SLIDE 1 Cell seeding of tissue engineering scaffolds studied by Monte Carlo simulations
Andreea-Paula ROBU*
Adrian NEAGU**
Lăcrămioara STOICU-TIVADAR*
* “Politehnica” University Timisoara ** University of Medicine and Pharmacy “Victor Babes” Timisoara
SLIDE 2 Contents
- Tissue Engineering
- The Differential Adhesion Hypothesis
- A computational model of a multi-cellular
system
- The simulation algorithm
- Cell seeding simulations of a porous scaffold
- Identification of energetic and geometric
conditions for optimal cell seeding
SLIDE 3 Tissue Engineering
- A new field of biomedical research
- Aims to create therapeutic constructs in vitro that can be
implanted in the human body
SLIDE 4
- Culturing living cells on a porous scaffold
- The scaffold gradually disappears, while the cells continue
to develop
Methods of tissue engineering
SLIDE 5 Cell rearrangements described by DAH
Steinberg’s differential adhesion hypothesis (DAH) states that:
- Cells move to form the largest number of strong connections
with their neighbors Cells tend to reach the minimum energy configuration
- Cells use their motility to achieve the desired configuration
SLIDE 6 The macromolecules involved in the processes of tissue
rearrangement are:
- cadherins - intercellular adhesion molecules
- integrins - substrate adhesion molecules
- The cohesion forces that act at cell interaction, respectively
the adhesion forces that act at the interaction between cells and substrate are transmitted through these molecules.
Molecular basis of cell adhesivity
SLIDE 7 Goals
- Build a computational model of tissue constructs
- Study cell seeding of porous scaffolds
- Identify the optimal conditions that lead to an uniform and
rapid distribution of cells in the scaffold
SLIDE 8 Computational model
- System: cell suspension located near a porous scaffold,
bathed in culture medium
- The 3D computational model is built on a cubic lattice:
each site of the lattice is occupied by either a cell or medium or biomaterial
- The porosity of the scaffold is achieved in the model by
taking into account the radius of the pores as well as the radius of the circular orifices that connect the pores
SLIDE 9
Model visualization
SLIDE 10 Computational algorithm Metropolis Monte Carlo
- An elementary move = swap of a cell with a volume
element of cell culture medium from its vicinity
- A move is accepted with a probability :
- A Monte Carlo step (MCS) is represented by the sequence
- f operations in which each cell is given the chance to make
a move
( )
min 1,exp( / )
T
P E E = −Δ
SLIDE 11 Energy of adhesion
cc cm ε γ 2 1 =
cm cm B cs cs B E γ γ * * + =
cs cc cs
ε ε γ − = 2
1
- The cell-substrate interfacial tension parameter:
- The cell-medium interfacial tension parameter:
SLIDE 12
- Input parameters:
- cohesion energy between cells
- adhesion energy between cells and scaffold
- radius of pores
- radius of circular orifices that connect the pores
- Output parameters:
- centre of mass of all cells
- centre of mass of seeded cells
- concentration of the cells remained in suspension
Input and output parameters
SLIDE 13 Simulation parameters
Values of input and output parameters in representative simulations
cs T
E ε
CM
z
SLIDE 14
The centre of mass of all cells The centre of mass of seeded cells - Simulation I
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SLIDE 15
The fraction of the cells outside the scaffold - Simulation I
SLIDE 16 Simulation I
Configuration after 80 000 MCS εcc=0, εcs=0.6, R=5, r=2 If the cells do not adhere to
each other, but they adhere to the scaffold, the seeding is rapid and cell distribution in the scaffold is uniform
SLIDE 17
The centre of mass of all cells The centre of mass of seeded cells - Simulation II
SLIDE 18
The fraction of the cells outside the scaffold - Simulation II
SLIDE 19 Simulation II
Configuration after 80 000 MCS εcc=0.8, εcs=0.6, R=5, r=2
- If the cell-cell interaction
energy is nonzero, but small enough to ensure a negative cell-scaffold interfacial tension, uniform distribution is reached, but the process is slower
- For a cell-cell interaction
energy of 0.8, cell aggregates emerge and the penetration of cells into the scaffold is slower
SLIDE 20
The centre of mass of all cells The centre of mass of seeded cells - Simulation III
SLIDE 21
The fraction of the cells outside the scaffold - Simulation III
SLIDE 22 Simulation III
Configuration after 80 000 MCS εcc=1, εcs=0.25, R=5, r=2
Seeding is severely hampered if the cell-cell interaction energy is larger than twice the cell- substrate interaction energy, making the cell- scaffold interfacial tension positive
SLIDE 23 Simulation IV
Configuration after 80 000 MCS εcc=0, εcs=0.6, R=8, r=5
If the orifices that connect the pores are large (exceeding half of the pore’s diameter), the scaffold is not contiguous and does not offer enough biomaterial to be attached to.
SLIDE 24 Conclusions
- We developed a computational model of a
cell suspension located on the surface of a porous scaffold
- Using the Metropolis Monte Carlo method,
we simulated the cell seeding process for different values of the cell-cell, and cell- scaffold interaction energy, and for different geometries of the scaffold
SLIDE 25 Conclusions
- Our simulations show clearly that the emergent
configuration is a result of a tug-of-war between cell-cell and cell-substrate interaction
- This study enables the optimisation of the cell
seeding
- Simulations of cell seeding are useful for testing
different experimental conditions, which in practice would be very expensive and hard to perform
SLIDE 26
Future Developments
cell proliferation
Model cell death process
scaffold degradation
SLIDE 27
Thank you for your attention! Takk for oppmerksomheten!
andreea.robu@aut.upt.ro
