A model-driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K-12 MG1655 that is biochemically and thermodynamically consistent
Version of Record online: 19 NOV 2013
© 2013 Wiley Periodicals, Inc.
Biotechnology and Bioengineering
Volume 111, Issue 4, pages 803–815, April 2014
How to Cite
McCloskey, D., Gangoiti, J. A., King, Z. A., Naviaux, R. K., Barshop, B. A., Palsson, B. O. and Feist, A. M. (2014), A model-driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K-12 MG1655 that is biochemically and thermodynamically consistent. Biotechnol. Bioeng., 111: 803–815. doi: 10.1002/bit.25133
- Issue online: 22 FEB 2014
- Version of Record online: 19 NOV 2013
- Accepted manuscript online: 12 OCT 2013 04:32AM EST
- Manuscript Accepted: 7 OCT 2013
- Manuscript Revised: 30 AUG 2013
- Manuscript Received: 26 JUN 2013
- Novo Nordisk Foundation
Additional supporting information may be found in the online version of this article at the publisher's web-site.
Figure S1. Rapid sampling growth characterization. A: Anaerobic steady-state consumption/production rate comparison. B: Aerobic steady-state consumption/production rate comparison. C: End fermentation profile for anaerobic cultures. D: Biomass and pH versus time for anaerobic growth. Not shown for the anaerobic conditions are the end fermentation pH values, which were found to be 4.8 ± 0.12 and 4.7 ± 0.02 for the rapid sampler and the anaerobic chamber, respectively.
Figure S2. Rapid sampling apparatus sampling reproducibility for sample volumes of interest. Error bars are representative of standard deviations taken from triplicates of water at a volume of 200 mL.
Figure S3. Thermodynamic reaction coverage. The distribution of reaction calls per subsystem in the iJO1366 network for 50 randomly selected metabolites repeated 10,000 times from the top 500 compounds are compared to the number of reactions calls that were allowed to be made based on the measured metabolites for anaerobic and aerobic growth conditions. There is less than 4%, 0.6%, 0.2%, and 0.06% chance of randomly selecting metabolites to be able to call the reaction reversibility based on thermodynamics for 1, 2, 3, and 4 reactions, respectively, in each of the subsystems according to the reaction coverage criteria defined in the Materials and Methods Section.
Table S1. Transitions, fragmentation patterns, and lower/upper limits of quantitation for compounds monitored in this study.
Table S2. Quantitative metabolomics of anaerobic and aerobic steady-state metabolism.
Table S3. Pathway thermodynamic feasibility.
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