Kathleen Green, MSc

Friday 2 June, 14:30, AIMS Main Lecture Hall

Abstract: Hypoglycemia and lactic acidosis are indicators of poor chances of survival in malaria-infected humans. These concentration changes could be the result of accelerated glycolytic flux in red blood cells upon infection by P. falciparum. Currently, there are no mathematical models that are able to quantify the contribution of this increased flux to hypoglycemia and lactic acidosis. Since these diagnostics are defined at the whole-body level it would be beneficial to relate them to enzyme-catalysed reactions. This would facilitate the analyse of drug effects on an individual reaction step in the parasite at the whole body disease state. Therefore a hierarchical kinetic modelling approach is suggested with the lower levels of the system being represented by enzyme-catalysed reactions while the higher levels are represented by the whole-body effects. There are detailed kinetic models available of Plasmodium glycolysis, human erythrocyte glycolysis and phenomenological models of whole-body glucose metabolism but these models have never been linked. The aim of this project is to combine these models to determine if accelerated glycolytic flux in red blood cells is sufficient to explain hypoglycemia and lactic acidosis. Furthermore it could lead to the identification of possible drug targets.

About: Kathleen Green completed her undergraduate studies at Stellenbosch University in Biomathematics, after which she attended the African Institute for Mathematical Sciences (AIMS) for the joint Honors degree in Biomathematics (with Stellenbosch University). She has always been interested in biochemistry and therefore chose to join the Molecular Systems Biology research group at Stellenbosch University for a Masters degree. In her masters research, she merged existing models to better understand the contribution of increased parasite burden to hypoglycaemia and lactic acidosis in malaria patients. She is currently pursuing a PhD which builds on her Masters work by using reduction methods to simplify large models, still within a whole body modelling framework.