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(to be completed)

 


ThinkMind // International Journal On Advances in Life Sciences, volume 4, numbers 3 and 4, 2012 // View article lifsci_v4_n34_2012_8


Evaluation of the Prediction of Gene Knockout Effects by Minimal Pathway Enumeration

Authors:
Takehide Soh
Katsumi Inoue
Tomoya Baba
Toyoyuki Takada
Toshihiko Shiroishi

Keywords: metabolic pathways; gene knockout; prediction method; minimal pathway; Keio collection.

Abstract:
In this paper, we propose a method to predict gene knockout effects for the cell growth by utilizing biological databases such as KEGG and EcoCyc, in which biological knowledge and experimental results have been collected. At first, biological networks are constructed from such databases and configure experimental conditions by giving source metabolites, target metabolites, and knockout genes. All minimal active pathways are then enumerated, which are minimal subsets of a given network using source metabolites to produce target metabolites. Finally, the effects of gene knockouts are predicted by measuring the difference of minimal active pathways between original networks and knockout ones. In the experiments, we applied it to predict the single gene knockout effects on the glycolysis pathway and amino acids biosynthesis in Escherichia coli. We also analyze which pathways are important to Escherichia coli and predict lethal pairs of knockout genes. In the results, our method predicted three out of four essential genes, which agree with the biological results of the Keio collection containing comprehensive cell growth data. In addition, predicted lethal pairs of genes also agree with the biological results of double gene knockouts.

Pages: 154 to 165

Copyright: Copyright (c) to authors, 2012. Used with permission.

Publication date: December 31, 2012

Published in: journal

ISSN: 1942-2660

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