Award details

Dynamics of enzyme aggregates of carbon core metabolism in growing and starved cells / a. Interactome studies

Reference	BB/F003412/1
Principal Investigator / Supervisor	Professor Colin Harwood
Co-Investigators / Co-Supervisors
Institution	Newcastle University
Department	Inst for Cell and Molecular Biosciences
Funding type	Research
Value (£)	356,827
Status	Completed
Type	Research Grant
Start date	01/08/2007
End date	31/01/2011
Duration	42 months

Abstract

The overall goal of Bacell-SysMo is the quantitative understanding of the interacting and dynamic regulatory processes that control the transition from growth to starvation - an essential issue for cell physiology and biotechnology. This goal will be accomplished through integrating quantitative data from a variety of post-genomic methods within mathematical models for data analyses, evaluation and prediction of systems behaviour. There are three integrative workpackages: WP1 will follow the dynamics of interacting components of metabolic and gene expression networks during the transition from growth to a glucose-starvation induced non-growing state. This WP is constructed as a series of partnerships between experimental and modelling groups that investigate specific cellular subsystems in an iterative procedure between model building/simulation and experiment, thereby fostering close collaborations. WP2 has the goal of integrating the modules into a consistent system representation on the background of a static genome-scale model of metabolism. While a whole cell model would be overly ambitious and problems with individual modules might arise, the integrated model will grow step-wise by integrating the functional modules. WP3 is the data generation platform that provides an inventory of the molecular architecture of growing and non-growing cells by using various omics approaches to provide global quantitative and structural data for modelling. These studies involve mRNA profiling, quantification of the level and synthesis rate of cellular proteins, their stability and sorting as well as integration into functional complexes, elucidation of the structure of the complexes and their in vivo assembly and localization.

Summary

The objective of this project is to develop an integrated understanding of the metabolic and genetic network that controls the transition from growth to glucose starvation in the model bacterium, Bacillus subtilis. In addition to serving as a model system, B. subtilis is an industrial workhorse for 'white biotechnology' since it serves is a primary producer of technical enzymes and other products (e.g. vitamins, antibiotics, flavour enhancers and biochemicals). The transition from growth to growth limitation is a fundamental ecophysiological response and is studied by academic researchers as a model for environmental signal processing and integration. Understanding this transition is also pivotal for industrial fermentations of Bacillus that occur predominantly under nutrient limitation. Our approach is to integrate biological data with mathematical models of the networks that regulate the transition from growth to starvation. The approach starts with quantitative monitoring of defined genetic and environmental perturbations under standardized growth conditions. These data are used for mathematical modelling of regulatory processes. As the programme develops, gaps in our understanding will be revealed by the failure of structural, genome-wide network analyses to describe the biological data. Our concept is to continuously probe model and data consistency in clearly defined (sub)projects, each involving an experimental and a modelling partner. The pivotal element is a model-driven experimental design, where model-based hypotheses are tested through targeted measurements of critical variables. Facilitated through standardized nomenclature, model formats, and defined input/output signals, modular mathematical models are then integrated into a consistent systems representation. In summary, the project will provide convincing evidence that close interactions between experimental and computational scientists on a well advanced model organism can significantly advance our quantitative understanding of, and eventually our ability to control, the highly dynamic and complex regulatory processes in microbes.

Committee	Closed Committee - Engineering & Biological Systems (EBS)
Research Topics	Microbiology, Systems Biology
Research Priority	X – Research Priority information not available
Research Initiative	Systems Biology of Microorganisms (SysMo) [2007-2008]
Funding Scheme	X – not Funded via a specific Funding Scheme

Associated awards:

BB/F003404/1 Structural analysis of the interaction networks

BB/F00348X/1 Localization of signal transduction components in the bacterial cell

I accept the terms and conditions of use (opens in new window)

export PDF file

back to list new search