Doctoral Degrees (Biochemistry)
Permanent URI for this collection
Browse
Browsing Doctoral Degrees (Biochemistry) by Author "Christensen, Carl David"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
- ItemDevelopment of an integrated metabolic analysis toolbox(Stellenbosch : Stellenbosch University, 2016-12) Christensen, Carl David; Rohwer, Johann Martin; Hofmeyr, Jan-Hendrik Servaas; Stellenbosch University. Faculty of Science. Dept. of Biochemistry.ENGLISH ABSTRACT: Life is arguably the most complex of all natural phenomena, yet it arises from essentially dead molecular components. The goal of systems biology is to be able to understand how the properties and non-linear interactions of these components give rise to the functions and behaviour of living biological systems. This represents the so-called “mechanistic explanation” where no individual component, nor the complete system itself, is privileged. In this dissertation a Python based software package called PySCeSToolbox is presented that includes tools that implement previously published theoretical frameworks for investigating kinetic models of metabolic systems. These tools are RateChar, which performs generalised supply-demand analysis (GSDA); SymCa, which performs symbolic metabolic control analysis; and ThermoKin, which distinguishes between the kinetic and thermodynamic contributions towards enzyme-catalysed reaction rates. Each of the frameworks contained within the tools of PySCeSToolbox views metabolism from a different vantage point: generalised supply-demand analysis gives a broad overview of the behaviour, control, and regulation of metabolic systems by taking into account their functional organisation; symbolic control analysis dissects the control properties of metabolic systems in terms of the physical chains of interactions between enzymes and metabolic intermediates; and the thermodynamic/kinetic framework zooms in on the properties of the enzymes themselves to determine their regulatory roles. The strength of PySCeSToolbox lies in its integration of these viewpoints into a single analysis package in a way that promotes their complementary use in the search for a mechanistic explanation of modelled metabolic systems. Through the application of these tools in the investigation of two previously published metabolic models, new knowledge regarding their behaviour is uncovered and subsequently explained in terms of their component properties and interactions. In a model of aspartatederived amino-acid synthesis, a GSDA reveals that aspartate-semialdehyde regulates the reaction block that produces it via the reaction blocks that consume it, in spite of the relatively high sensitivity of its supply enzyme towards this intermediate. Subsequently, the regulatory contributions of each of the four aspartate-semialdehyde consuming blocks towards the producing block are quantified. In a model of pyruvate branch metabolism, application of GSDA shows that the flux through a NADH/NAD+ consuming reaction block decreases when the ratio of NADH to NAD+ increases. Rather than being a result of substrate inhibition, this phenomenon is shown to be the result of an interaction of the NADH/NAD+ intermediates with a reaction elsewhere in the pathway. Symbolic control analysis of the pyruvate branch model exposes a number of features that explain the unintuitive flux response described above. Firstly, only some control patterns are important for determining the flux control at any time. Secondly, different control patterns are 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 are responsible for the flux control. Additional use of the thermodynamic/kinetic framework to focus on the enzymes that constitute the control patterns relates their values to the properties of individual enzyme-catalysed reactions (i.e. their elasticities). This framework is also used to explain the behaviour of the elasticity coefficient components of the unintuitive flux response, which are shown to be mostly mass-action controlled. Ultimately this two-pronged strategy provides a mechanistic explanation of the flux response, in which this high-level property is quantitatively linked to various low-level components. The design of PySCeSToolbox as a Python-based software library allows it to integrate with the existing scientific Python ecosystem, thus providing access to a variety of additional third-party software tools to aid in the analysis of metabolic systems. This design also encourages the use of a scripting approach to designing in silico modelling experiments, which in turn promotes reproducibility through the re-use of such scripts. Moreover, PySCeSToolbox provides computational access to theoretical analysis frameworks that would otherwise have been inaccessible to researchers, as these frameworks are not implemented elsewhere.