systems modelling of emt cell signalling pathways in heart valve development

Systems Modelling of EMT Cell Signalling Pathways in Heart Valve

DevelopmentTariq Abdulla1, Ryan Imms1, Jean-Marc Schleich2 and Ron Summers1

VPH 201001/10/2010

1Dept. Electronic and Electrical Engineering, SEIC, Loughborough University, LEICS, UK, LE11 3TUE-mail: T.Abdulla@lboro.ac.uk Web: http://www-staff.lboro.ac.uk/~elta22LTSI, University of Rennes 1, Rennes, F-35000, France

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“Epithelial to Mesenchymal Transition”

Outline

Heart Development – what happens? Heart Looping Neural Crest Cell Migration Endocardial Cushion Growth Congenital Heart Defects

Systems Modelling - how do we do it? Conceptual Model Network Modelling Tissue Modelling Integration

Conclusion and Future Work

Heart Development: what happens?

Rear View

Membranous Septum

Muscular Septum

Neural Crest Cell Migration

Endocardial Cushion Growth

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Systems Modelling – how do we do it?

Different types of computational model are suitable for different levels of biological scale

E.g. Biochemical reactions can be represented as networks or ODEs. Cellular behaviour can be modelled with agent based models.

Use models at one level of scale, to pass information to models at another level of scale

Conceptual Modeling

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Network Modelling

KEGG

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Notch Signalling

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Notch Signalling

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Tissue Modelling Tissues are often modelled as though they

are continuous But many of the interesting things that

happen in tissues are to do with individual cell behaviour, and social behaviour (structure)

When there is an abnormality at tissue level we may need to know whether this is hypotrophic (fewer cells) or hypoplastic (smaller cells)

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Tissue Modelling A lot of the movement of cells around each

other, and how they interact, can be explained by their relative adhesiveness to other cells

This is the Differential Adhesion Hypothesis

Compucell3D

Compucell3D

Integration

We take a proactive approach in model annotation, and are even developing methods for multiscale annotation

This includes combining terms from multiple reference ontologies in post-composition

Use of common formats such as SBML

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Molecules

Cells

Tissues

Organs

?PMR2

Ontologies

Conclusion and Future Work

Modelling systems of such complexity is difficult, but it’s essential if we are to understand them

Comparison with in vivo or in vitro data is essential for model validation and improvement

This project has the potential to be applied to tissue engineering

Questions or suggestions?

Thanks to (in no order):

Ron Summers Ryan Imms Jean-Marc Schleich Fanny Bajolle Lucile Houyel