Notes
Result generation
- Two types of simulation is being run. In one type of simulation, new parameter distribution is generated for each of the Control and silencing experiments. In the other type of simulation, first a parameter distribution is created and with that same parameter distribution the ensemble models of control and PYK(pyruvate kinase) silencing is being generated.
- When we silence the model using our skeleton model, the PEP(Phosphoenol pyruvate) accumulates and PYR(pyruvate) depletes. But when we calculate statistics from our ensemble of models generated with the parameter distribution, the average steady-state concentration shows a different behavior. In this mean value result, the PYK does deplete but there is no accumulation of PEP. Analyzing the results, we found that there is no specific parameter that is responsible for this undesired result rather it is due to different parameter distributions.
- When we silence the Pyruvate Kinase (dividing Vmax of PYK with 2 or 4 or 10) the PEP is supposed to accumulate and PYR is supposed to deplete. In our average value from the ensemble of models PYR does deplete but PEP does not accumulate. The rate laws has been verified and no mistake was found there. Therefore now the impact of other parameters on this silencing activity is being adjusted.
- We tried to first find out which factor is the most appropriate to divide the Vmax. We found that till factor 4 the PEP accumulates and after factor 4 although PEP concentration is higher than control but it is lower than the concentration we get by dividing with 4. So for silencing PYK we divided the Vmax with 4.
- We then generated 225 stead-states from control model using 300 total parameters. We used this 225 SS models to simulate steady-state for Pyruvate Kinase silenced by dividing Vmax with 4. This gives 202 SS models in PYK_Silence. We then deleted the No-steady state models of PYK_Silence from Control Data.
- We then wrote a Matlab script to filter the steady-state result from both Control and PYK_Silence for which the PEP concentration is higher in PYK_Silence compared to Control. We did this because we wanted to associate this fundamental information with our model and this is one of the criteria that the models should satisfy in order to perform correctly. This gives a total of 108 models where PEP is accumulated and Pyr is consumed in PYK_silence compared to Control
- We then took the parameter distribution associated with this 108 models to simulate the steady-state for different extracellular Serine concentration.
- For ease of notation we will designate the control model as shCntrl and the Pyruvate kinase silencing model as shPyk.
Model Checklist
| Criteria | Result | Comments |
|---|---|---|
| In the warburg effect, energy production is shifted from pyruvate metabolism to lactate production. To imitate this physiological phenomena in our model, the Lactate dehydrogenase (LDH) should have higher flux compared to Mitochondrial pyruvate metabolism (MPM). | YES | In shCntrl the LDH flux is 0.000385149 and for MPM the flux value is 1.09621E-07. This clearly indicates that the flux through LDH is higher in the model compared to MPM. |
| Acorrding to Chaneton et. al. [1] when the pyruvate kinase is silenced, the phosphoenol pyruvate (PEP) should be accumulating and pyruvate should be depleting. | YES (with observation) | The average value calculated from 108 ensemble models shows that the PEP concentration in shCntrl as 0.000638559 and in shPyk as 0.000875017 indicating PEP accumulation in the shPyk. However, the paper reported a 100 fold increase in PEP in their experiment whereas in our model it is only 1.3 fold. |
| Acorrding to Chaneton et. al. [1] ~50% decrease is reported in Pyruvate levels in shPyk. | YES | In our model, the concentration of Pyruvate in shCntrl is 0.00080755 and in shPyk the concentration is 0.000450444 showing a decrease in Pyruvate for shPyk. In our model the decrease is ~44%. |
| Chaneton et. al. [1] also reported that Blocking PYK activity shifted the metabolism of glucose away from lactate production to citrate production in the mitochondria. This is shown in Figure 2 of the paper where cumulative intensities of each of the metabolite isotopomers was analyzed at the indicate time point. In the figure it can be seen that the cummulative intensity of Lactate is lower in shPyk compared to shCntrl. | YES | In our model, the intracellular steady-state Lactate concentration of shCntrl is 0.00074 and for shPyk it is 0.00041. This shows that the lactate production is decreased in shPyk compared to shCntrl as shown in the paper. |
References
- ↑ 1.0 1.1 1.2 Barbara Chaneton, Petra Hillmann, Liang Zheng, Agnès C. L. Martin, Oliver D. K. Maddocks, Achuthanunni Chokkathukalam, Joseph E. Coyle, Andris Jankevics, Finn P. Holding, Karen H. Vousden, Christian Frezza, Marc O’Reilly & Eyal Gottlieb (2012). 'Serine is a natural ligand and allosteric activator of pyruvate kinase M2, Nature, 491:458–462 (doi)
