Kinetic model optimization and its application to mitigating the Warburg effect through multiple enzyme alterations

Conor O'Brien, Andrew Allman, Prodromos Daoutidis, Wei-Shou Hu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Pathway engineering is a powerful tool in biotechnological and clinical applications. However, many phenomena cannot be rewired with a single enzyme change, and in a complex network like energy metabolism, the selection of combinations of targets to engineer is a daunting task. To facilitate this process, we have developed an optimization framework and applied it to a mechanistic kinetic model of energy metabolism. We then identified combinations of enzyme alternations that led to the elimination of the Warburg effect seen in the metabolism of cancer cells and cell lines, a phenomenon coupling rapid proliferation to lactate production. Typically, optimization approaches use integer variables to achieve the desired flux redistribution with a minimum number of altered genes. This framework uses convex penalty terms to replace these integer variables and improve computational tractability. Optimal solutions are identified which substantially reduce or eliminate lactate production while maintaining the requirements for cellular proliferation using three or more enzymes.

Original languageEnglish (US)
Pages (from-to)154-164
Number of pages11
JournalMetabolic Engineering
Volume56
DOIs
StatePublished - Dec 2019

Keywords

  • Aerobic glycolysis
  • Central metabolism
  • Kinetic modeling
  • Lactate
  • Mathematical optimization
  • Warburg effect

PubMed: MeSH publication types

  • Journal Article

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