Browsing by Author "Green, Kathleen Alice"
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- ItemComputational and analytical methods for constructing a multilevel model for human glucose metabolism(Stellenbosch : Stellenbosch University, 2022-03) Green, Kathleen Alice; Snoep, Jacob Leendert; Van Niekerk, David Douglas ; Cang, Hui; Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences.ENGLISH ABSTRACT: Glucose metabolism is carefully regulated in humans to ensure that homeosta- sis is maintained. Disruptions in the multiple processes involved, or the inabil- ity to sustain adequate glucose concentrations, can cause various metabolic complications that can become life threatening. These complications can present as a result of diseases such as Type 2 diabetes (hyperglycaemia), or severe malaria (hypoglycaemia). In the context of malaria, two key metabolic indicators for poor chance of survival are hypoglycaemia (low plasma glu- cose concentrations) and lactic acidosis (high plasma lactate concentrations). Currently, it is understood that these conditions are the result of various clin- ical complications, and the extent to which the malaria parasite Plasmodium falciparum contributes to them is unknown. This contribution could be a consequence of the accelerated glycolytic flux, brought about by the parasite increasing the glucose demand and lactate production, once it has invaded the host’s red blood cells, a hypothesis that is tested in this thesis using a mathematical modelling approach. We used a new approach to building a whole body glucose metabolism model that is well-grounded in a large number of clinical studies following a thorough literature review to obtain clinical data on glucose metabolism. This model is parametrised using data from 49 different studies, and 74 figures that have been successfully reproduced between different softwares. The model construction is performed using a specialised package for model merging called Hierarchical Model Composition [1]. This model consists of several different organs that contribute to glucose metabolism in humans with a specific compartment that was incorporated to describe red blood cell metabolism. In addition to the reference model built for glucose metabolism in a healthy individual, we extend the model to represent malaria patients by explicitly modelling parasitaemia via the inclusion of a detailed mathematical model for Plasmodium falciparum into the red blood cell compartment. The multilevel model for malaria reveals that a 13% parasite burden leads to hypoglycaemia, but lactic acidosis as is observed in malaria patients, is not induced. Patient data and sensitivity analysis is used for initial model validations and identification of potential treatment targets in the parasite’s glycolytic pathway. The multilevel model is large (303 variables) which makes it difficult to anal- yse. Therefore we developed a flexible model reduction technique that can aid in the simplification of the multilevel model through selection of the relevant enzyme mechanisms, while retaining the whole body descriptions on the higher level. This reduction method applies a combination of structural and kinetic modification to the original model, and was tested on different modelling struc- tures and kinetics occurring in biochemical pathways. Thereafter, the method is extended to biological applications which show how multiple model simpli- fications for different inhibitor titration studies can be investigated starting from a single model description and performing various selections of reactions or species. During model merging we encountered logistical challenges such as unit con- version and the use of unique identifiers that are generic for merging different modules into a single model. Our solution was to use automated approaches as much as possible as developed in the Systems Biology community, and to code additional solutions for our automated workflow. This work highlights the benefits of utilising automated approaches, as well as combining differ- ent computational and analytical techniques from different disciplines, during model construction, validation and analysis. By making these models, all datasets, and simulation experiment descriptions available on JWS Online [2], FAIRDOMHub [3], and PK database [4], we envisage that future improve- ments and extensions can be implemented in a systematic way owing to the modular structure of the model, and the transparency and reproducibility of the construction process.