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Towards an understanding of dynamic transcriptional regulation at global scale in bacteria: a systems biology approach


BaSysBio aims to achieve major breakthroughs in the understanding of the regulation of gene transcription in bacteria at a global scale. The highly dynamic gene regulation is mediated by transcription factors (TF) that trigger or repress the expression of their target genes. Transcription control is embedded into a hierarchical flow of information from genes to phenotype in which many regulatory steps can occur. BaSysBio adopts a systems biology approach in which quantitative experimental data will be generated for each step of the information flow, and will fuel computational modelling. High-throughput technologies (living cell arrays, tiling DNA microarrays, multidimensional liquid chromatography proteomics and quantitative metabolomics) will be developed in conjunction with new computational modelling concepts to facilitate the understanding of biological complexity. Models will simulate the cellular transcriptional responses to environmental changes and their impact on metabolism and proteome dynamics.

The iterative process of simulations and model-driven targeted experiments will generate novel hypotheses about the mechanistic nature of dynamic cellular responses, unravel emerging systems properties, and ultimately provide an efficient roadmap to tackle novel, pathogenic organisms. This system-based strategy will enable BaSysBio i) to understand how transcriptional regulation and metabolism are quantitatively integrated at a global level; ii) to unravel cellular transcriptional responses in conditions mimicking pathogenesis.

Finally, the project will validate the general applicability of the knowledge and integrated modelling-experimental strategy developed in the highly tractable B. subtilis model towards an understanding of regulatory networks controlling pathogenesis in disease-causing bacteria. BaSysBio will make a significant contribution towards overcoming the structural obstacles that hinder the development of systems biology in Europe.

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IP - Integrated Project


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Participantes (16)