Integration of kinetic models with data from 13C-metabolic flux experiments
Date
2007-12
Authors
Journal Title
Journal ISSN
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Publisher
Stellenbosch : University of Stellenbosch
Abstract
A detailed mathematical description of all the processes in a cell could be an
informative tool for investigating biological function. Detailed kinetic models
could be built either by obtaining enzyme kinetic parameters in vitro, or
by obtaining them from time series analyses of metabolite data from rapid
pulse experiments. A genome scale in vitro enzyme kinetic assay project
would be prohibitively laborious with the current technologies. Further,
there are still uncertainties about the importance of in vivo effects such as
metabolite channelling, spatial effects and molecular crowding which could
make in vitro determined parameters invalid. Accordingly, there is much
interest in in vivo experiments for kinetic modelling. In vivo experimental
methods suffer from a number of technical and even fundamental problems.
Technical problems are being solved by more sensitive metabolomics tools
and rapid sampling technologies. However, the large number of effectors of
each enzyme reaction makes it impossible to obtain models at the level of detail
possible with the in vitro method. Ultimately, the solution to building a
genome scale Silicon Cell is to make use of both strategies. As metabolomics
technologies are rapidly improving, it would thus make sense to follow the
parts-based in vitro kinetics methodology, and carry out a detailed accuracy
assessment of the model with in vivo experiments. To address the problem
of the fundamental limit of information from concentration time-series, other
in vivo experiments will have to be carried out as well. 13C-metabolic flux
analysis has recently undergone vast improvements with the use of better experimental
protocols and powerful algorithms for flux calculation. Incorporation
of this type of experiment in the validation protocol is the aim of this thesis, which represents an intermediary step towards using the genome-scale
stoichiometric models as platforms for building genome-scale kinetic models.
It is illustrated here how kinetic models can be combined with metabolic
flux data in a special way which allows correct modelling of boundary conditions
and validation using novel concepts. We used 13C-metabolic flux
analysis and gas chromatography-mass-spectrometry to measure metabolic
fluxes through the central metabolic pathways of the yeast Saccharomyces
cerevisiae. This data was integrated with a previously constructed detailed
kinetic model of fermentative glycolysis in the yeast to illustrate our approach.
Various implications for such data integration with kinetic models
were identified and a software program was designed for this purpose.
Description
Thesis (MSc (Biochemistry))--University of Stellenbosch, 2007.
Keywords
Dissertations -- Biochemistry, Theses -- Biochemistry, Molecular biology -- Data processing