Applications of generalised supply-demand analysis

[摘要] ENGLISH ABSTRACT: Supply-demand analysis (SDA) is a tool that allows for the control, regulationand behaviour of metabolic pathways to be understood. In this framework, reactionsare grouped into reaction blocks that represent the supply and demand of ametabolic product. The elasticities of these supply and demand blocks can be usedto determine the degree of control either block has over the flux in the pathwayand the degree of homoeostasis of the metabolic product that links the blocks. Ratecharacteristic plots, on which the rates of supply and demand blocks are plotted asfunctions of the concentration of the linking metabolite, represent a powerful visualtool in this framework.Generalised supply-demand analysis (GSDA) allows for the analysis of metabolicmodels of arbitrary size and complexity without prior knowledge of the regulatorystructure of the pathway. This is achieved by performing SDA on each variablemetabolite in a pathway instead of choosing a single linking metabolite. GSDA alsoprovides other benefits over SDA as it allows for potential sites of regulation andregulatory metabolites to be identified. Additionally it allows for the identificationand quantification of the relative contribution of di erent routes of regulation froman intermediate to a reaction block.Moiety-conserved cycles present a challenge in performing in silico SDA or GSDA,as the total concentration of a moiety must remain constant, thereby limiting therange of possible concentrations of the metabolites between which it cycles. The firstgoal of this thesis was to develop methods to perform GSDA on two-membered andinterlinked moiety-conserved cycles. We showed that by expressing the membersof a moiety-conserved cycle as a ratio, rather than individual metabolite concentrations,we can freely vary the ratio without breaking moiety conservation in aGSDA. Furthermore, we showed that by linking the concentrations of the membersof two interlinked two-membered moiety-conserved cycles to a 'linking metabolite,we could vary the concentration of this metabolite, within constraints, without breaking moiety conservation.The Python Simulator for Cellular Systems (PySCeS) is a software package developedwithin our group that provides a variety of tools for the analysis of cellularsystems. The RateChar module for PySCeS was previously developed as a tool toperform GSDA on kinetic models of metabolic pathways by automatically generatingrate characteristic plots for each variable metabolite in a pathway. The plotsgenerated by RateChar, however, were at times unclear when the models analysedwere too complex. Additionally, invalid results where steady-states could not bereached were not filtered out, and therefore appeared together with valid results onthe rate characteristic plots generated by RateChar. We therefore set out to improveupon RateChar by building plotting interface that produces clear and error-free ratecharacteristics. The resulting RCFigure class allows users to interactively changethe composition of a rate characteristic plot and it includes automatic error checking.It also provides clearer rate characteristics with e ective use of colour.Using these tools two case studies were undertaken. In the first, GSDA was used toinvestigate the regulation of aspartate-derived amino acid synthesis in Arabidopsisthaliana. A central result was that the direct interaction of aspartate-semialdehyde(ASA), a metabolite at a branch point in the pathway, with the enzyme that producesit only accounts for 7% of the total response in the flux of supply. Instead,89% of the observed flux response was due to ASA interacting with of the downstreamenzymes for which it is a substrate. This result was unexpected as the ASAproducing enzyme had a high elasticity towards ASA.In a second case study moiety-conserved cycles in a model of the pyruvate branchesin lactic acid bacteria were linearised using the above mentioned method. Thisserved to illustrate how multiple reaction blocks are connected by these conservedmoieties. By performing GSDA on this model, we demonstrated that the interactionsof these conserved moieties with the various reaction blocks in the pathway,led to non-monotonic behaviour of the rate characteristics of the supply and demandfor the moiety ratios. An example of this is that flux would increase inresponse to an increase in product for certain ranges.This thesis illustrates the power of GSDA as an entry point in studying metabolicpathways, as it can potentially reveal properties of the regulation and behaviour ofmetabolic pathways that were not previously known, even if these pathways weresubjected to previous analysis and a kinetic model is available. In general it alsodemonstrates how e ective analysis tools and metabolic models are vital for thestudy of metabolism.

[发布机构] Stellenbosch University