Yuraszeck2010 - Vulnerabilities in the Tau Network in Tau Pathophysiology

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Yuraszeck2010 - Vulnerabilities in the Tau Network in Tau Pathophysiology

This model is described in the article:

Vulnerabilities in the tau network and the role of ultrasensitive points in tau pathophysiology.
Yuraszeck TM, Neveu P, Rodriguez-Fernandez M, Robinson A, Kosik KS, Doyle FJ 3rd.
PLoS Comput. Biol. 2010; 6(11): e1000997

Abstract:

The multifactorial nature of disease motivates the use of systems-level analyses to understand their pathology. We used a systems biology approach to study tau aggregation, one of the hallmark features of Alzheimer's disease. A mathematical model was constructed to capture the current state of knowledge concerning tau's behavior and interactions in cells. The model was implemented in silico in the form of ordinary differential equations. The identifiability of the model was assessed and parameters were estimated to generate two cellular states: a population of solutions that corresponds to normal tau homeostasis and a population of solutions that displays aggregation-prone behavior. The model of normal tau homeostasis was robust to perturbations, and disturbances in multiple processes were required to achieve an aggregation-prone state. The aggregation-prone state was ultrasensitive to perturbations in diverse subsets of networks. Tau aggregation requires that multiple cellular parameters are set coordinately to a set of values that drive pathological assembly of tau. This model provides a foundation on which to build and increase our understanding of the series of events that lead to tau aggregation and may ultimately be used to identify critical intervention points that can direct the cell away from tau aggregation to aid in the treatment of tau-mediated (or related) aggregation diseases including Alzheimer's.

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Format
SBML (L2V4)
Related Publication
  • Vulnerabilities in the tau network and the role of ultrasensitive points in tau pathophysiology.
  • Yuraszeck TM, Neveu P, Rodriguez-Fernandez M, Robinson A, Kosik KS, Doyle FJ 3rd
  • PLoS computational biology , 11/ 2010 , Volume 6 , pages: e1000997
  • Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, California, USA.
  • The multifactorial nature of disease motivates the use of systems-level analyses to understand their pathology. We used a systems biology approach to study tau aggregation, one of the hallmark features of Alzheimer's disease. A mathematical model was constructed to capture the current state of knowledge concerning tau's behavior and interactions in cells. The model was implemented in silico in the form of ordinary differential equations. The identifiability of the model was assessed and parameters were estimated to generate two cellular states: a population of solutions that corresponds to normal tau homeostasis and a population of solutions that displays aggregation-prone behavior. The model of normal tau homeostasis was robust to perturbations, and disturbances in multiple processes were required to achieve an aggregation-prone state. The aggregation-prone state was ultrasensitive to perturbations in diverse subsets of networks. Tau aggregation requires that multiple cellular parameters are set coordinately to a set of values that drive pathological assembly of tau. This model provides a foundation on which to build and increase our understanding of the series of events that lead to tau aggregation and may ultimately be used to identify critical intervention points that can direct the cell away from tau aggregation to aid in the treatment of tau-mediated (or related) aggregation diseases including Alzheimer's.
Contributors
Audald Lloret i Villas

Metadata information

is
BioModels Database MODEL1408150000
BioModels Database BIOMD0000000542
isDescribedBy
PubMed 21085645
hasTaxon
Taxonomy Homo sapiens
isVersionOf
Gene Ontology inclusion body assembly
hasProperty
Human Disease Ontology Alzheimer's disease
Human Disease Ontology tauopathy
Curation status
Curated
  • Model originally submitted by : Audald Lloret i Villas
  • Submitted: Aug 15, 2014 10:58:21 AM
  • Last Modified: Sep 23, 2014 7:41:53 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Sep 23, 2014 7:41:53 PM
    • Submitted by: Audald Lloret i Villas
    • With comment: Current version of Yuraszeck2010 - Vulnerabilities in the Tau Network in Tau Pathophysiology
  • Version: 1 public model Download this version
    • Submitted on: Aug 15, 2014 10:58:21 AM
    • Submitted by: Audald Lloret i Villas
    • With comment: Original import of Yuraszeck2010 - Vulnerabilities in the Tau Network in Tau Pathophysiology
Curator's comment:
(added: 15 Aug 2014, 12:18:53, updated: 15 Aug 2014, 12:18:53)
Aggregation-prone simulation from Figure 6 has been reproduced here. Percent change in microtubule bound 4R tau protein with respect to basal concentration during 5000 arbitrary units. Parameters are took from “Run1” of “Disease Params” sheet, on Dataset S1. To run this plot, the specie “Tau04MT” from Table S1 using the reactions from Table S2 is divided by the specie “Tau04MT” from Table S1 using the reactions from Table S2 including a 5-fold increase in the parameter associated with the binding of normally phosphorylated tau 3R to microtubules (reaction 12). The simulation was done using Copasi v4.12 (Build 81) and the plots were generated using Gnuplot. The models with simulation settings can be downloaded from the below links: - Copasi file of “Tau04MT” basal concentration - Copasi file of “Tau04MT” concentration when 5-fold increase in reaction 12 is implemented