ArticlePloS one2013
ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 47 citations in OpenAlex.
- Monitoring and modelling the glutamine metabolic pathway: a review and future perspectives.Metabolomics : Official journal of the Metabolomic Society · 2023Review
- Highlighting the potential ofFrontiers in microbiology · 2023Article
- Examining organic acid production potential and growth-coupled strategies in Issatchenkia orientalis using constraint-based modeling.Biotechnology progress · 2022Article
- Genome-driven cell engineering review:Essays in biochemistry · 2019Review
- Engineering biological systems using automated biofoundries.Metabolic engineering · 2017Review
- IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.Scientific reports · 2017Article
- In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories.Microbiology and molecular biology reviews : MMBR · 2016Review
- Co-evolution of strain design methods based on flux balance and elementary mode analysis.Metabolic engineering communications · 2015Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP) based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT) method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.
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Registered trials
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