2014 Fiscal Year Annual Research Report
Ｆｌｕｘｏｍｉｃ ａｐｐｒｏａｃｈｅｓ ｆｏｒ Ｙｅａｓｔ ｍｅｔａｂｏｌｉｓｍ
| Project/Area Number |
24510268
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| Research Institution | Keio University |
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Principal Investigator |
MURRAY Douglas 慶應義塾大学, 政策・メディア研究科, 特任准教授 (50458965)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Keywords | 国際研究者交流 / ドイツ：オーストリア：英国 / 計算および実験結果の交換 |
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| Outline of Annual Research Achievements |
We developed a tool to map SBML Model to carbon atom transition maps. This was applied to the Yeast community FBA model and we are currently writing a paper for this software. This work is in collaboration with Glasgow and Vienna Universities.
We used this model in INCA (http://mfa.vueinnovations.com/) to estimate the fluxes during isotopically stable and non-stable experiments.
Our data showed that during high respiration significant flux is directed towards ATP biosynthesis. Some of these data were integrated into a global view of histone regulation (Amariei, et al. 2014). Moreover, many of the algorithms used to analyse these data were published (Amariei, et al. 2014).
We are also finalising a manuscript on the importance of CO2 assimilation and lipid mobilisation during the yeast respiratory oscillation. These data confirmed that lipids and CO2 fuel the high respiration.
A new Dynamic Flux balance analyses method (cyclic FBA) was developed, which method allows for the prediction of metabolic fluxes with little a priori knowledge. We are currently comparing simulated results with measured fluxes and preparing a manuscript. These data show that during the change from catabolism to anabolism in the cell the cytoplasic fluxes are surprisingly stable, and mitochondrial dynamics for ethanol uptake and amino acid biosynthesis precursors are important. Parts of this work were presented at the Isaac Newton Institute and was done in collaboration with Humboldt University.
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[Presentation] Optimal metabolic dynamics resolved by cyclic FBA2014
Author(s)
Sabrina Hoffmann, Willi Gottstein, Rainer Machne, Ralf Steuer, Douglas Murray
Organizer
Stoichiometric modelling (SM) of microbial metabolism
Place of Presentation
Isaac Newton Institute for Mathematical Science, Cambridge University (UK)
Year and Date
2014-11-04 – 2014-11-04
Invited
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