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Computational modeling of sphingolipid metabolism.

Wronowska W, Charzyńska A, Nienałtowski K, Gambin A - BMC Syst Biol (2015)

Bottom Line: Contrary to the previous approaches, we use a model that reflects cell compartmentalization thereby highlighting the differences among individual organelles.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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Computer Science Polish Academy of Sciences, Warsaw, Poland. wwro@biol.uw.edu.pl.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

The local sensitivity analysis of the CER species to the highly significant parameters
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Related In: Results  -  Collection

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Fig2: The local sensitivity analysis of the CER species to the highly significant parameters

Mentions: For the outcome of the local sensitivity analysis [30] performed for the system in stationary state homeostasis, see Fig. 2 and Additional file 1: Figures S1-S3. The following conclusions were drawn.


Computational modeling of sphingolipid metabolism.

Wronowska W, Charzyńska A, Nienałtowski K, Gambin A - BMC Syst Biol (2015)

The local sensitivity analysis of the CER species to the highly significant parameters
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4537549&req=5

Fig2: The local sensitivity analysis of the CER species to the highly significant parameters
Mentions: For the outcome of the local sensitivity analysis [30] performed for the system in stationary state homeostasis, see Fig. 2 and Additional file 1: Figures S1-S3. The following conclusions were drawn.

Bottom Line: Contrary to the previous approaches, we use a model that reflects cell compartmentalization thereby highlighting the differences among individual organelles.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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Computer Science Polish Academy of Sciences, Warsaw, Poland. wwro@biol.uw.edu.pl.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus