FastPros: screening of reaction knockout strategies for metabolic engineering

Motivation: Although constraint-based flux analysis of knockout strains has facilitated the production of desirable metabolites in microbes, current screening methods have placed a limitation on the number knockouts that can be simultaneously analyzed. Results: Here, we propose a novel screening method named FastPros. In this method, the potential of a given reaction knockout for production of a specific metabolite is evaluated by shadow pricing of the constraint in the flux balance analysis, which generates a screening score to obtain candidate knockout sets. To evaluate the performance of FastPros, we screened knockout sets to produce each metabolite in the entire Escherichia coli metabolic network. We found that 75% of these metabolites could be produced under biomass maximization conditions by adding up to 25 reaction knockouts. Furthermore, we demonstrated that using FastPros in tandem with another screening method, OptKnock, could further improve target metabolite productivity. Availability and implementation: Source code is freely available at http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/FastPros/, implemented in MATLAB and COBRA toolbox. Contact: chikara.furusawa@riken.jp or shimizu@ist.osaka-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

[1]  Miguel Rocha,et al.  OptFlux: an open-source software platform for in silico metabolic engineering , 2010, BMC Systems Biology.

[2]  Kevin M. Smith,et al.  Metabolic engineering of Escherichia coli for 1-butanol production. , 2008, Metabolic engineering.

[3]  Adam M. Feist,et al.  The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli , 2008, Nature Biotechnology.

[4]  Sunwon Park,et al.  Prediction of novel synthetic pathways for the production of desired chemicals , 2010, BMC Systems Biology.

[5]  Tomer Shlomi,et al.  Predicting metabolic engineering knockout strategies for chemical production: accounting for competing pathways , 2010, Bioinform..

[6]  Ali R. Zomorrodi,et al.  Mathematical optimization applications in metabolic networks. , 2012, Metabolic engineering.

[7]  Sean R. Collins,et al.  A tool-kit for high-throughput, quantitative analyses of genetic interactions in E. coli , 2008, Nature Methods.

[8]  J. Nielsen,et al.  Fuel ethanol production from lignocellulose: a challenge for metabolic engineering and process integration , 2001, Applied Microbiology and Biotechnology.

[9]  H. Shimizu,et al.  In silico screening of triple reaction knockout Escherichia coli strains for overproduction of useful metabolites. , 2013, Journal of bioscience and bioengineering.

[10]  Tom M. Conrad,et al.  Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models , 2010, Molecular systems biology.

[11]  Chikara Furusawa,et al.  Reconstruction and verification of a genome-scale metabolic model for Synechocystis sp. PCC6803 , 2011, Applied Microbiology and Biotechnology.

[12]  A. Burgard,et al.  Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol. , 2011, Nature chemical biology.

[13]  M. Levandowsky,et al.  Distance between Sets , 1971, Nature.

[14]  J. Reed,et al.  Large-Scale Bi-Level Strain Design Approaches and Mixed-Integer Programming Solution Techniques , 2011, PloS one.

[15]  S. Lee,et al.  Metabolic engineering of Escherichia coli for the production of l-valine based on transcriptome analysis and in silico gene knockout simulation , 2007, Proceedings of the National Academy of Sciences.

[16]  Jason A. Papin,et al.  Applications of genome-scale metabolic reconstructions , 2009, Molecular systems biology.

[17]  G. Stephanopoulos,et al.  Identifying gene targets for the metabolic engineering of lycopene biosynthesis in Escherichia coli. , 2005, Metabolic engineering.

[18]  Jens Nielsen,et al.  Evolutionary programming as a platform for in silico metabolic engineering , 2005, BMC Bioinformatics.

[19]  B. Palsson,et al.  Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110 , 1994, Applied and environmental microbiology.

[20]  Mithilesh Mishra,et al.  Faculty Opinions recommendation of High-throughput, quantitative analyses of genetic interactions in E. coli. , 2008 .

[21]  R. K. De,et al.  Comparing methods for metabolic network analysis and an application to metabolic engineering. , 2013, Gene.

[22]  Jonathan A. Kelner,et al.  Large-scale identification of genetic design strategies using local search , 2009, Molecular systems biology.

[23]  Costas D Maranas,et al.  OptStrain: a computational framework for redesign of microbial production systems. , 2004, Genome research.

[24]  Chikara Furusawa,et al.  Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum , 2009, Microbial cell factories.

[25]  Hiroshi Shimizu,et al.  An in silico platform for the design of heterologous pathways in nonnative metabolite production , 2012, BMC Bioinformatics.

[26]  J. Keasling Manufacturing Molecules Through Metabolic Engineering , 2010, Science.

[27]  Jeffrey D Orth,et al.  What is flux balance analysis? , 2010, Nature Biotechnology.

[28]  J. Foster,et al.  Evolution of Bacterial Phosphoglycerate Mutases: Non-Homologous Isofunctional Enzymes Undergoing Gene Losses, Gains and Lateral Transfers , 2010, PloS one.

[29]  Jennifer L. Reed,et al.  OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains , 2010, BMC Systems Biology.

[30]  C. Wittmann,et al.  From zero to hero--design-based systems metabolic engineering of Corynebacterium glutamicum for L-lysine production. , 2011, Metabolic engineering.

[31]  C. Maranas,et al.  An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems. , 2006, Metabolic engineering.

[32]  Hiroshi Shimizu,et al.  Metabolic engineering--integrating methodologies of molecular breeding and bioprocess systems engineering. , 2002, Journal of bioscience and bioengineering.

[33]  Dennis Eichmann,et al.  Metabolic Engineering Principles And Methodologies , 2016 .

[34]  Adam M. Feist,et al.  A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information , 2007, Molecular systems biology.

[35]  A. Burgard,et al.  Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization , 2003, Biotechnology and bioengineering.

[36]  R. Mahadevan,et al.  The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. , 2003, Metabolic engineering.

[37]  F. Blattner,et al.  In silico design and adaptive evolution of Escherichia coli for production of lactic acid. , 2005, Biotechnology and bioengineering.

[38]  H. Mori,et al.  Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection , 2006, Molecular systems biology.

[39]  Julio Vera,et al.  Multi-objective steady state optimization of biochemical reaction networks using a constrained genetic algorithm , 2008, Comput. Chem. Eng..