Proctor2010 - UCHL1 Protein Aggregation

Model Identifier
BIOMD0000000293
Short description

This a model from the article:
Modelling the Role of UCH-L1 on Protein Aggregation in Age-Related Neurodegeneration.
Proctor CJ, Tangeman PJ, Ardley HC. PLoS One. 2010 Oct 6;5(10):e13175 20949132 ,
Abstract:
Overexpression of the de-ubiquitinating enzyme UCH-L1 leads to inclusion formation in response to proteasome impairment. These inclusions contain components of the ubiquitin-proteasome system and α-synuclein confirming that the ubiquitin-proteasome system plays an important role in protein aggregation. The processes involved are very complex and so we have chosen to take a systems biology approach to examine the system whereby we combine mathematical modelling with experiments in an iterative process. The experiments show that cells are very heterogeneous with respect to inclusion formation and so we use stochastic simulation. The model shows that the variability is partly due to stochastic effects but also depends on protein expression levels of UCH-L1 within cells. The model also indicates that the aggregation process can start even before any proteasome inhibition is present, but that proteasome inhibition greatly accelerates aggregation progression. This leads to less efficient protein degradation and hence more aggregation suggesting that there is a vicious cycle. However, proteasome inhibition may not necessarily be the initiating event. Our combined modelling and experimental approach show that stochastic effects play an important role in the aggregation process and could explain the variability in the age of disease onset. Furthermore, our model provides a valuable tool, as it can be easily modified and extended to incorporate new experimental data, test hypotheses and make testable predictions.


To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.


To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Format
SBML (L2V4)
Related Publication
  • Modelling the role of UCH-L1 on protein aggregation in age-related neurodegeneration. Click here to expand
  • Carole J Proctor, Paul J Tangeman, Helen C Ardley
  • PloS one , 10/ 2010 , Volume 5 , Issue 10 , pages: e13175 , PubMed ID: 20949132
  • Center for Integrated Systems Biology of Ageing and Nutrition, Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne, United Kingdom. c.j.proctor@ncl.ac.uk
  • Overexpression of the de-ubiquitinating enzyme UCH-L1 leads to inclusion formation in response to proteasome impairment. These inclusions contain components of the ubiquitin-proteasome system and α-synuclein confirming that the ubiquitin-proteasome system plays an important role in protein aggregation. The processes involved are very complex and so we have chosen to take a systems biology approach to examine the system whereby we combine mathematical modelling with experiments in an iterative process. The experiments show that cells are very heterogeneous with respect to inclusion formation and so we use stochastic simulation. The model shows that the variability is partly due to stochastic effects but also depends on protein expression levels of UCH-L1 within cells. The model also indicates that the aggregation process can start even before any proteasome inhibition is present, but that proteasome inhibition greatly accelerates aggregation progression. This leads to less efficient protein degradation and hence more aggregation suggesting that there is a vicious cycle. However, proteasome inhibition may not necessarily be the initiating event. Our combined modelling and experimental approach show that stochastic effects play an important role in the aggregation process and could explain the variability in the age of disease onset. Furthermore, our model provides a valuable tool, as it can be easily modified and extended to incorporate new experimental data, test hypotheses and make testable predictions.
Contributors
Submitter of the first revision: Carole Proctor
Submitter of this revision: Lucian Smith
Curator: Lucian Smith

Metadata information

is (2 statements)
BioModels Database BIOMD0000000293
BioModels Database MODEL0912070000

isDerivedFrom (1 statement)
BioModels Database BIOMD0000000105

isDescribedBy (1 statement)
PubMed 20949132

hasTaxon (1 statement)
Taxonomy Homo sapiens

isVersionOf (3 statements)
isPartOf (1 statement)
KEGG Pathway Parkinson's disease

hasVersion (1 statement)
Human Disease Ontology neurodegenerative disease

hasProperty (2 statements)
Human Disease Ontology Parkinson's disease
Mathematical Modelling Ontology Ordinary differential equation model


Curation status
Curated


Connected external resources