PS01 OTHE-06

A Mathematical Approach to Investigate the Protein Aggregation in Alexander Disease

Monday, July 14 from 6:00pm - 9:00pm in

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Lihini Kankanamge

Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada. Waisman Center, University of Wisconsin–Madison, Madison, Wisconsin, United States. Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina, United States
"A Mathematical Approach to Investigate the Protein Aggregation in Alexander Disease"
Intermediate filaments (IFs) are among the three major cytoskeletal protein families, primarily serving as stress absorbers within cells. This study focuses on Alexander disease (AxD), a neurodegenerative condition associated with the formation of protein aggregates, including cell-type-specific IF proteins such as Glial Fibrillary Acidic Protein (GFAP). Disruptions in GFAP organization within astrocytes, pivotal central nervous system (CNS) cells, are concomitant with the formation of Rosenthal Fibres (RF). In patients diagnosed with AxD, various point mutations in the gene encoding GFAP have been identified; however, their specific impact on GFAP organization in astrocytes remains poorly understood. In this study, mathematical models are constructed to investigate potential mechanisms driving GFAP protein aggregation. To gain a comprehensive understanding of the correlation between defects in GFAP assembly and AxD pathogenesis, these mathematical models are specifically designed to investigate RF formation. In modelling GFAP organization both in vitro and in vivo, GFAP material is categorized into five distinct pools: wild type (WT) and mutant (M) soluble pools, WT and M filamentous insoluble pools, and M aggregate pool. Transitions between these structural states are modelled using systems of ordinary differential equations (ODEs). This work centers on the effects of four mutation groups that lead to distinct patterns of protein aggregation, which were previously experimentally investigated. By analyzing ODE systems of WT and M protein polymerization, both in isolation and in interaction, this study explores the impact of each mutation group to identify key parameters driving aggregation mechanisms.


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