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| '''News:''' | {{attachment:csmgbanner.png|cell systems group banner}} |
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| '''Advance notice. The Biochemical Society has approved plans for the 71st Harden Conference 19-23 September 2011: Metabolic Pathway Analysis 3.''' | ----- == News == == Metabolic Pathway Analysis 2019 == . This was held in Riga, Latvia, 12-16 August. Details are at https://events.lu.lv/MPA2019 |
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| == Understanding the Control of Metabolism == . David Fell's 1997 book is now available via !ResearchGate. |
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| 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. | ----- == Latest papers: == 1. Woodfield, Helen; Fenyk, Stepan; Wallington, Emma; Bates, Ruth; Brown, Alexander; Guschina, Irina; Marillia, Elizabeth; Taylor, David; Fell, David; Harwood, John; Fawcett, Tony. |
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| 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. | ''Increase in lysophosphatidate acyltransferase activity in oilseed rape (Brassica napus L.) increases seed triacylglycerol content despite its low intrinsic flux control coefficient. '' New Phytologist, in press (2019). https://doi.org/10.1111/nph.16100 |
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| 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. <<latex(a$^1$)>> |
1. 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, (2019). [[http://ietdl.org/t/gbNTm|Open Access]] https://doi.org/10.1049/enb.2018.5003 == Previous papers: == * Pfau, Christian, Masakapalli, Poolman, Sweetlove & Ebenhoe. ''The intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling. ''Nature Scientific Reports, (2018) https://www.nature.com/articles/s41598-018-30884-x [[https://doi.org/10.1038/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). [[https://doi.org/10.1016/j.ymben.2018.01.002|DOI]] * Ahmad Ahmad, Hassan B. Hartman , S. Krishnakumar, David A. Fell , Mark G. Poolman , Shireesh Srivastava. ''A Genome Scale Model of ''Geobacillus thermoglucosidasius'' (C56-YS93) reveals its biotechnological potential on rice straw hydrolysate''. J. Biotech. '''251,''' 30-37 (2017) [[http://dx.doi.org/10.1016/j.jbiotec.2017.03.031|DOI]] (This work was part of the [[http://www.ricefuel.net/index.html|Ricefuel]] project funded by the BBSRC and the DBT, India). <<BR>> * Pentjuss A., Stalidzans E., Liepins J., Kokina A., Martynova J., Zikmanis P., Mozga I., Scherbaka R., Hartman H., Poolman M. G., Fell D. A., Vigants A. '' Model based biotechnological potential analysis of ''Kluyveromyces marxianus'' central metabolism''. J. Industrial Microbiology and Biotechnology, '''44''', 1177-1190 (2017). [[http://mudshark.brookes.ac.uk/Publications/10.1007/s10295-017-1946-8|DOI]] = Background = . 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. ----- = Related Sites = We also host the following web sites related to our research: * [[http://sysbio.brookes.ac.uk|The website of the International Study Group for Systems Biology]] * [[http://mpa.brookes.ac.uk|The website for the Metabolic Pathways Analysis series of meetings]] |
News
Metabolic Pathway Analysis 2019
This was held in Riga, Latvia, 12-16 August. Details are at https://events.lu.lv/MPA2019
Understanding the Control of Metabolism
David Fell's 1997 book is now available via ResearchGate.
Latest papers:
- 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, in press (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, (2019). Open Access https://doi.org/10.1049/enb.2018.5003
Previous papers:
Pfau, Christian, Masakapalli, Poolman, Sweetlove & Ebenhoe. The intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling. Nature Scientific Reports, (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
Ahmad Ahmad, Hassan B. Hartman , S. Krishnakumar, David A. Fell , Mark G. Poolman , Shireesh Srivastava. A Genome Scale Model of Geobacillus thermoglucosidasius (C56-YS93) reveals its biotechnological potential on rice straw hydrolysate. J. Biotech. 251, 30-37 (2017) DOI (This work was part of the Ricefuel project funded by the BBSRC and the DBT, India).
Pentjuss A., Stalidzans E., Liepins J., Kokina A., Martynova J., Zikmanis P., Mozga I., Scherbaka R., Hartman H., Poolman M. G., Fell D. A., Vigants A. Model based biotechnological potential analysis of Kluyveromyces marxianus central metabolism. J. Industrial Microbiology and Biotechnology, 44, 1177-1190 (2017). DOI
Background
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.
Related Sites
We also host the following web sites related to our research: