Glycolytic flux control of glyceraldehyde 3-phosphate dehydrogenase in yeast

Odendaal, Christoff (2019-12)

Thesis (MSc)--Stellenbosch University, 2019.

Thesis

ENGLISH ABSTRACT: To save precious experimental time and resources and to gain a deeper understanding of living systems, modelling approaches and systems biological tools like Metabolic Control Analysis (MCA) offer the opportunity to analyse these systems at the level of integrated reaction networks. These tools can aid in the discovery of promising industrial and pharmaceutical metabolic targets. In addition, modelling promises to reduce duplication of work by allowing for the integration of existing models into larger networks that have extended predictive capacity. This is known as the modular approach to model construction. A cornerstone of the modular approach to metabolic modelling is that model expansion increases the predictive abilities of a given model instead of just changing it to describe a new, narrow set of behaviours. Glycolysis - a ubiquitous pathway responsible for glucose catabolism - was probably the first metabolic pathway to be modelled and a history of iterative model expansion is now starting to take shape based on this model. The model by Teusink et al. [1] and its descendent by Du Preez et al. [2] are two existing glycolytic models of Saccharomyces cerevisiae that represent such an expansion. Du Preez and colleagues adapted the steady-state Teusink model in silico to describe glycolytic oscillations. This presents a good opportunity to test whether the adjustment expanded the model’s predictive capacity or just changed it to a new, narrow set of behaviours. Iodoacetic acid (IAA), a specific, irreversible inhibitor of glyceraldehyde 3-phosphate dehydrogenase (GAPDH), was used to perturb yeast glycolysis for the calculation of the glycolytic flux control coefficient of GAPDH. The ability of the model to correctly predict the flux control of GAPDH would be a validation of the model. We found that both the Teusink and the Du Preez models predicted the glycolytic control of GAPDH to be close to zero, which was in good agreement with our experimental finding. Furthermore, the models could predict the effect of larger perturbations of GAPDH reasonably well. This finding is also exciting as it validates the usefulness of IAA as a chemical perturbant that can be used to experimentally measure GAPDH’s glycolytic flux control, which can be reapplied to other metabolic systems where it might have clinical or industrial significance.

AFRIKAANSE OPSOMMING: Om kosbare eksperimentele tyd en hulpbronne te bespaar en om ’n dieper begrip van lewende sisteme te bekom, bied modellering en sisteembiologiese middele die geleentheid om lewende sisteme op die vlak van geïntegreede-reaksienetwerke te analiseer. Dit kan help om belowende nywerheids- en farmaseutiese teikens in die metabolisme uit te lig. Verder beloof modellering om herhaling van werk te verminder deur vir die integrasie van bestaande modelle in groter netwerke toe te laat – hierdie uitgebreide netwerke het dan ook uitgebreide voorspellingsvermoë. Dit staan bekend as die modulêre benadering tot modelkonstruksie. ’n Hoeksteen van die modulêre benadering to metabolismemodellering is dat modeluitbreiding die voorspellingsvermoë van ’n gegewe model verbeter en nie bloot aanpas tot ’n nuwe, noue stel metaboliese gedrag nie. Glikolise - ’n algemene padweg verantwoordelik vir glukoseafbraak - was waarskynlik die eerste gemodelleerde padweg en ’n geskiedenis van herhaalde modeluitbreiding is aan’t groei gebaseer op hierdie padweg. Die model deur Teusink et al. [1] en sy afstammeling deur Du Preez et al. [2] is twee bestaande glikolisemodelle van Saccharomyces cerevisiae wat só ’n uitbreiding verteenwoordig. Du Preez en kollegas het die bestendige-toestand-model deur Teusink aangepas in silico om glikolitiese ossillasies te kan beskryf. Dit bied ’n goeie geleentheid vir ’n toets: is die model se voorspellingsvermoë uitgebrei, of bloot verstel na ’n nuwe, noue gedragsrepertoire? Jodoasynsuur (IAA), ’n spesifieke, onomkeerbare inhibitor van gliseraldehied-3-fosfaat dehidrogenase (GAPDH), is gebruik om gisglikolise te perturbeer vir die berekening van die glikolisefluksie-kontrokontolekoëffisiënt van GAPDH. Die vermoë om die fluksiekontrole van GAPDH akkuraat te voorspel, sal ’n validering van die model wees. Ons het bevind dat beide die Teusink- and die Du Preez-modelle voorspel het dat die glikolisekontrole van GAPDH byna nul is, wat goed met ons eksperimentele data ooreenstem. Verder, kon die modelle die effek van groter perturbasies van GAPDH-aktiwiteit redelik goed voorspel. Dit is ’n belowende bevinding, want dit valideer ook die nut van IAA as ’n chemise perturbasiemiddel wat eksperimenteel aangewend kan word om GAPDH se glikolitiesefluksie-beheer te bepaal. Dít kan nou gebruik word in ander metaboliese stelsels wat van kliniese of industriële belang is.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/106924
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