetic potentials of yet uncultured microorganisms.

Comparative Genome Analysis of Four Magnetotactic Bacteria Reveals a Complex Set of Group-Specific Genes Implicated in Magnetosome Biomineralization and Function

Magnetotactic bacteria (MTB) are a heterogeneous group of aquatic prokaryotes with a unique intracellular organelle, the magnetosome, which orients the cell along magnetic field lines. Magnetotaxis is a complex phenotype, which depends on the coordinate synthesis of magnetosomes and the ability to swim and orient along the direction caused by the interaction with the Earths magnetic field. Although a number of putative magnetotaxis genes were recently identified within a conserved genomic magnetosome island (MAI) of several MTB, their functions have remained mostly unknown, and it was speculated that additional genes located outside the MAI might be involved in magnetosome formation and magnetotaxis. In order to identify genes specifically associated with the magnetotactic phenotype, we conducted comparisons between four sequenced magnetotactic Alphaproteobacteria including the nearly complete genome of Magnetospirillum gryphiswaldense strain MSR-1, the complete genome of Magnetospirillum magneticum strain AMB-1, the complete genome of the magnetic coccus MC-1, and the comparative-ready preliminary genome assembly of Magnetospirillum magnetotacticum strain MS-1 against an in-house database comprising 426 complete bacterial and archaeal genome sequences. A magnetobacterial core genome of about 891 genes was found shared by all four MTB. In addition to a set of approximately 152 genus-specific genes shared by the three Magnetospirillum strains, we identified 28 genes as group specific, i.e., which occur in all four analyzed MTB but exhibit no (MTB-specific genes) or only remote (MTB-related genes) similarity to any genes from nonmagnetotactic organisms and which besides various novel genes include nearly all mam and mms genes previously shown to control magnetosome formation. The MTB-specific and MTB-related genes to a large extent display synteny, partially encode previously unrecognized magnetosome membrane proteins, and are either located within (18 genes) or outside (10 genes) the MAI of M. gryphiswaldense. These genes, which represent less than 1% of the 4,268 open reading frames of the MSR-1 genome, as yet are mostly of unknown functions but are likely to be specifically involved in magnetotaxis and, thus, represent prime targets for future experimental analysis.

JCoast – A biologist-centric software tool for data mining and comparison of prokaryotic (meta)genomes

BackgroundCurrent sequencing technologies give access to sequence information for genomes and metagenomes at a tremendous speed. Subsequent data processing is mainly performed by automatic pipelines provided by the sequencing centers. Although, standardised workflows are desirable and useful in many respects, rational data mining, comparative genomics, and especially the interpretation of the sequence information in the biological context, demands for intuitive, flexible, and extendable solutions.ResultsThe JCoast software tool was primarily designed to analyse and compare (meta)genome sequences of prokaryotes. Based on a pre-computed GenDB database project, JCoast offers a flexible graphical user interface (GUI), as well as an application programming interface (API) that facilitates back-end data access. JCoast offers individual, cross genome-, and metagenome analysis, and assists the biologist in exploration of large and complex datasets.ConclusionJCoast combines all functions required for the mining, annotation, and interpretation of (meta)genomic data. The lightweight software solution allows the user to easily take advantage of advanced back-end database structures by providing a programming and graphical user interface to answer biological questions. JCoast is available at the project homepage.

Archaea-Like Genes for C1-Transfer Enzymes in Planctomycetes: Phylogenetic Implications of Their Unexpected Presence in This Phylum

The unexpected presence of archaea-like genes for tetrahydromethanopterin (H4MPT)-dependent enzymes in the completely sequenced genome of the aerobic marine planctomycete Pirellula sp. strain 1 (“Rhodopirellula baltica”) and in the currently sequenced genome of the aerobic freshwater planctomycete Gemmata obscuriglobus strain UQM2246 revives the discussion on the origin of these genes in the bacterial domain. We compared the genomic arrangement of these genes in Planctomycetes and methylotrophic proteobacteria and performed a phylogenetic analysis of the encoded protein sequences to address the question whether the genes have been present in the common ancestor of Bacteria and Archaea or were transferred laterally from the archaeal to the bacterial domain and therein. Although this question could not be solved using the data presented here, some constraints on the evolution of the genes involved in archaeal and bacterial H4MPT-dependent C1-transfer may be proposed: (i) lateral gene transfer (LGT) from Archaea to a common ancestor of Proteobacteria and Planctomycetes seems more likely than the presence of the genes in the common ancestor of Bacteria and Archaea; (ii) a single event of interdomain LGT can be favored over two independent events; and (iii) the archaeal donor of the genes might have been a representative of the Methanosarcinales. In the bacterial domain, the acquired genes evolved according to distinct environmental and metabolic constraints, reflected by specific rearrangements of gene order, gene recruitment, and gene duplication, with subsequent functional specialization. During the course of evolution, genes were lost from some planctomycete genomes or replaced by orthologous genes from proteobacterial lineages.

