Development of an integrated metabolic analysis toolbox

[摘要] ENGLISH ABSTRACT: Life is arguably the most complex of all natural phenomena, yet it arises from essentiallydead molecular components. The goal of systems biology is to be able to understand how theproperties and non-linear interactions of these components give rise to the functions and behaviourof living biological systems. This represents the so-called 'mechanistic explanationwhere no individual component, nor the complete system itself, is privileged.In this dissertation a Python based software package called PySCeSToolbox is presentedthat includes tools that implement previously published theoretical frameworks for investigatingkinetic models of metabolic systems. These tools are RateChar, which performs generalisedsupply-demand analysis (GSDA); SymCa, which performs symbolic metabolic controlanalysis; and ThermoKin, which distinguishes between the kinetic and thermodynamic contributionstowards enzyme-catalysed reaction rates. Each of the frameworks contained withinthe tools of PySCeSToolbox views metabolism from a different vantage point: generalisedsupply-demand analysis gives a broad overview of the behaviour, control, and regulationof metabolic systems by taking into account their functional organisation; symbolic controlanalysis dissects the control properties of metabolic systems in terms of the physical chains ofinteractions between enzymes and metabolic intermediates; and the thermodynamic/kineticframework zooms in on the properties of the enzymes themselves to determine their regulatoryroles. The strength of PySCeSToolbox lies in its integration of these viewpoints into asingle analysis package in a way that promotes their complementary use in the search for amechanistic explanation of modelled metabolic systems.Through the application of these tools in the investigation of two previously publishedmetabolic models, new knowledge regarding their behaviour is uncovered and subsequentlyexplained in terms of their component properties and interactions. In a model of aspartatederivedamino-acid synthesis, a GSDA reveals that aspartate-semialdehyde regulates the reactionblock that produces it via the reaction blocks that consume it, in spite of the relativelyhigh sensitivity of its supply enzyme towards this intermediate. Subsequently, the regulatorycontributions of each of the four aspartate-semialdehyde consuming blocks towards theproducing block are quantified. In a model of pyruvate branch metabolism, application ofGSDA shows that the flux through a NADH/NAD+ consuming reaction block decreases whenthe ratio of NADH to NAD+ increases. Rather than being a result of substrate inhibition, thisphenomenon is shown to be the result of an interaction of the NADH/NAD+ intermediateswith a reaction elsewhere in the pathway.Symbolic control analysis of the pyruvate branch model exposes a number of features thatexplain the unintuitive flux response described above. Firstly, only some control patterns areimportant for determining the flux control at any time. Secondly, different control patternsare dominant under different conditions, and dominance shifts as these conditions change.Finally, dissection of these chains of effects identifies the components of the system that areresponsible for the flux control. Additional use of the thermodynamic/kinetic framework tofocus on the enzymes that constitute the control patterns relates their values to the propertiesof individual enzyme-catalysed reactions (i.e. their elasticities). This framework is alsoused to explain the behaviour of the elasticity coefficient components of the unintuitive fluxresponse, which are shown to be mostly mass-action controlled. Ultimately this two-prongedstrategy provides a mechanistic explanation of the flux response, in which this high-levelproperty is quantitatively linked to various low-level components.The design of PySCeSToolbox as a Python-based software library allows it to integratewith the existing scientific Python ecosystem, thus providing access to a variety of additionalthird-party software tools to aid in the analysis of metabolic systems. This design also encouragesthe use of a scripting approach to designing in silico modelling experiments, which inturn promotes reproducibility through the re-use of such scripts. Moreover, PySCeSToolboxprovides computational access to theoretical analysis frameworks that would otherwise havebeen inaccessible to researchers, as these frameworks are not implemented elsewhere.

[发布机构] Stellenbosch University