Post on 15-Jan-2016
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Universityof Sheffield
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Modelling Tissue Development
Rod Smallwood, Mike Holcombe, Sheila Mac Neil, Rod Hose, Richard Clayton (University of Sheffield), Jenny Southgate (University of York)
Universityof Sheffield
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The social behaviour of cells
How do these individual cells …
… assemble into this complex tissue?
Universityof Sheffield
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Building an integrative systems biology: the Human Physiome Project
• The aim of the Human Physiome Project is to provide a “quantitative description of physiological dynamics and functional behaviour of the intact organism”
• it is overseen by the Physiome and Bioengineering Committee of the IUPS (International Union of Physiological Sciences)
• projects include the Cardiome (heart), the Endotheliome (lining of blood vessels), Micro-circulation …
• … and the Epitheliome – computational modelling of the social behaviour of (epithelial) cells
Universityof Sheffield
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Where does cell modelling fit into the Physiome Project?
Hunter P, Robbins P, Noble D (2002) The IUPS human physiome project. Eur J Physiol 445 1-9
Social modelof cell
Cellular tissue10-5m
TheEpitheliome
Universityof Sheffield
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The social life of the cell is important!
• Essential step from single-cell to multi-cellular organisms
• Tissues and organs are self-assembling systems
• No organising principle above the level of a single cell
– so order is an emergent property of cellular interaction
• This is a salient feature of biological systems - order emerges as the result of the interaction of large numbers of complex entities
Courtesy of Sheila Mac Neil, Sheffield
Universityof Sheffield
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What are the drivers?
Screening for epithelial cancers
Contraction of skin grafts
Wound healing
Courtesy of Dawn Walker & Sheila Mac Neil, Sheffield
Universityof Sheffield
www.dcs.shef.ac.uk/~rod/
What are the common features?
• Self assembly/disassembly
• Forces between cells
• Cell motility
• Cell signalling as a result of mechanical forces
• Only an empirical understanding of the processes
– e.g. differentiation at an air-liquid interface
Courtesy of Sheila Mac Neil, Sheffield
Universityof Sheffield
www.dcs.shef.ac.uk/~rod/
From ants to epithelium• Existing models of tissue are either descriptive or derive function from structure
– need a predictive model, not a descriptive model– in advance of healing, there is no structure in a wound, so need to develop
structure from function• What paradigm can we use to model self-assembly of large numbers of very
complex entities?• The basic idea came from work
on the social behaviour of ants– we are interested in the socialbehaviour of cells
• Two key insights were essential– a mechanism for integrating
cellular biology into the‘social model’
– linking the ‘social model’ to aphysical model of the tissuebehaviour
Courtesy of Francis Ratnieks, Sheffield
Universityof Sheffield
www.dcs.shef.ac.uk/~rod/
Simulation of monolayer growth
NO
. CE
LL
S
ITERATION NUMBER
Physiological Ca2+ (2 mM)
Low Ca2+ (0.09 mM)
STEM CELL
TRANSIT AMPLIFYING CELL
MITOTIC CELL
QUIESCENT CELL
STEM CELL
TRANSIT AMPLIFYING CELL
MITOTIC CELL
QUIESCENT CELL
Ca2+ = 2mM Ca2+ = 0.09mM
Universityof Sheffield
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in silico wound healing
Physiological Ca2+ (2mM) Low Ca2+ (0.09mM)
Universityof Sheffield
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in vitro wound healing
Low Ca2+Physiological Ca2+
(Cell movie from Gemma Hill, Jack Birch Unit for Molecular Carcinogenesis, University of York)
Universityof Sheffield
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Major challenges
• Developing a ‘realistic’ physical model that is computationally tractable for ~106 cells
• Deciding what is important - sparseness (parsimony)
• Linking individual cell dynamics to a continuum model of tissue
– how does stress at the tissue level affectmechano-transduction at the cytoskeletallevel
– how is the signalling resulting from a woundrelated to cellular-level response
• Comparing tissue growth in vitro and in silico
– how do we validate the computational model
Balaban et al 2001 Nature Cell Biology 3 466
Universityof Sheffield
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Summary
• We have developed a proof-of-concept model of the social behaviour of cells
• The model shows similar behaviour to urothelial cells grown in vitro
• In principle, the model:– can incorporate the biological mechanisms which control
cell behaviour– can be scaled up to realistic numbers of cells
• In practice, sparseness will be essential!• The model is changing biologists’ thinking and driving
biological experiments• Strong validation is essential
Universityof Sheffield
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Acknowledgements
Cell biology: Jenny Southgate (York) Sheila Mac Neil Eva Qwarnstrom
Modelling: Mike Holcombe Dawn Walker Steven Wood
Engineering: Rod Hose Peter Hunter (Auckland)
Funding: Engineering & Physical Sciences Research Council (EPSRC) Higher Education Funding Council for England (HEFCE)
Universityof Sheffield
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