Team:Freiburg/Content/Results/Modeling

From 2014.igem.org

(Difference between revisions)
Line 18: Line 18:
</section>
</section>
 +
<!-- ===================================================MLV Model=================================================== -->
<section>
<section>
<h2 id="Results-Modeling-Model-MLV-Infection-Formulation">Model Formulation</h2>
<h2 id="Results-Modeling-Model-MLV-Infection-Formulation">Model Formulation</h2>
Line 48: Line 49:
<p>The diffusion of the virions follows the fick’s law of diffusion. u is the velocity of sedimentation due to gravity. Since the virions are instable at 37°C, they decay in the medium with a constant decay rate k<sub>d_vm</sub>. Thus an additional term was added to the partial differential equation (PDE).</p>
<p>The diffusion of the virions follows the fick’s law of diffusion. u is the velocity of sedimentation due to gravity. Since the virions are instable at 37°C, they decay in the medium with a constant decay rate k<sub>d_vm</sub>. Thus an additional term was added to the partial differential equation (PDE).</p>
-
<a href="https://static.igem.org/mediawiki/2014/6/62/Freiburg2014_Results_modeling_pde.jpg"> <!-- ORGINAL -->
+
 
<img src="https://static.igem.org/mediawiki/2014/6/62/Freiburg2014_Results_modeling_pde.jpg"> <!-- Thumbnail -->
<img src="https://static.igem.org/mediawiki/2014/6/62/Freiburg2014_Results_modeling_pde.jpg"> <!-- Thumbnail -->
 +
 +
 +
<p>The diffusion coefficient D<sub>v</sub> can be calculated according to the Stokes–Einstein equation, </p>
 +
 +
 +
<img src="https://static.igem.org/mediawiki/2014/9/96/Freiburg2014_Results_modeling_D_v.jpg"> <!-- Thumbnail -->
 +
 +
 +
<p>and u was estimated as the Stokes settling velocity.</p>
 +
 +
 +
<img src="https://static.igem.org/mediawiki/2014/1/1b/Freiburg2014_Results_modeling_u.jpg"> <!-- Thumbnail -->
 +
 +
 +
<p>To solve the PDE, boundary conditions are required at the top and the bottom of the medium. At the top (z=h), net flux of virions has to be zero, so that</p>
 +
 +
 +
<img src="https://static.igem.org/mediawiki/2014/6/68/Freiburg2014_Results_modeling_pdebc2.jpg"> <!-- Thumbnail -->
 +
 +
 +
<p>At the bottom (z=0), virions bind irreversibly onto the cell surface and are subsequently internalized. The binding rate is proportional to local virus concentration, cell density and density of mCAT1 receptor on the cell surface. Moreover, the binding is saturating at high receptor density, so a Michaelis-constant for receptor density was added to the equation. </p>
 +
 +
 +
<img src="https://static.igem.org/mediawiki/2014/0/0b/Freiburg2014_Results_modeling_pdebc1.jpg"> <!-- Thumbnail -->
 +
 +
 +
<p>Second, the MLV undergoes several steps (see Fig. 1 (3)-(7)) after the internalization to be integrated into the genome. However, it is difficult to determine the intracellular concentration of each viral component. The only output of our experiments was the transduction efficiency determined by flow cytometry. Thus it makes more sense to consider the dynamics between infected and non-infected cells.</p>
 +
 +
<p>According to the location of intracellular viral particles, the cells were divided into three populations (see Fig. 3): virus-free cells (C<sub>f</sub>), cells that carry MLV in the cytoplasm (C<sub>c</sub>) and cells with viral DNA integrated in the genome (C<sub>i</sub>). Similarly, intracellular viral particles were divided into cytoplasmic viruses (V<sub>c</sub>) and integrated viruses (V<sub>i</sub>). Particularly, a subpopulation of cytoplasmic virus inside the virus-carrying cells only (V<sub>f</sub>) was also considered to enable further calculations. </p>
 +
 +
 +
<figure>
 +
<a href="https://static.igem.org/mediawiki/2014/0/03/Freiburg2014_Results_modeling_population.jpg"> <!-- ORGINAL -->
 +
<img src="https://static.igem.org/mediawiki/2014/0/03/Freiburg2014_Results_modeling_population.jpg"> <!-- Thumbnail -->
</a>
</a>
 +
<figcaption>
 +
<p class="header"><b>Figure 3. </b> Cell and virus populations and their density.</p>
 +
</figcaption>
 +
        </figure>
 +
 +
