Abstract
The advent of genome-scale models of metabolism has laid the foundation for the development of computational procedures for suggesting genetic manipulations that lead to overproduction. Previously, for increasing the production of Lactate in E. coli, a traditional method of chemical synthesis was being used, this always lead the products are far below their theoretical maximums. This is not surprise as the cellular metabolism is always competing with the chemical overproduction. Besides, several optimization algorithms often get stuck at a local minimum in a multi-modal error. In this research, a hybrid of Artificial Bee Colony (ABC) and Flux Balance Analysis (FBA) is proposed for suggesting gene deletion strategies leading to the overproduction of Lactate in E. coli. In this work, the ABC is introduced as an optimization algorithm based on the intelligent behavior of honey bee swarm. As for the evaluation of fitness part, each mutant strain is evaluated by resorting to the simulation of its phenotype using the FBA, together with the premise that microorganisms have maximized their growth along natural evolution. This is the first research that successfully combined ABC and FBA for identifying optimum knockout strategies. The successfully created hybrid algorithm is applied to the E. coli model dataset.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hofvendahl, K., Hahn-Hagerdal, B.: Factors Affecting the Fermentative Lactic Acid Production from Renewable Resources. Enzyme and Microbial Technology 26(2-4), 87–107 (2000)
John, R.P., Nampoothiri, K.M., Pandey, A.: Production of L(+) Lactic Acid from Cassava Starch Hydrolyzate by Immobilized Lactobacillus delbrueckii. J. Basic Microbiol. 47(1), 25–30 (2007)
Chang, D.E., Jung, H.C., Rhee, J.S., Pan, J.G.: Homofermentative Production of D- or L-Lactate in Metabolically Engineered Escherichia coli RR1. Appl. Environ. Microbiol. 65(4), 1384–1389 (1999)
Karaboga, D., Basturk, B.: A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm. Journal of Global Optimization 39(3), 459–471 (2007)
Edwards, J.S., Palsson, B.O.: Metabolic Flux Balance Analysis and The In Silico Analysis of Escheichia coli K-12 Gene Deletions. BMC Bioinformatics 1, 1 (2000)
Hua, Q., Joyce, A.R., Fong, S.S., Palsson, B.O.: Metabolic Analysis of Adaptive Evolution for In Silico-Designed Lactate-Producing Strains. Biotechnology and Bioengineering 95(5), 992–1002 (2006)
Zhou, L., Zuo, Z.R., Chen, X.Z., Niu, D.D., Tian, K.M., Bernard, A.P., et al.: Evaluation of Genetic Manipulation Strategies on D-Lactate Production By Escherichia Coli. Current Microbiology 62(3), 981–989 (2010)
Zhu, Y., Eiteman, M.A., DeWitt, K., Altman, E.: Homolactate Fermentation by Metabolically Engineered Escherichia coli Strain. Applied and Environmental Microbiology 73(2), 456–464 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, S.S. et al. (2013). A Hybrid of Artificial Bee Colony and Flux Balance Analysis for Identifying Optimum Knockout Strategies for Producing High Yields of Lactate in Echerichia Coli . In: Sidhu, A., Dhillon, S. (eds) Advances in Biomedical Infrastructure 2013. Studies in Computational Intelligence, vol 477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37137-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-37137-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37136-3
Online ISBN: 978-3-642-37137-0
eBook Packages: EngineeringEngineering (R0)