the biology of ageing e-science integration and simulation system tom kirkwood, darren wilkinson,...
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The Biology of Ageing e-Science Integration and
Simulation System
Tom Kirkwood, Darren Wilkinson,
Richard Boys, Colin Gillespie,
Carole Proctor, Daryl Shanley
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GRID-based research node to model/simulate hypotheses about mechanisms of ageing
Accessible and interactive
Nature Reviews Molecular Cell Biology 2003;4: 243 -249
www.basis.ncl.ac.uk
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DNA
RNA
PROTEIN
Degradation oraggregation (e.g.amyloid)
Antioxidants
Modelling the ageing processCopying errors,Telomere shortening
Mutationse.g. ROS
Transcription errors
Translation errors
Damage,denaturinge.g. ROS
Chaperones
Refolding
mtDNA
ATP
ROS
ROS
ATP
ROS, etc
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Virtual Ageing Cell• Telomere loss and oxidative stress: Proctor & Kirkwood Mech
Ageing Dev 2001.• Mitochondrial mutation: Kowald & Kirkwood J Theor Biol 2000.• Somatic mutation: Kirkwood & Proctor Mech Ageing Dev 2003.• Telomere capping: Proctor & Kirkwood Aging Cell 2003• Extrachromosomal DNA circles: Gillespie et al J Theor Biol
2004 • Genetic pathways: eg Sir2 gene action (in progress)• Protein turnover: Chaperones, ubiquitin-proteasome system
(Proctor et al. Mech Ageing Dev 2004 and in progress)• Antioxidant system: Shanley et al (in progress)• Network models:
• Mitochondrial mutation, oxidative stress, protein turnover (Kowald & Kirkwood Mutation Res 1996)
• Somatic mutation, telomere loss, mitochondrial mutation (oxidative stress (Sozou & Kirkwood JTheor Biol 2001)
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A module of the virtual ageing cell: the action of chaperones
and their role in ageing
Proctor et al. 2004 Mechanisms in Ageing and Development
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Cellular functions of chaperones
• Folding of nascent proteins• Assist in assembly of protein structures• Refolding of denatured proteins• Transport of proteins through cellular
membranes• Targeting of proteins for degradation• Prevention of protein aggregation
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Protein model for quality control
Wickner et al. (1999) Science 286 1888-1893
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Hsp90 Model of Regulation of HSF1
Zou et al. (1998) Cell 94:471-480
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Steps in building and using a model
1. Draw a diagram of the system.2. Give values to the boxes representing
the number of molecules and to the arrows representing the reaction rates.
3. Use a software tool to translate the diagram into computer code.
4. Use the simulator to discover the dynamic behaviour of the system.
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Building a model of the chaperone system
(i) The role of chaperones in preventing protein aggregation
refoldingbinding
aggregation
degradation
synthesis + folding into native state MisP
Hsp90
AggPNatP
ROS
ADP
ATP MisPHsp90
Abbreviations:NatP native proteinMisP misfolded proteinAggP aggregated proteinROS reactive oxygen species
misfolding
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(ii) Autoregulation of Hsp90
Abbreviations:Hsf1 heat shock factor-1DIH dimer of Hsf1TriH trimer of Hsf1HSE heat shock element
Hsp90
Hsf1
Hsp90
Hsf1binding
degradation
dimerisation
synthesis
TriHDiH trimerisation
HSEHSE
TriH DNA binding
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Model is coded in SBML<sbml xmlns="http://www.sbml.org/sbml/level2" version="1" level="2" ><model id="Hsp90model1" ><listOfCompartments><compartment id="cell" spatialDimensions="3" size=”1” name="cell" /></listOfCompartments><listOfSpecies><species id="NatP" compartment="cell" initialAmount="6000000.0" name=“NatP" /><species id=“Hsp90" compartment="cell" initialAmount=“30000.0" name=" Hsp90 " />
.</listOfSpecies><listOfParameters><parameter id="k1" value="7.04E-8" name=“k1" />
.</listOfParameters><listOfReactions><reaction id="protein_misfolding" reversible="false" ><listOfReactants><speciesReference species=“NatP" ></speciesReference></listOfReactants><listOfProducts><speciesReference species=“MisP" ></speciesReference></listOfProducts>
.</reaction>
.</listOfReactions></model></sbml>
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Stochastic simulation
refoldingbinding
aggregation
degradation
synthesis + folding into native state MisP
Hsp90
AggPNatP
ROS
ADP
ATP MisPHsp90
Abbreviations:NatP native proteinMisP misfolded proteinAggP aggregated proteinROS reactive oxygen species
misfolding
• Reactions are picked at random according to their rates.
• After each reaction, the number of each species is updated.
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Adding further detail to the model
degraded protein
Ub
Ub
Ub
Ub MisP
Ub
Ub Ub
Ub
ATP ADP
Proteasome
MisP
Ub
Ub
Ub
Ub
Ub = ubiquitin
ATP ADP
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Combining models in the BASIS system
• Other components will include models of: the mitochondria; the antioxidant system; damage to nuclear DNA; telomere shortening; and signalling pathways.
• Combining the mitochondria and chaperone model via ROS and ATP
Mitochondriamodel
Chaperonemodel
ROS
ATP
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BASIS: architecture
User PC
Internet (GRID)
BASISfile
servere-mail
notification
Web server
CGI scripts
Web browser
BASIS client software
Linux beowulf cluster
Web services
API
Database JobSchedul
er
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BASIS: architecture
• Web server is running apache• Condor as a job scheduler• python as an all purpose glue• SBML is parsed and manipulated using
libSBML for C & python• postgresql for the database• graphviz for the visualisation of the SBML
models
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BASIS: model repository
• Users have a private space for their models/simulations
• Once a model is made public it cannot be deleted– useful for the publication of models
• Models can be accessed through a web-service interface– other tools can access the models
• Models are referenced using urn’s, e.g. urn:basis.ncl:model:10
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Example web-services#To put a model into your space
putModel(SId, sbml)
#Using libSBML & graphviz
visualiseSBMLReaction(sbml, #reaction)
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What’s new?
• More interaction with biologists– especially PhD students
• Virtual ageing cell– more computer resources needed – Grid
• Web services– import models from other databases
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BASIS TeamTom Kirkwood Darren Wilkinson Richard BoysColin Gillespie Carole Proctor Daryl Shanley
Collaborators at NewcastleThomas von Zglinicki David LydallGabriele SaretzkiTim Cowen (IAH/UCL)Doug TurnbullChris MorrisJohn MathersNeil Wipat
NE E-Science CentrePaul WatsonRob Smith
UnileverJanette JonesJonathan PowellFrans van der OuderaaBerlin (MPI Inst. Mol. Genet.)Axel KowaldUniversity of BolognaClaudio Franceschi Silvana Valensin Paolo TieriINSERM ParisFrancois TaddeiTufts University/USDAJose OrdovasUniversity of LiverpoolBrian MerryUniversity of SemmelweisCsaba SotiOttawa Regional Cancer CentreDoug Gray
Acknowledgements