Filter and export

Publications

What is a Publication?
4 Publications visible to you, out of a total of 4
Basic Regulatory Principles of Escherichia coli's Electron Transport Chain for Varying Oxygen Conditions

Abstract (Expand)

For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known … that the global transcriptional regulators FNR and ArcA are involved in oxygen response it is unclear how they interplay in the regulation of ETC enzymes under micro-aerobic chemostat conditions. Also, there are diverse results which and how quinones (oxidised/reduced, ubiquinone/other quinones) are controlling the ArcBA two-component system. In the following a mathematical model of the E. coli ETC linked to basic modules for substrate uptake, fermentation product excretion and biomass formation is introduced. The kinetic modelling focusses on regulatory principles of the ETC for varying oxygen conditions in glucose-limited continuous cultures. The model is based on the balance of electron donation (glucose) and acceptance (oxygen or other acceptors). Also, it is able to account for different chemostat conditions due to changed substrate concentrations and dilution rates. The parameter identification process is divided into an estimation and a validation step based on previously published and new experimental data. The model shows that experimentally observed, qualitatively different behaviour of the ubiquinone redox state and the ArcA activity profile in the micro-aerobic range for different experimental conditions can emerge from a single network structure. The network structure features a strong feed-forward effect from the FNR regulatory system to the ArcBA regulatory system via a common control of the dehydrogenases of the ETC. The model supports the hypothesis that ubiquinone but not ubiquinol plays a key role in determining the activity of ArcBA in a glucose-limited chemostat at micro-aerobic conditions.

Editor:

Date Published: 30th Sep 2014

Publication Type: Not specified

A mathematical model of metabolism and regulation provides a systems-level view of how Escherichia coli responds to oxygen

Abstract (Expand)

The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of … energy supply, carbon, and redox metabolism. The measurement of transcript levels, metabolite concentrations and metabolic fluxes per se gives an incomplete picture. An appreciation of the interdependencies between the different measurement values is essential for systems-level understanding. Mathematical modeling has the potential to provide a coherent and quantitative description of the interplay between gene expression, metabolite concentrations, and metabolic fluxes. Escherichia coli undergoes major adaptations in central metabolism when the availability of oxygen changes. Thus, an integrated description of the oxygen response provides a benchmark of our understanding of carbon, energy, and redox metabolism. We present the first comprehensive model of the central metabolism of E. coli that describes steady-state metabolism at different levels of oxygen availability. Variables of the model are metabolite concentrations, gene expression levels, transcription factor activities, metabolic fluxes, and biomass concentration. We analyze the model with respect to the production capabilities of central metabolism of E. coli. In particular, we predict how precursor and biomass concentration are affected by product formation.

Editor:

Date Published: 27th Mar 2014

Publication Type: Not specified

Transcript profiling and inference of Escherichia coli K-12 ArcA activity across the range of physiologically relevant oxygen concentrations

Abstract (Expand)

Oxygen availability is the major determinant of the metabolic modes adopted by Escherichia coli. Whilst much is known about E. coli gene expression and metabolism under fully aerobic and anaerobic … conditions, the intermediate oxygen tensions that are encountered in natural niches are understudied. Here for the first time the transcript profiles of E. coli K-12 across the physiologically significant range of oxygen availabilities are described. These suggested a progressive switch to aerobic respiratory metabolism and a remodeling of the cell envelope as oxygen availability increased. The transcriptional responses were consistent with changes in the abundances of cytochrome bd and bo and outer membrane protein W. The observed transcript and protein profiles result from changes in the activities of regulators that respond to oxygen itself, or to metabolic and environmental signals that are sensitive to oxygen availability (aerobiosis). A probabilistic model (TFinfer) was used to predict the activity of the indirect oxygen-sensing two-component system ArcBA across the aerobiosis range. The model implied that the activity of the regulator ArcA correlated with aerobiosis, but not with the redox state of the ubiquinone pool, challenging the idea that ArcA activity is inhibited by oxidized ubiquinone. Measurement of the amount of phosphorylated ArcA correlated with the predicted ArcA activities and with aerobiosis, suggesting that fermentation product-mediated inhibition of ArcB phosphatase activity is the dominant mechanism for regulating ArcA activity under the conditions used here.

Authors: , , , Eleanor W Trotter, H M Shahzad Asif, Guido Sanguinetti, , ,

Date Published: 22nd Jan 2011

Publication Type: Not specified

TFInfer: a tool for probabilistic inference of transcription factor activities

Abstract (Expand)

SUMMARY: TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now … been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively. AVAILABILITY: http://homepages.inf.ed.ac.uk/gsanguin/TFInfer.html CONTACT: gsanguin@staffmail.ed.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: H M Shahzad Asif, , , Neil D Lawrence, Magnus Rattray,

Date Published: 24th Aug 2010

Publication Type: Not specified

Powered by
 (v.1.16.0-pre)
About FAIRDOMHub | Funding and Programmes | Credits | Terms & Conditions | Imprint | Cookie preferences
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH