An extended and generalized framework for the calculation of metabolic intervention strategies based on minimal cut sets

PLoS Comput Biol. 2020 Jul 27;16(7):e1008110. doi: 10.1371/journal.pcbi.1008110. eCollection 2020 Jul.

Abstract

The concept of minimal cut sets (MCS) provides a flexible framework for analyzing properties of metabolic networks and for computing metabolic intervention strategies. In particular, it has been used to support the targeted design of microbial strains for bio-based production processes. Herein we present a number of major extensions that generalize the existing MCS approach and broaden its scope for applications in metabolic engineering. We first introduce a modified approach to integrate gene-protein-reaction associations (GPR) in the metabolic network structure for the computation of gene-based intervention strategies. In particular, we present a set of novel compression rules for GPR associations, which effectively speedup the computation of gene-based MCS by a factor of up to one order of magnitude. These rules are not specific for MCS and as well applicable to other computational strain design methods. Second, we enhance the MCS framework by allowing the definition of multiple target (undesired) and multiple protected (desired) regions. This enables precise tailoring of the metabolic solution space of the designed strain with unlimited flexibility. Together with further generalizations such as individual cost factors for each intervention, direct combinations of reaction/gene deletions and additions as well as the possibility to search for substrate co-feeding strategies, the scope of the MCS framework could be broadly extended. We demonstrate the applicability and performance benefits of the described developments by computing (gene-based) Escherichia coli strain designs for the bio-based production of 2,3-butanediol, a chemical, that has recently received much attention in the field of metabolic engineering. With our extended framework, we could identify promising strain designs that were formerly unpredictable, including those based on substrate co-feeding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adenosine Triphosphate / chemistry
  • Aerobiosis
  • Algorithms
  • Butylene Glycols / pharmacology
  • Computer Simulation
  • Escherichia coli / genetics*
  • Gene Deletion*
  • Industrial Microbiology
  • Metabolic Engineering / methods*
  • Metabolic Networks and Pathways*
  • Models, Biological
  • Models, Statistical
  • Oxidation-Reduction
  • Stochastic Processes

Substances

  • Butylene Glycols
  • 2,3-butylene glycol
  • Adenosine Triphosphate

Grants and funding

PS and SK received funding from the European Research Council (Grant 721176). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.