Computational genomics of prokaryotes


Wijzig gegevens

Titel Computational genomics of prokaryotes
Looptijd 2003 - 12 / 2007
Status Afgesloten
Dissertatie Ja
Onderzoeknummer OND1300998
Leverancier gegevens METIS Wageningen Universiteit en Researchcentrum

Samenvatting (EN)

Overall aims This project aims to reconstruct the cellular processes, metabolic potential (metabolome) and regulatory networks of selected gram-positive Bacteria and Archaea, by in silico analysis of all proteins encoded by their chromosome. Initially the "in-house confidential" and publicly available genome sequences will be used, and later this analysis will be extended to genomes that become available during the project . The results will be incorporated into "virtual cell" databases, consisting of modules that include the majority of genes and predicted encoded proteins, signalling and information pathways, transport systems, regulatory networks, metabolic routes and their possible interactions, but also the corresponding substrates, intermediates and products. This will provide a basis for the translation of the genotype into specific phenotypic traits of several lactic acid bacteria (Lactococcus, Lactobacillus, Streptococcus), bacilli, clostridia and Archaea (Pyrococcus, Suëàlobus). Subsequently, in silico comparative genomics of different prokaryotic microbes will provide a detailed picture of the distribution of the overall gene-pool among these organisms, the architecture of the metabolome and an inventory of both shared and unique genes and encoded properties of each species. In general, this should lead to important advances in the understanding of prokaryote evolution, and will contribute to the prediction of their metabolic functions. As a model case, special attention will be paid to the regulatory networks operating in Bacillus subtilis. Ongoing transcriptome analysis using DNA-microarrays of this bacterium provides a wealth of transcriptome data, for which bioinformatics tools will be used and developed to be able to identify and visualize in a dynamic way the underlying regulatory networks. The resulting system will then be applied for the determination of gene networks in other target prokaryotes. Key objectives Comparative computational genomics will be used: - to significantly improve functional annotation of selected genomes of gram-positive Bacteria and Archaea. - to initiate the construction of "virtual cell" databases for selected microbes, consisting of modules for metabolic pathways, signalling / information pathways, transport routes, replication machinery, etc. - to develop bioinformatics tools for automatic and interactive visualization of "virtual cell" components/networks, providing a framework for future incorporation of transcriptome, proteome and metabolome data. - to develop a dynamical system for identification, modelling and simulation of gene regulatory networks, combined with interactive tools for network visualization. - to gain insight in prokaryotic evolution by comparing conserved (core) vs unique features of genome organization, genes and pathways of prokayotes at different levels: genus-species-strain Approach Optimisation of genome annotation, particularly to assign functions to encoded proteins previously classified as "conserved hypothetical" and "unknown" will be tackled using a variety of homology methods, non-homology methods and integrated methods. These include methods that use whole genome comparisons to predict function, e.g. from gene context, functional coupling, fusion analysis, etc. The "virtual cell" databases will be built in a step-wise, modular fashion, starting with metabolic pathways and transport systems, and subsequent addition of signalling and regulatory elements. Reconstruction of the cellular processes will be based on existing metabolic databases. In addition, automated methods to reconstruct metabolic pathways from genome data will be used. This project will make use of specialized databases (e.g. genomes, metabolic pathways) and bioinformatics software tools that are available at CMBI IKIJNI and I'WI (RUG) and through internet, but also those that are developed within this project. In particular, we aim to develop algorithms for automatic detection of specific regulatory elements (e.g. promoters, ribosome-binding sites, operators and other cis-acting elements). Another key objective is to develop software for automatic visualization of "virtual cell" components/networks of individual organisms from complete genome input. Automated methods for comparison of whole genomes, gene clusters and pathways will be used. In addition, new methods will be developed specifically directed at analyzing gene context in multiple genomes. Elements of innovation This proposal has several novel elements, such as: - integral approach from genome sequence to metabolome of gram-positive bacteria and archaea - step-wise, iterative reconstruction of "virtual cells" for several different prokaryotes - modules that allow prediction and user-friendly visualization of specific cellular networks - development of a dynamic system for identification, modelling and simulation of gene regulatory networks, combined with interactive tools for network visualization. - comparative genomics of prokaryotes (gram-positive bacteria & archaea) by database linking and database mining - probing principles of microbial evolution at several different levels (genus-species-strain) Relevance for BMI and biomolecular research The results of this project should provide: - a specialized expertise center (with network partners) for comparative genomics of prokaryotes - training of PhD students and post docs at the bioinformatics institutes CMBI (Nijmegen) and IWI (Groningen), followed by implementation within participating groups (universities of Nijmegen, Wageningen, Groningen) and network partners (WCFS, NIZO food research) - a framework for virtual cell databases for a variety of gram-positive bacteria and archaea - detailed insight into relation between genetics, evolution and physiology of prokaryotes - targets for validation of in silico predictions - the virtual cell framework as a basis for improved mathematical modelling of metabolism, gene regulation and predictions of dynamic behaviour - targets for metabolic engineering studies to redirect growth requirements, stress response or product formation - metabolic models that form the basis for subsequent transcriptome and proteome analysis - automated virtual cell visualisation BIO-IT-infrastructure, allowing future integration of global, genomics-based methods like transcriptome, proteome and metabolome analysis. - new bioinformatic tools for analyzing multiple and related genomes The proposed research directly relates to the definitions of Biomolecular Informatics as stated in the NOW programme, i.e. (i) to exploit and integrate genome-wide data and knowledge to answer biological questions; (ii) to simulate and validate function and dynamics of biomolecular systems; (iii) to provide and give access to large datasets and tools to exploit them. Moreover, the proposal directly relates to the research themes A, B, C and D. It is our specific purpose that the databases and systems to be developed will have wide applicability in the analysis of gene networks in other organisms, thanks to the generic set-up

Betrokken organisaties

Betrokken personen

Bovenliggende onderzoeksactiviteit(en)


A70000 Volksgezondheid en gezondheidszorg
D16200 Software, algoritmen, besturingssystemen
D16400 Informatiesystemen, databases
D21100 Bioinformatica, biomathematica, biomechanica
D21300 Biochemie
D21400 Genetica
D22100 Microbiologie

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