Team:KULeuven/Death

Modeling Celldeath

1. Description of the cell death system

For a full description, we refer to the extended project page. This section shows only a brief summary of the cell death description.

The cell death mechanism we use, will be induced when stimulus 1 (L-arabinose) or stimulus 2 (lactose) and at the same time a cold temperature is applied.

Procedure: We grow the bacteria at the optimal temperature of 37 degrees. Then we produce the protein we wish by applying the correct stimulus, e.g., L-arabinose to produce AFP. After synthesizing the desired amount of protein, we lower the temperature to induce the cell death mechanism.

FIGURE 1: pLac-luxR hybrid promotor		FIGURE 2: plux-cI promotor

ODE

2. CellDeath Model

3. Simulations

We made a simulation in such a way that the ribokey-RNA is present at a constant value (figure 3). With this assumption, the only variable in the production for CeaB would be CeaB mRNA which linearly increases. Initially the production of CeaB is increasing non-linearly, but after a certain amount of time CeaB production becomes linear (figure 4); at that moment the degradation of CeaB is becoming important as well. Production of CeaB is the rate-limiting reaction.

Here, the input of lactose or arabinose is assumed to be constant. To improve this model, it could be updated with a varying input for lactose or arabinose. Also a temperature-varying parameter will be necessary, because the promoter we use is temperature sensitive.

FIGURE 3: ribokey-RNA value hold constant, increase of CeaB



FIGURE 4: Eventually CeaB concentration increases linearly with time

4. Sensitivity analysis

In these graphs, the 'parameters'-axis shows the parameters that are varied in the sensitivity analysis, while the ones along the states axis are the ones monitored as output. The z-axis is a measure for the sensitivity of the parameter under study.

The sensitivity plots are starting from 10 seconds and ending with 10 000 seconds. The importance of sensitivity shifts from the transcription parameter to the degradation parameters.

In nature the transcription parameters will be important for a longer time, but with our simplified model the sensitivity of degradation parameters is already more important than transcription parameters after 1000s.

For optimizing the system in future, we suggest to rebuild the promoter sequence to become higher value for transcription parameters. Another possibility is to lower the degradation parameters by increasing stability of the CeaB protein. The parameter scan figures display the results of a possible variation in these parameters.

FIGURE 5: sensitivity at 10s		FIGURE 6: sensitivity at 100s
FIGURE 7: sensitivity at 1000s		FIGURE 8: sensitivity at 10000s

FIGURE 9: CeaB transcription parameter scan, values between 0.02 and 0.03



FIGURE 10: CeaB degradation parameter scan, values between 0.0009 and 0.0001