Megx.net—database resources for marine ecological genomics

Marine microbial genomics and metagenomics is an emerging field in environmental research. Since the completion of the first marine bacterial genome in 2003, the number of fully sequenced marine bacteria has grown rapidly. Concurrently, marine metagenomics studies are performed on a regular basis, and the resulting number of sequences is growing exponentially. To address environmentally relevant questions like organismal adaptations to oceanic provinces and regional differences in the microbial cycling of nutrients, it is necessary to couple sequence data with geographical information and supplement them with contextual information like physical, chemical and biological data. Therefore, new specialized databases are needed to organize and standardize data storage as well as centralize data access and interpretation. We introduce Megx.net, a set of databases and tools that handle genomic and metagenomic sequences in their environmental contexts. Megx.net includes (i) a geographic information system to systematically store and analyse marine genomic and metagenomic data in conjunction with contextual information; (ii) an environmental genome browser with fast search functionalities; (iii) a database with precomputed analyses for selected complete genomes; and (iv) a database and tool to classify metagenomic fragments based on oligonucleotide signatures. These integrative databases and webserver will help researchers to generate a better understanding of the functioning of marine ecosystems. All resources are freely accessible at .

Detailed proteome analysis of growing cells of the planctomycete Rhodopirellula baltica SH1T.

Rhodopirellula baltica SH1T, which was isolated from the water column of the Kieler Bight, a bay in the southwestern Baltic Sea, is a marine aerobic, heterotrophic representative of the ubiquitous bacterial phylum Planctomycetes. We analyzed the R. baltica proteome by applying different preanalytical protein as well as peptide separation techniques (1‐D and 2‐DE, HPLC separation) prior to MS. That way, we could identify a total of 1115 nonredundant proteins from the intracellular proteome and from different cell wall protein fractions. With the contribution of 709 novel proteins resulting from this study, the current comprehensive R. baltica proteomic dataset consists of 1267 unique proteins (accounting for 17.3% of the total putative protein‐coding ORFs), including 261 proteins with a predicted signal peptide. The identified proteins were functionally categorized using Clusters of Orthologous Groups (COGs), and their potential cellular locations were predicted by bioinformatic tools. A unique protein family that contains several YTV domains and is rich in cysteine and proline was found to be a component of the R. baltica proteinaceous cell wall. Based on this comprehensive proteome analysis a global schema of the major metabolic pathways of growing R. baltica cells was deduced.

MetaMine – A tool to detect and analyse gene patterns in their environmental context

BackgroundModern sequencing technologies allow rapid sequencing and bioinformatic analysis of genomes and metagenomes. With every new sequencing project a vast number of new proteins become available with many genes remaining functionally unclassified based on evidences from sequence similarities alone. Extending similarity searches with gene pattern approaches, defined as genes sharing a distinct genomic neighbourhood, have shown to significantly improve the number of functional assignments. Further functional evidences can be gained by correlating these gene patterns with prevailing environmental parameters. MetaMine was developed to approach the large pool of unclassified proteins by searching for recurrent gene patterns across habitats based on key genes.ResultsMetaMine is an interactive data mining tool which enables the detection of gene patterns in an environmental context. The gene pattern search starts with a user defined environmentally interesting key gene. With this gene a BLAST search is carried out against the Microbial Ecological Genomics DataBase (MEGDB) containing marine genomic and metagenomic sequences. This is followed by the determination of all neighbouring genes within a given distance and a search for functionally equivalent genes. In the final step a set of common genes present in a defined number of distinct genomes is determined. The gene patterns found are associated with their individual pattern instances describing gene order and directions. They are presented together with information about the sample and the habitat. MetaMine is implemented in Java and provided as a client/server application with a user-friendly graphical user interface. The system was evaluated with environmentally relevant genes related to the methane-cycle and carbon monoxide oxidation.ConclusionMetaMine offers a targeted, semi-automatic search for gene patterns based on expert input. The graphical user interface of MetaMine provides a user-friendly overview of the computed gene patterns for further inspection in an ecological context. Prevailing biological processes associated with a key gene can be used to infer new annotations and shape hypotheses to guide further analyses. The use-cases demonstrate that meaningful gene patterns can be quickly detected using MetaMine.MetaMine is freely available for academic use from http://www.megx.net/metamine.

MetaLook: a 3D visualisation software for marine ecological genomics

BackgroundMarine ecological genomics can be defined as the application of genomic sciences to understand the structure and function of marine ecosystems. In this field of research, the analysis of genomes and metagenomes of environmental relevance must take into account the corresponding habitat (contextual) data, e.g. water depth, physical and chemical parameters. The creation of specialised software tools and databases is requisite to allow this new kind of integrated analysis.ResultsWe implemented the MetaLook software for visualisation and analysis of marine ecological genomic and metagenomic data with respect to habitat parameters. MetaLook offers a three-dimensional user interface to interactively visualise DNA sequences on a world map, based on a centralised georeferenced database. The user can define environmental containers to organise the sequences according to different habitat criteria. To find similar sequences, the containers can be queried with either genes from the georeferenced database or user-imported sequences, using the BLAST algorithm. This allows an interactive assessment of the distribution of gene functions in the environment.ConclusionMetaLook allows scientists to investigate sequence data in their environmental context and to explore correlations between genes and habitat parameters. This software is a step towards the creation of specialised tools to study constrained distributions and habitat specificity of genes correlated with specific processes.MetaLook is available at: http://www.megx.net/metalook