<p>The dynamics between different cell and virus populations was influenced by several factors (see Fig. 4), including binding of new virions, intracellular degradation of viral particles wit rate k<sub>d_vc</sub>, integration of viral DNA with integration rate k<sub>in</sub>, and cell division with a constant growth rate μ. </p>
 +
 +
<figure>
 +
<a href="https://static.igem.org/mediawiki/2014/8/86/Freiburg2014_Results_modeling_virus_dynamics.jpg"> <!-- ORGINAL -->
 +
<img src="https://static.igem.org/mediawiki/2014/8/86/Freiburg2014_Results_modeling_virus_dynamics.jpg"> <!-- Thumbnail -->
 +
</a>
 +
<figcaption>
 +
<p class="header"><b>Figure 4. </b> Dynamics of cell and virus populations.</p>
 +
</figcaption>
 +
        </figure>
 +
 +
<p>Thus the differential equations were set up as follows. </p>
 +
 +
 +
 +
<img src="https://static.igem.org/mediawiki/2014/3/3c/Freiburg2014_Results_modeling_Cf.jpg"> <!-- Thumbnail -->
 +
 +
<img src="https://static.igem.org/mediawiki/2014/d/d7/Freiburg2014_Results_modeling_Cc.jpg"> <!-- Thumbnail -->
 +
 +
<img src="https://static.igem.org/mediawiki/2014/2/2c/Freiburg2014_Results_modeling_Ci.jpg"> <!-- Thumbnail -->
 +
 +
<img src="https://static.igem.org/mediawiki/2014/3/30/Freiburg2014_Results_modeling_Vf.jpg"> <!-- Thumbnail -->
 +
 +
<img src="https://static.igem.org/mediawiki/2014/6/6e/Freiburg2014_Results_modeling_Vc.jpg"> <!-- Thumbnail -->
 +
 +
<p>δ<sub>1</sub> is the possibility of a virus-carrying cell that becomes virus-free owing to the degradation of intracellular virus. Since multiple cytoplasmic viruses are unlikely to degrade at the same time, the possibility equals the fraction of virus-carrying cells with only one virus. Since the distribution of the multiplicities of infection (MOI) follows the poisson distribution, δ<sub>1</sub> can be calculated using the following equation, </p>
 +
 +
<img src="https://static.igem.org/mediawiki/2014/0/02/Freiburg2014_Results_modeling_delta1.jpg"> <!-- Thumbnail -->
 +
 +
<p>where n_v is the average number of virus per cell inside the virus-carrying cells.</p>
 +
 +
<img src="https://static.igem.org/mediawiki/2014/7/7a/Freiburg2014_Results_modeling_nv.jpg"> <!-- Thumbnail -->
 +
 +
<p>δ<sub>2</sub> is the possibility of a virus-carrying cell that becomes virus-free during cell division. Because virus particles enter two daughter cells in a random process, one of them may lose all particles and became virus-free again. δ<sub>2</sub> depends on the MOI of the cell. </p>
 +
 +
<p>Besides, terms for the integration are calculated at time τ prior to the current time point t. τ is the mean trafficking time of the virus inside the cytoplasm and includes time for reverse transcription and viral transport (see Fig. 1 (3)-(4)). These terms turn these differential equations into a delayed differential equation system (DDE), which was solved here by numerical methods using MATLAB. </p>
 +
 +
<p>The experimental output, the transduction efficiency, is defined as the fraction of virus-integrated cells. </p>
 +
 +
<img src="https://static.igem.org/mediawiki/2014/f/f1/Freiburg2014_Results_modeling_eff.jpg"> <!-- Thumbnail -->
</section>
</section>
 +
<!-- ===================================================MLV analysis=================================================== -->
<section>
<section>
<h2 id="Results-Modeling-Data-MLV-Infection-Analysis">Data Analysis</h2>
<h2 id="Results-Modeling-Data-MLV-Infection-Analysis">Data Analysis</h2>
 +
 +
<h3>Extracellular virus degradation</h3>
 +
 +
<p>The extracellular degradation rate of MLV (k<sub>d_vm</sub>) was first investigated. MLV suspension was incubated at 37 °C for different durations. The viral concentration should follow a single exponential decay function. </p>
 +
 +
<img src="https://static.igem.org/mediawiki/2014/1/1f/Freiburg2014_Results_modeling_exp_decay.jpg"> <!-- Thumbnail -->
 +
</section>
</section>

Revision as of 18:18, 16 October 2014

The AcCELLerator

Modeling

The AcCELLerator is based on the combination of two systems: the light-regulated gene expression and the retroviral gene delivery.

MLV Infection

Model Formulation

In our project, gene delivery was achieved by infecting the cells with recombinant murine leukemia virus (MLV). As a typical retrovirus, its life cycle has been well characterized. Usually, this process can be divided artificially into several steps, including adsorption, internalization, integration, replication, assembly and release. However, our recombinant MLVs lacked the genes which are essentially for the replication and the virus assembly. Thus only the gene of interest (GOI) could be integrated into the genome and expressed. The process from adsorption to integration can be again subdivided into seven steps, so that each step can be described with a simple mathematical model.

Figure 1. (1) The infection is initiated by the adsorption of the virions onto the cell surface, which is covered by the specific receptor mCAT1. (2) Once the virion binds with the receptor, fusion of viral and cell membrane is triggered and the viral core is internalized into the cytoplasm. (3) Using viral RNA as template, double stranded DNA is produced by reverse transcriptase. (4) The viral DNA is then transported along the microtubuli to the microtubule organizing center near the nucleus. (5) During the transcription and transport, the viral molecules could be degraded by cellular factors. (6) During cell division, the nuclear envelope dissolves and the viral DNA is imported into the nucleus. (7) Viral DNA is integrated into the chromosome by integrase. (modified from1)

The whole infection process was described by a set of differential equations, which was adopted from a previous work1 with small modifications.

First, a viral suspension of depth h was added to a layer of adherent cells to infect them (see Fig. 2). The concentration of the virion (Vm) is a function of both time and depth. It is influenced by four different processes: diffusion, sedimentation, degradation and binding.

Figure 2. Virus suspension and cells

The diffusion of the virions follows the fick’s law of diffusion. u is the velocity of sedimentation due to gravity. Since the virions are instable at 37°C, they decay in the medium with a constant decay rate kd_vm. Thus an additional term was added to the partial differential equation (PDE).

The diffusion coefficient Dv can be calculated according to the Stokes–Einstein equation,

and u was estimated as the Stokes settling velocity.

To solve the PDE, boundary conditions are required at the top and the bottom of the medium. At the top (z=h), net flux of virions has to be zero, so that

At the bottom (z=0), virions bind irreversibly onto the cell surface and are subsequently internalized. The binding rate is proportional to local virus concentration, cell density and density of mCAT1 receptor on the cell surface. Moreover, the binding is saturating at high receptor density, so a Michaelis-constant for receptor density was added to the equation.

Second, the MLV undergoes several steps (see Fig. 1 (3)-(7)) after the internalization to be integrated into the genome. However, it is difficult to determine the intracellular concentration of each viral component. The only output of our experiments was the transduction efficiency determined by flow cytometry. Thus it makes more sense to consider the dynamics between infected and non-infected cells.

According to the location of intracellular viral particles, the cells were divided into three populations (see Fig. 3): virus-free cells (Cf), cells that carry MLV in the cytoplasm (Cc) and cells with viral DNA integrated in the genome (Ci). Similarly, intracellular viral particles were divided into cytoplasmic viruses (Vc) and integrated viruses (Vi). Particularly, a subpopulation of cytoplasmic virus inside the virus-carrying cells only (Vf) was also considered to enable further calculations.

Figure 3. Cell and virus populations and their density.

The dynamics between different cell and virus populations was influenced by several factors (see Fig. 4), including binding of new virions, intracellular degradation of viral particles wit rate kd_vc, integration of viral DNA with integration rate kin, and cell division with a constant growth rate μ.

Figure 4. Dynamics of cell and virus populations.

Thus the differential equations were set up as follows.

δ1 is the possibility of a virus-carrying cell that becomes virus-free owing to the degradation of intracellular virus. Since multiple cytoplasmic viruses are unlikely to degrade at the same time, the possibility equals the fraction of virus-carrying cells with only one virus. Since the distribution of the multiplicities of infection (MOI) follows the poisson distribution, δ1 can be calculated using the following equation,

where n_v is the average number of virus per cell inside the virus-carrying cells.

δ2 is the possibility of a virus-carrying cell that becomes virus-free during cell division. Because virus particles enter two daughter cells in a random process, one of them may lose all particles and became virus-free again. δ2 depends on the MOI of the cell.

Besides, terms for the integration are calculated at time τ prior to the current time point t. τ is the mean trafficking time of the virus inside the cytoplasm and includes time for reverse transcription and viral transport (see Fig. 1 (3)-(4)). These terms turn these differential equations into a delayed differential equation system (DDE), which was solved here by numerical methods using MATLAB.

The experimental output, the transduction efficiency, is defined as the fraction of virus-integrated cells.

Data Analysis

Extracellular virus degradation

The extracellular degradation rate of MLV (kd_vm) was first investigated. MLV suspension was incubated at 37 °C for different durations. The viral concentration should follow a single exponential decay function.

Light System

Model Formulation

Data Analysis