Practical 4

In this practical you will familiarise yourselves with the constraint scanning method covered in the lectures this morning. Specifically you will investigate the response of a rice GSM to changes in photon input. For reference, have a look at the paper.

  1. Download and open the rice model (rice model link here).

  2. Download and import the module with additional constraints (rice model constraint dictionaries).

  3. Create an LP object with the rice GSM as argument (see previous LP exercise for details on how to do this).

  4. Set the objective to minimisation of all fluxes. Since minimisation is the default direction, all you need to do is to use the lp.SetObjective() method with all reactions in the LP object as argument, which can be obtained as lp.cnames.values()

  5. Use the dictionary of biomass fluxes as fixed constraints (lp.SetFixedFlux(...)) and the dictionary of bounds on transporter reactions as flux bounds (lp.SetFluxBounds(...)).

  6. Try to solve the LP and make sure the number of reactions in the solution is non-zero.

  7. You will scan the photon uptake reaction by fixing its flux to a set of value in a linear range, specifically 50 points evenly distributed from 0 to 10. To do this, first generate a list of these values (have a look at your solution to exercise (f) of the python practical).

  8. Define a dictionary where you will collect the LP solutions.

  9. Write a for loop over the list of values generated above. Inside the loop, set the constrain on the photon uptake reaction (chl_Photon_tx) equal to the loop variable, solve the LP, and collect the solution in the dictionary created above (you can use the loop variable as key).

  10. You will now analyse the LP data. Import the module DataSets from Data. In order to collect the names of all reactions that appear in any of the solutions, create an empty dictionary and run a for loop to update it with the reaction names from the solutions generated previously, e.g.: 

   1 >>> reacs = {}
   2 >>> for sol in sol_collection: #given that sol_collection is the dictionary of solutions 
   3         reacs.update(sol_collection[sol])