Team:Freiburg Bioware/Modeling/Virus Production
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Revision as of 19:28, 27 October 2010
Model for Virus Production
Reaction Scheme
Reducing the complexity of virus production we divide the cell into
three compartments: the extracellular matrix (all quantities
with the index ext), the cytoplasm (cyt) and the
nucleus (nuc). Four plasmids are transfected - the
plasmid coding for the helper proteins (helper), the gene
of interest (goi) and two types of plasmids coding for the capsid
proteins (capwt [wild type], capmod [modified]).
The plasmids are transported into the nucleus where gene expression is
initiated. Processed mRNA is transported into the cytoplasm and proteins
(phelper, pcapwt, pcapmod) are produced.
Containing a nuclear localization sequence proteins are relocated into
the nucleus where capsid assembly occurs. The viral capsid is compose
of 60 subunits of viral coat proteins. Titration of the two plasmids
coding for the capsid proteins leads to virus surfaces with different
ratios of wild type and modified capsid proteins.
The gene of interest is replicated by cellular polymerases and single
stranded DNA (ssDNA) is encapsidated into the preformed capsids
(capsid) forming infectious viral particles (V).
Finally the recombinant viruses are released into the extracellular
matrix and can be harvested for transduction.
Figure
1: Schematic overview of virus production: A production cell
line is transfected with 4 plasmid types. DNA is replicated,
transcribed (1) and proteins are synthesized (2). Capsid assembly
occurs (3) and single-stranded DNA is packaged into the viral particle
(4).
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Reduced Reaction Scheme
Even the coarse model for virus production described in the previous
paragraph would still consist of 24 ODEs containing 39 parameters (35
rate constants and 4 initial plasmid concentrations). Taking into
account the linearity of the law of mass action (LMA) for simple
transport processes we can neglect these fast reactions and for this
reason reduce the model to the rate limiting steps like protein
synthetization, capsid formation and virus packaging.
Differential Equations
The 13 reactions for the virus production are represented in a system
of 17 coupled ODEs.
In addition to the terms provided by the law of mass action we
considered the following terms:
- a linear degradation of ssDNA in the nucleus with the rate constant k14,1
- replication of ssDNA in the nucleus with the rate constant k15,1
Methods and Simulation
The ODE model was implemented in MathWorks® MATLAB R2010b. Integration
of the differential equations was achieved using the stiff integrator ode15s
with automatic integration step size management.
In order to adjust the dynamical model to biological data we extracted
the average intensity out of the time lapse recordings of fluorescence
experiments as well as published values for the rate constants. For
initial conditions we took the plasmid concentrations we used in
experiments.
Figure
4: A shows the average intensity of mCherry recorded using
fluorescence microscopy. The curve corresponds to the rising phase of
protein concentration and is expected to saturate for longer times as
the harvest of viral particles is done after 3 days (4320min). B: time course of the intensity of
mCherry. Due to the weak expression of mCherry the signal to noise
ratio is quiet low and the functional dependency is not clearly
determinable.
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The average intensity was extracted from the raw data through a script written in MathWorks® MATLAB. Download the m-File (MATLAB source code). |
The used model parameters are given in the table below.
Table 1: Rate constants for the virus production model. Generally foward reactions were assumed to be faster than reverse ones. Replication of ssDNA is slower than its degradation. |
Download the m-File (MATLAB source code).
Results and Discussion
Figure
5:
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Figure
6:
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Figure
7:
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Figure
9: Data fitting approach. The model can be fitted perfectely to
the data (not shown) but is not meaningfull in a biological sense
because exponential increase does not occur in this system. Considering
the fact that virus concentration should saturate a sigmoidal shape is
expected. Such a fit was not achieved because to many unknown
parameters for one single data set.
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