Explicit consideration of topological and parameter uncertainty gives new insights into a well-established model of glycolysis

Fiona Achcar, Michael P. Barrett, Rainer Breitling

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Previous models of glycolysis in the sleeping sickness parasite Trypanosoma brucei assumed that the core part of glycolysis in this unicellular parasite is tightly compartimentalized within an organelle, the glycosome, which had previously been shown to contain most of the glycolytic enzymes. The glycosomes were assumed to be largely impermeable, and exchange of metabolites between the cytosol and the glycosome was assumed to be regulated by specific transporters in the glycosomal membrane. This tight compartmentalization was considered to be essential for parasite viability. Recently, size-specific metabolite pores were discovered in the membrane of glycosomes. These channels are proposed to allow smaller metabolites to diffuse across the membrane but not larger ones. In light of this new finding, we re-analyzed the model taking into account uncertainty about the topology of the metabolic system in T. brucei, as well as uncertainty about the values of all parameters of individual enzymatic reactions. Our analysis shows that these newly-discovered nonspecific pores are not necessarily incompatible with our current knowledge of the glycosomal metabolic system, provided that the known cytosolic activities of the glycosomal enzymes play an important role in the regulation of glycolytic fluxes and the concentration of metabolic intermediates of the pathway. Previous models of glycolysis in the sleeping sickness parasite Trypanosoma brucei assumed that the core part of glycolysis in this parasite requires tight compartmentalization within an organelle, the glycosome. Recently, this idea was challenged when size-specific metabolite pores were discovered in the glycosomal membrane. We use a novel uncertainty-aware computational modelling approach to explore the consequences of this finding. © 2013 FEBS.
    Original languageEnglish
    Pages (from-to)4640-4651
    Number of pages11
    JournalFEBS Journal
    Volume280
    Issue number18
    DOIs
    Publication statusPublished - Sep 2013

    Keywords

    • computational modelling
    • glycolysis
    • parameter sampling
    • systems biology
    • topological uncertainty

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