International Study Group for Systems Biology 2020
This was held on 10-12 September as a hybrid online-physical meeting. Some information is given on the current ISGSB site.
Understanding the Control of Metabolism
David Fell's 1997 book is now available via ResearchGate.
Noemi Tejera, Lisa Crossman, Bruce Pearson, Emily Stoakes, Fauzy Nasher, Bilal Djeghout, Mark Poolman, John Wain, Dipali Singh. Genome-scale metabolic model driven design of a defined medium for Campylobacter jejuni M1cam. Frontiers in Microbiology, 11, 1072 (2020). https://doi.org/10.3389/fmicb.2020.01072
Thea SB Møller, Gang Liu, Hassan B Hartman, Martin H Rau, Sisse Mortensen, Kristian Thamsborg, Andreas E Johansen, Morten OA Sommer, Luca Guardabassi, Mark G Poolman, John E Olsen. Global responses to oxytetracycline treatment in tetracycline-resistant Escherichia coli. Sci Rep 10, 8438 (2020). https://doi.org/10.1038/s41598-020-64995-1
Lieven, C., Beber, M.E., Olivier, B.G., Poolman M.G et al. MEMOTE for standardized genome-scale metabolic model testing. Nat Biotechnol 38, 272–276 (2020). https://doi.org/10.1038/s41587-020-0446-y
Woodfield, Helen; Fenyk, Stepan; Wallington, Emma; Bates, Ruth; Brown, Alexander; Guschina, Irina; Marillia, Elizabeth; Taylor, David; Fell, David; Harwood, John; Fawcett, Tony. Increase in lysophosphatidate acyltransferase activity in oilseed rape (Brassica napus L.) increases seed triacylglycerol content despite its low intrinsic flux control coefficient. New Phytologist, 224, 700-711 (2019). https://doi.org/10.1111/nph.16100
Rupert O. J. Norman, Thomas Millat, Sarah Schatschneider, Anne M. Henstra, Ronja Breitkopf, Bart Pander, Florence J. Annan, Pawel Piatek, Hassan B. Hartman, Mark G. Poolman, David A.Fell, Klaus Winzer, Nigel P. Minton and Charlie Hodgman. A genome-scale model of Clostridium autoethanogenum reveals optimal bioprocess conditions for .high-value chemical production from carbon monoxide. Engineering Biology, 3:32 (2019). Open Access https://doi.org/10.1049/enb.2018.5003
Pfau, Christian, Masakapalli, Poolman, Sweetlove & Ebenhoe. The intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling. Nature Scientific Reports, 8:12504(2018) https://www.nature.com/articles/s41598-018-30884-x DOI
Zia Fatma, Hassan Hartman, Mark G. Poolman, David A. Fell, Shireesh Srivastava , Tabinda Shakeela and Syed Shams Yazdani. Model-assisted metabolic engineering of Escherichia coli for long chain alkane and alcohol production, Metabolic Engineering, 45, 134-141 (2018). DOI
Our group began nearly forty 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: