Systematizing the generation of missing metabolic knowledge
Article first published online: 29 JUN 2010
Copyright © 2010 Wiley Periodicals, Inc.
Biotechnology and Bioengineering
Volume 107, Issue 3, pages 403–412, 15 October 2010
How to Cite
Orth, J. D. and Palsson, B. Ø. (2010), Systematizing the generation of missing metabolic knowledge. Biotechnol. Bioeng., 107: 403–412. doi: 10.1002/bit.22844
- Issue published online: 20 AUG 2010
- Article first published online: 29 JUN 2010
- Manuscript Accepted: 14 JUN 2010
- Manuscript Revised: 7 JUN 2010
- Manuscript Received: 12 MAR 2010
- National Institutes of Health. Grant Number: R01 GM057089
- gene annotation;
- metabolic network reconstruction;
Genome-scale metabolic network reconstructions are built from all of the known metabolic reactions and genes in a target organism. However, since our knowledge of any organism is incomplete, these network reconstructions contain gaps. Reactions may be missing, resulting in dead-ends in pathways, while unknown gene products may catalyze known reactions. New computational methods that analyze data, such as growth phenotypes or gene essentiality, in the context of genome-scale metabolic networks, have been developed to predict these missing reactions or genes likely to fill these knowledge gaps. A growing number of experimental studies are appearing that address these computational predictions, leading to discovery of new metabolic capabilities in the target organism. Gap-filling methods can thus be used to improve metabolic network models while simultaneously leading to discovery of new metabolic gene functions. Biotechnol. Bioeng. 2010;107: 403–412. © 2010 Wiley Periodicals, Inc.