def test_measurements_adapter(iJO1366):
iJO1366, biomass_reaction, is_ec_model = iJO1366
uptake_secretion_rates = [
{
"name": "Foo",
"identifier": "CHEBI:42758",
"namespace": "chebi",
"measurement": -9.0,
"uncertainty": 0,
},
{
"name": "Foo",
"identifier": "CHEBI:16236",
"namespace": "chebi",
"measurement": 4.9,
"uncertainty": 0,
},
]
fluxomics = [
{
"name": "Foo",
"identifier": "PFK",
"namespace": "bigg.reaction",
"measurement": 4.8,
"uncertainty": 0,
},
{
"name": "Foo",
"identifier": "PGK",
"namespace": "bigg.reaction",
"measurement": 5,
"uncertainty": 0,
},
]
proteomics = {
"identifier": "P0A8V2",
"measurement": 5.03e-6,
"uncertainty": 0
}
operations, warnings, errors = apply_measurements(
iJO1366,
biomass_reaction,
is_ec_model,
fluxomics,
[],
proteomics,
uptake_secretion_rates,
[],
None,
)
# 4 operations (2 rates + 2 fluxomics) + 1 warning (not an ecModel) are expected:
assert len(operations) == 4
assert len(warnings) == 1
assert len(errors) == 0
def test_measurements_adapter_ec_model(eciML1515):
# successfully flexibilize -> apply kinetics + growth rate + only 1 protein
eciML1515, biomass_reaction, is_ec_model = eciML1515
proteomics = [
{
"identifier": "P0AFG8",
"measurement": 8.2e-3, # very high value (should be kept)
"uncertainty": 8.2e-6,
},
{
"identifier": "P15254",
"measurement": 6.54e-8, # very low value (should be removed)
"uncertainty": 0,
},
]
uptake_secretion_rates = [
{
"name": "glucose",
"identifier": "MNXM41",
"namespace": "metanetx.chemical",
"measurement": -9.8,
"uncertainty": 0.3,
},
{
"name": "ethanol",
"identifier": "MNXM303",
"namespace": "metanetx.chemical",
"measurement": 0.5,
"uncertainty": 0,
},
]
growth_rate = {"measurement": 0.1, "uncertainty": 0.01}
operations, warnings, errors = apply_measurements(
eciML1515,
biomass_reaction,
is_ec_model,
[],
[],
proteomics,
uptake_secretion_rates,
[],
growth_rate,
)
# 4 operations (1 protein + 1 uptake + 1 secretion + growth rate) + 1 warning
# (removed protein due to flexibilization) are expected:
assert len(operations) == 4
assert len(warnings) == 1
assert len(errors) == 0
def test_measurements_adapter(iJO1366):
iJO1366, biomass_reaction = iJO1366
uptake_secretion_rates = [
{
"name": "Foo",
"identifier": "CHEBI:42758",
"namespace": "chebi",
"measurement": -9.0,
"uncertainty": 0,
},
{
"name": "Foo",
"identifier": "CHEBI:16236",
"namespace": "chebi",
"measurement": 4.9,
"uncertainty": 0,
},
]
fluxomics = [
{
"name": "Foo",
"identifier": "PFK",
"namespace": "bigg.reaction",
"measurement": 4.8,
"uncertainty": 0,
},
{
"name": "Foo",
"identifier": "PGK",
"namespace": "bigg.reaction",
"measurement": 5,
"uncertainty": 0,
},
]
operations, warnings, errors = apply_measurements(iJO1366,
biomass_reaction,
fluxomics, [],
uptake_secretion_rates,
[], None)
assert len(operations) == 4
assert len(errors) == 0
def test_measurements_adapter_ec_model_skip(eciML1515):
# skip flexibilization (no growth rate provided) + skip unmatched protein
eciML1515, biomass_reaction, is_ec_model = eciML1515
proteomics = [
{
"identifier": "P15254",
"measurement": 6.54e-8, # protein in model (should be kept)
"uncertainty": 0,
},
{
"identifier": "P0A8V2", # protein not in model (should be skipped)
"measurement": 5.03e-6,
"uncertainty": 0,
},
]
operations, warnings, errors = apply_measurements(eciML1515,
biomass_reaction,
is_ec_model, [], [],
proteomics, [], [], [])
# 1 operation (kept protein) + 1 warning (skipped protein) are expected:
assert len(operations) == 1
assert len(warnings) == 1
assert len(errors) == 0
def test_measurements_adapter_errors(iJO1366):
# record unmatched metabolites and reactions as errors
iJO1366, biomass_reaction, is_ec_model = iJO1366
uptake_secretion_rates = [
{
"name": "not a match",
"identifier": "CHEBI:123456789", # non-existing id
"namespace": "chebi",
"measurement": 4.9,
"uncertainty": 0,
},
]
fluxomics = [
{
"name": "not a match",
"identifier": "ASDFGHJKL", # non-existing id
"namespace": "bigg.reaction",
"measurement": 5,
"uncertainty": 0,
},
]
operations, warnings, errors = apply_measurements(
iJO1366,
biomass_reaction,
is_ec_model,
fluxomics,
[],
[],
uptake_secretion_rates,
[],
None,
)
# 2 errors (metabolite not found + reaction not found) are expected:
assert len(operations) == 0
assert len(warnings) == 0
assert len(errors) == 2
def model_modify(
model_id,
medium,
genotype,
fluxomics,
metabolomics,
uptake_secretion_rates,
molar_yields,
growth_rate,
):
if not request.is_json:
abort(415, "Non-JSON request content is not supported")
try:
model_wrapper = storage.get(model_id)
except Unauthorized as error:
abort(401, error.message)
except Forbidden as error:
abort(403, error.message)
except ModelNotFound as error:
abort(404, error.message)
# Use the context manager to undo all modifications to the shared model instance on
# completion.
with model_wrapper.model as model:
# Build list of operations to perform on the model
operations = []
warnings = []
errors = []
if medium:
results = apply_medium(model, medium)
operations.extend(results[0])
warnings.extend(results[1])
errors.extend(results[2])
if genotype:
results = apply_genotype(model, genotype)
operations.extend(results[0])
warnings.extend(results[1])
errors.extend(results[2])
if (
fluxomics
or metabolomics
or uptake_secretion_rates
or molar_yields
or growth_rate
):
results = apply_measurements(
model,
model_wrapper.biomass_reaction,
fluxomics,
metabolomics,
uptake_secretion_rates,
molar_yields,
growth_rate,
)
operations.extend(results[0])
warnings.extend(results[1])
errors.extend(results[2])
if errors:
# If any errors occured during modifications, discard generated operations
# and return the error messages to the client for follow-up
return {"errors": errors}, 400
else:
return {"operations": operations, "warnings": warnings}