Title: Virtualisation of gene knockout experiments based on kinetic modelling: Escherichia coli as an algorithmic case

Authors: Rudong Li; Guohui Ding; Yixue Li

Addresses: Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China ' Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Bioinformation Technology, Shanghai 200235, China ' Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Bioinformation Technology, Shanghai 200235, China

Abstract: Since substantial biological studies focus on molecular essentialities (e.g., gene knockout experiments), virtualisation of such studies saves experimental costs and facilitates knowledge acquisition and bio-engineering. Nevertheless, non-quantitative methods are incompetent and the traditional flux-balance analysis (FBA) is less effective at physiological rather than genome scale. In this respect, kinetic modelling can simulate bio-pathway dynamics and enhance functional characterisations of bio-molecules. However, conventional sensitivity or flux control analysis has limited predictive ability for structural perturbations like gene knockouts. Thus we hereby conceived a novel algorithm for in silico evaluating molecular essentialities based on dynamical systems. Exemplified by E. coli central carbon metabolism, our method was accurate. We found that E. coli central metabolic genes could be categorised into four types of essentiality; moreover, E. coli metabolism might be supported by a minimum of six genes. Additionally, comparing with FBA and a previous kinetic-modelling method, our method was more effective.

Keywords: gene essentiality; molecular knockout; in silico evaluation; kinetic modelling; system collapse; dysfunctionality; cell survivability; fundamental physiology; E. coli; central metabolism.

DOI: 10.1504/IJCBDD.2017.083879

International Journal of Computational Biology and Drug Design, 2017 Vol.10 No.2, pp.157 - 188

Received: 04 Aug 2016
Accepted: 19 Sep 2016

Published online: 15 Apr 2017 *

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