(567k) Redesigning Microbial Production Systems Under Thermodynamic Constraints
AIChE Annual Meeting
2010
2010 Annual Meeting
Food, Pharmaceutical & Bioengineering Division
Poster Session: Bioengineering
Wednesday, November 10, 2010 - 6:00pm to 8:00pm
We present a two-stage computational framework that guides the pathway modification of a genome-scale microbial metabolic network for the overproduction of a desired chemical. The modification considers both addition of non-native functionalities from external databases such as KEGG [1] and from hypothetical enzyme reactions generated using a framework called BNICE [2]. The algorithm computes a list of the top operational modes of the super-network preferred by the microbe by solving a mixed-integer linear programming (MILP) problem which maximizes the biomass yield. This can be done by imposing integer cuts which iteratively cut off previously obtained solutions from the feasible region in looking for the next best solution. After obtaining each preferred operational mode for the super-network, we fix the network architecture and calculate the ranges of the production rates of our desired chemical by solving a linear programming (LP) problem. Notice that in both stages, thermodynamics of the biochemical reactions are explicitly considered in the form of linear constraints, which we first employed in the genome-scale thermodynamic analysis of E. coli metabolism [3] and the analysis of metabolic network diversity [2]. The results give a ranked list of biochemical activities to add and to knock out in redesigning microbial hosts.
[1] Kanehisa, M., S. Goto, M. Hattori, K. F. Aoki-Kinoshita, M. Itoh, S. Kawashima, T. Katayama, M. Araki, and M. Hirakawa. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 34: D354-D357 (2006).
[2] Hatzimanikatis, V., C. Li, J. A. Ionita, C. S. Henry, M. D. Jankowski, and L. J. Broadbelt. Exploring the diversity of complex metabolic networks. Bioinformatics 21: 1603-1609 (2005).
[3] Henry, C. S., M. D. Jankowski, L. J. Broadbelt, and V. Hatzimanikatis. Genome-scale thermodynamic analysis of Escherichia coli metabolism. Biophys. J. 90: 1453-1461 (2006).