Institute of Fundamental Technological Research

Bioenergetic failure, oxidative stress, and changes in mitochondrial morphology are common pathologic hallmarks of amyotrophic lateral sclerosis (ALS) in several cellular and animal models. Disturbed mitochondrial physiology has serious consequences for proper functioning of the cell, leading to the chronic mitochondrial stress. Mitochondria, being in the center of cellular metabolism, play a pivotal role in adaptation to stress conditions. We found that mitochondrial dysfunction and adaptation processes differ in primary fibroblasts derived from patients diagnosed with either sporadic or familial forms of ALS. The evaluation of mitochondrial parameters such as the mitochondrial membrane potential, the oxygen consumption rate, the activity and levels of respiratory chain complexes, and the levels of ATP, reactive oxygen species, and Ca2+ show that the bioenergetic properties of mitochondria are different in sporadic ALS, familial ALS, and control groups. Comparative statistical analysis of the data set (with use of principal component analysis and support vector machine) identifies and distinguishes 3 separate groups despite the small number of investigated cell lines and high variability in measured parameters. These findings could be a first step in development of a new tool for predicting sporadic and familial forms of ALS and could contribute to knowledge of its pathophysiology.

amyotrophic lateral sclerosis, neurodegeneration, primary fibroblasts, PCA

Background
As suggested by the origin of the word, sphingolipids are mysterious molecules with various roles in antagonistic cellular processes such as autophagy, apoptosis, proliferation and differentiation. Moreover, sphingolipids have recently been recognized as important messengers in cellular signaling pathways. Notably, sphingolipid metabolism disorders have been observed in various pathological conditions such as cancer and neurodegeneration.

Results
The existing formal models of sphingolipid metabolism focus mainly on de novo ceramide synthesis or are limited to biochemical transformations of particular subspecies. Here, we propose the first comprehensive computational model of sphingolipid metabolism in human tissue. Contrary to the previous approaches, we use a model that reflects cell compartmentalization thereby highlighting the differences among individual organelles.

Conclusions
The model that we present here was validated using recently proposed methods of model analysis, allowing to detect the most sensitive and experimentally non-identifiable parameters and determine the main sources of model variance. Moreover, we demonstrate the usefulness of our model in the study of molecular processes underlying Alzheimer’s disease, which are associated with sphingolipid metabolism.

Sphingolipid metabolism, Kinetic model, Sensitivity analysis

Motivation: Stochasticity is an indispensable aspect of biochemical processes at the cellular level. Studies on how the noise enters and propagates in biochemical systems provided us with non-trivial insights into the origins of stochasticity, in total, however, they constitute a patchwork of different theoretical analyses.

Results: Here we present a flexible and widely applicable noise decomposition tool that allows us to calculate contributions of individual reactions to the total variability of a system’s output. With the package it is, therefore, possible to quantify how the noise enters and propagates in biochemical systems. We also demonstrate and exemplify using the JAK-STAT signalling pathway that the noise contributions resulting from individual reactions can be inferred from data experimental data along with Bayesian parameter inference. The method is based on the linear noise approximation, which is assumed to provide a reasonable representation of analyzed systems.