Computational model of sphingolipids metabolism: a case study of Alzheimer's disease

TL;DR

This paper presents the first comprehensive computational model of human sphingolipid metabolism, explicitly incorporating cellular compartmentalization, and demonstrates its application to understanding molecular mechanisms in Alzheimer's disease.

Contribution

The study introduces a novel, detailed computational model of sphingolipid metabolism that includes organelle-specific processes, advancing previous models limited to specific pathways.

Findings

Model validated using advanced analysis techniques

Identified key parameters influencing model behavior

Applied model to study Alzheimer's disease mechanisms

Abstract

Background: Sphingolipids - as suggested by the prefix in their name - are mysterious molecules, which play surprisingly various roles in opposable cellular processes, like autophagy, apoptosis, proliferation and differentiation. Recently they have been also recognized as important messengers in cellular signalling pathways. More importantly, sphingolipid metabolism disorders were observed in various pathological conditions such as cancer and neurodegeneration. Results: Existing formal models of sphingolipids metabolism concentrates mostly on de novo ceramide synthesis or restrict their focus to biochemical transformations of a particular subspecies. We propose first comprehensive computational model of sphingolipid metabolism in human tissue. In contrast to previous approaches we explicitly model compartmentalization what allows emphasizing the differences among individual organelles. Conclusions: Presented here model was validated by means of recently proposed model analysis technics allowing for detection of most sensitive and experimentally non-identifiable parameters and determination of main sources of model variance. Moreover, we demonstrate the utility of the model for the study of molecular processes underlying Alzheimer's disease.