Salmonella paper is Editor's Choice article for the June issue of Microbiology. The group's latest paper (see below) has been selected as the Editor's Choice article for June 2014 and will be Open Access for the whole of the month on the current issue page.
BBSRC Network in Industrial Biotechnology and Bioenergy (NIBB): David Fell is assisting Nigel Minton in running the C1NET: Chemicals from C1 gas NIBB. Its website has just gone live. See the BBSRC and Oxford Brookes University announcements.
Latest paper: Hassan B. Hartman, David A. Fell, Sergio Rossell, Peter Ruhdal Jensen, Martin J. Woodward, Lotte Thorndahl, Lotte Jelsbak, John Elmerdahl Olsen, Anu Raghunathan, Simon Daefler,and Mark G. Poolman. Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation. Microbiology 160:1252-1266 (2014) DOI:10.1099/mic.0.076091-0
Previous paper: Uldis Kalnenieks, Agris Pentjuss, Reinis Rutkis, Egils Stalidzans and David A. Fell. Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies. Front. Microbiol. 5:42. (2014) doi: 10.3389/fmicb.2014.00042 (Open access)
Our group began nearly thirty years ago with initial interests in computer simulation of metabolism and the theoretical analysis of metabolic control and regulation. Whilst these still remain areas of interest, we have since developed interests in modelling signal transduction, in various different approaches to network analysis of metabolism, and in reconstructing metabolic networks from genomic data. In the course of this research, we have addressed problems in microbial, plant and mammalian metabolism, often in conjunction with collaborators who have contributed experimental results.
Our current work centres on modelling the networks of reactions in cells, with particular emphasis on metabolism. It forms part of the emerging field of Systems Biology, in that we are concerned with understanding how biological function arises from the interactions between many components, and with building predictive models. We have to develop and apply suitable theoretical tools, including metabolic control analysis, computer simulation and other forms of algebraic and numerical analysis. In addition, we are investigating how to decipher the metabolic information contained in genome sequences. We are involved in projects on microbial, plant and animal metabolism, each in collaboration with an experimental team.
Potential applications of our work include the design of changes in cellular metabolism to improve the output of product such as antibiotics, detecting vulnerable sites in cellular networks that could be targets for drugs to control disease-causing organisms, and improved understanding of how organisms manage to adjust their metabolism in response to environmental changes and other signals.
We also host the following web sites related to our research: