title: Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment.
abstract: Metabolic engineering is a research field that focuses on the design of models for metabolism, and uses computational procedures to suggest genetic manipulation. It aims to improve the yield of particular chemical or biochemical products. Several traditional metabolic engineering methods are commonly used to increase the production of a desired target, but the products are always far below their theoretical maximums. Using numeral optimisation algorithms to identify gene knockouts may stall at a local minimum in a multivariable function. This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. The dataset used in this work was from the iJO1366 Escherichia coli metabolic network. The experimental results include the production rate, growth rate and a list of knockout genes. From the comparative analysis, ABCMOMA produced better results compared to previous works, showing potential for solving genetic engineering problems.
authors.affiliation: Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. Electronic address: pwtang2@live.utm.my.
authors.forename: Phooi Wah
authors.initials: PW
authors.lastname: Tang
authors.affiliation: Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. Electronic address: ywchoon2@live.utm.my.
authors.forename: Yee Wen
authors.initials: YW
authors.lastname: Choon
authors.affiliation: Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. Electronic address: saberi@utm.my.
authors.forename: Mohd Saberi
authors.initials: MS
authors.lastname: Mohamad
authors.affiliation: Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. Electronic address: safaai@utm.my.
authors.forename: Safaai
authors.initials: S
authors.lastname: Deris
authors.affiliation: Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia. Electronic address: suhaimi@putra.upm.edu.my.
authors.forename: Suhaimi
authors.initials: S
authors.lastname: Napis
mesh_terms: D000465:Algorithms; D000818:Animals; D001516:Bees / Q000378:metabolism*; D066264:Datasets as Topic; D004926:Escherichia coli / Q000235:genetics / Q000254:growth & development / Q000378:metabolism*; D055786:Gene Knockout Techniques; D019344:Lactic Acid / Q000096:biosynthesis* / Q000378:metabolism; D060847:Metabolic Engineering; D053858:Metabolic Networks and Pathways / Q000235:genetics; D008954:Models, Biological; D019802:Succinic Acid / Q000378:metabolism*
chemical_list: D019344:Lactic Acid; D019802:Succinic Acid
keywords: Artificial bee colony; Escherichia coli; Gene knockout; Metabolic engineering; Minimisation of metabolic adjustment