3335
Comment: Added link to US travel grant procedure.
|
4908
|
Deletions are marked like this. | Additions are marked like this. |
Line 4: | Line 4: |
=== Meeting news === '''Metabolic Pathway Analysis 2013''' will be held in Oxford, 16-20 September. See its [[http://www.accliphot.eu/mpa-2013/|website]] for details. |
== News == == Metabolic Pathway Analysis 2019 == . This was held in Riga, Latvia, 12-16 August. Details are at https://events.lu.lv/MPA2019 |
Line 7: | Line 8: |
'''News:''' NSF has funded some travel grants for US attendees. The application procedure is given on the [[http://www.accliphot.eu/mpa-2013/|conference website]], closing date 15 August 2013. | == Understanding the Control of Metabolism == . David Fell's 1997 book is now available via !ResearchGate. |
Line 9: | Line 12: |
'''New paper online ahead of print:''' Maurice Cheung et al, A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions. The Plant Journal .[[http://onlinelibrary.wiley.com/doi/10.1111/tpj.12252/abstract|accepted manuscript]] | == 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. ''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 |
Line 11: | Line 15: |
'''Previous paper: '''Mark G. Poolman, Sudip Kundu, Rahul Shaw and David A Fell. Responses to Light Intensity in a Genome–Scale Model of Rice Metabolism. ''Plant Physiology'', 162, 1060-1072, 2013, [[./Publications/articles|PDF]] available. [ [[http://dx.doi.org/10.1104/pp.113.216762|DOI: 10.1104/pp.113.216762]] ] ----- |
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]] |
Line 14: | Line 24: |
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 '''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. |
Line 16: | Line 26: |
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. | . 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. |
Line 18: | Line 28: |
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. | . 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. |
Line 24: | Line 34: |
* [[http://sysbio.brookes.ac.uk|The website of the International Study Group for Systems Biology]] |
* [[http://sysbio.brookes.ac.uk|The website of the International Study Group for Systems Biology]] |
Line 27: | Line 36: |
* [[http://mpa.brookes.ac.uk|The website for the Metabolic Pathways Analysis series of meetings]] * [[http://mitoscop.brookes.ac.uk|The website for the BBSRC-ANR project MitoScoP]] * [[http://frim.brookes.ac.uk|The website for the EraSysBio+ project Fruit Integrative Modelling]] |
* [[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: