7. Simulating at INST State

FreeFlux can estimate metabolic fluxes for organisms that uptake one-carbon compounds like autotrophs using carbon dioxide. For this, kinetics of intermediate MDVs are required at the isotopically non-stationary (INST) state. The derived MDVs will be a function of time.

To simulate MDVs at INST state, use the following commands, similar to those used for steady state:

from freeflux import Model

MODEL_FILE = 'path/to/reactions.tsv'

model = Model('demo')
model.read_from_file(MODEL_FILE)

isim = model.simulator('inst')
isim.set_target_EMUs({
    'Glu': [[1,2,3], '12345'],
    'Cit': '2345'
})
isim.set_labeling_strategy(
    'AcCoA',
    labeling_pattern = ['01', '11'],
    percentage = [0.25, 0.25],
    purity = [1, 1]
)

fluxes = {'v1': 10,
          'v2': 10,
          'v3': 5,
          'v4': 5,
          'v5': 5,
          'v6_f': 12.5,   # "_f" denotes forward flux
          'v6_b': 7.5,    # "_b" denotes backward flux
          'v7': 5}
for fluxid, value in fluxes.items():
    isim.set_flux(fluxid, value)

# or read from file
FLUXES_FILE = 'path/to/fluxes.tsv'
isim.set_fluxes_from_file(FLUXES_FILE)

The input files can be found here.

In addition to the fluxes, metabolite concentrations are also required for INST state simulation. The concentration of metabolites can be set as follows:

concs = {'OAA': 0.1,
         'Cit': 5,
         'AKG': 0.3,
         'Suc': 1,
         'Fum': 0.2,
         'Glu': 0.5}
for concid, value in concs.items():
    isim.set_concentration(concid, value)

# or read from file
CONCS_FILE = 'path/to/concentrations.tsv'
isim.set_concentrations_from_file(CONCS_FILE)

Lastly, set the time points when MDVs will be simulated:

isim.set_timepoints([0, 0.1, 0.2, 0.5, 1, 2])

Note: Units for flux, concentration, and timepoint are not specified in this toy example, but they should be included in practical examples.

Finally, to simulate the kinetics of MDVs, use the following code:

isim.prepare()
res = isim.simulate()

for emuid in ['Glu_123', 'Glu_12345', 'Cit_2345']:
    res.plot_MDV_kinetics(emuid, show_fig = True, output_dir = None)

Similarly, the work can be done using the with statement:

with model.simulator('inst') as isim:
    isim.set_target_EMUs({
        'Glu': [[1,2,3], '12345'],
        'Cit': '2345'
    })
    isim.set_timepoints([0, 0.1, 0.2, 0.5, 1, 2])
    isim.set_labeling_strategy(
        'AcCoA',
        labeling_pattern = ['01', '11'],
        percentage = [0.25, 0.25],
        purity = [1, 1]
    )
    isim.set_fluxes_from_file(FLUXES_FILE)
    isim.set_concentrations_from_file(CONCS_FILE)
    isim.prepare()
    res = isim.simulate()

A more complex example of simulation at INST state using an Synechocystis model is provided in the script “tutorial_synechocystis_inst_simulation.py”