project_folder = "./ec_model_2019_06_25_output/"
project_name = "psb_orth"
organism = "Escherichia coli"
kcat_database_path = "./ec_model_2019_06_25_output/kcat_database_combined.json"
protein_kcat_database_path = "ec_model_2019_06_25_input_keff_paper/gene_id_data_mapping.json"
get_reactions_kcat_mapping(sbml_path, project_folder, project_name, organism, kcat_database_path, protein_kcat_database_path)
# Step 7
input_sbml = "./ec_model_2019_06_25_input/iJO1366.xml"
project_folder = "./ec_model_2019_06_25_output/"
project_name = "psb_orth"
get_initial_spreadsheets_with_sbml(input_sbml, project_folder, project_name)
# Step 8
input_sbml = "./ec_model_2019_06_25_input/iJO1366.xml"
project_folder = "./ec_model_2019_06_25_output/"
project_name = "psb_orth"
get_protein_mass_mapping_with_sbml(input_sbml, project_folder, project_name)
# Step 9
input_sbml = "./ec_model_2019_06_25_input/iJO1366.xml"
output_sbml = "iJO1366_sMOMENT_2019_06_25_GECKO_ANALOGON.xml"
project_folder = "./ec_model_2019_06_25_output/"
project_name = "psb_orth"
excluded_reactions = ["CO2tex", "O2tex", "H2tex"]
create_smoment_model_reaction_wise_with_sbml(input_sbml, output_sbml, project_folder, project_name, excluded_reactions)
# Step 10 - Generate model with standard exchanges scenario
model = set_up_ec_model_with_sbml("ec_model_2019_06_25_output/iJO1366_sMOMENT_2019_06_25.xml", .25)
cobra.io.write_sbml_model(model, "ec_model_2019_06_25_output/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO.xml")
print("Variability of formate" + ";" +
";".join([str(x) for x in values["formate_var"]]))
print("Variability of lactate" + ";" +
";".join([str(x) for x in values["lactate_var"]]))
print("Variability of succinate" + ";" +
";".join([str(x) for x in values["succinate_var"]]))
print("Variability of CO2" + ";" +
";".join([str(x) for x in values["co2_var"]]))
print("Variability of O2" + ";" +
";".join([str(x) for x in values["o2_var"]]))
print("Variability of protein pool" + ";" +
";".join([str(x) for x in values["prot_pool_var"]]))
print("Minimal O2" + ";" + ";".join([str(x) for x in values["o2_min"]]))
print("Maximal O2" + ";" + ";".join([str(x) for x in values["o2_max"]]))
model = set_up_ec_model_with_sbml(
"./iJO1366star/ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES_FMINCON_CHANGE_FACTOR_50.xml",
0.095)
aerobic_space = list(np.linspace(.14, 9.53, 25)) + list(
np.linspace(9.54, 13.829, 25))
fba_with_glucose_levels(model, aerobic_space, "Aerobe")
"""
print("===")
model.reactions.EX_o2_e.lower_bound = 0
anaerobic_space = list(np.linspace(1.26, 16.69, 25)) + list(np.linspace(16.7, 24.987, 25))
fba_with_glucose_levels(model, anaerobic_space, "Anaerobe")
"""
"Max prot pool?:", fba_solution.fluxes.ER_pool_TG_ ==
model_smoment.reactions.ER_pool_TG_.upper_bound)
print(
"Max glucose?:", fba_solution.fluxes.EX_glc__D_e ==
model_smoment.reactions.EX_glc__D_e.lower_bound)
model_smoment.summary(fva=1.0)
print("Used protein pool:", fba_solution.fluxes.ER_pool_TG_)
print("Used glucose uptake:", fba_solution.fluxes.EX_glc__D_e)
print("=======")
print("")
print("")
print("")
model_gecko = set_up_ec_model_with_sbml(
"./iJO1366star/ec_model_2019_06_25_output/iJO1366_2019_06_25_GECKO.xml",
0.095)
model_smoment = set_up_ec_model_with_sbml(
"./iJO1366star/ec_model_2019_06_25_output/iJO1366_sMOMENT_2019_06_25_GECKO_ANALOGON.xml",
0.095)
print(len(model_gecko.reactions))
print(len(model_smoment.reactions))
print("***")
print(len(model_gecko.metabolites))
print(len(model_smoment.metabolites))
fba_with_glucose_levels(model_gecko, model_smoment,
[1000, 50, 13.9, 9.53, 8.5, 5, 2.5][::-1], "Aerobe")
print("===")
model_gecko.reactions.EX_o2_e.lower_bound = 0
import cobra
# Internal modules
from ec_model_2019_06_25_data_scenarios_for_optimization import ec_model_scenarios_for_optimization
from ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
from autopacmen.submodules.reaction_flux_control_by_scenario import reaction_flux_control_by_scenario
from autopacmen.submodules.get_differential_reactions import get_differential_reactions
from autopacmen.submodules.helper_general import json_write
# Set-up of project
flux_control_folder = "iJO1366star/ec_model_2019_06_25_output_optimization/flux_control_data_2019_06_25_manual_changes/"
project_name = "psb_orth"
# Read SBML model
print("Reading SBML model...")
original_thermogecko_sbml_path: str = "./iJO1366star/ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES.xml"
model: cobra.Model = set_up_ec_model_with_sbml(original_thermogecko_sbml_path,
.095)
# Set protein bound
model.reactions.get_by_id("ER_pool_TG_").upper_bound = .095
# Get flux controlling proteins
print("Getting flux control files...")
reaction_flux_control_by_scenario(model, flux_control_folder, project_name,
ec_model_scenarios_for_optimization)
# Get differential proteins
print("Getting differential reactions (Growth)...")
unique_differential_reactions_of_scenarios, _ = \
get_differential_reactions(list(ec_model_scenarios_for_optimization.keys()), flux_control_folder, project_name,
ec_model_scenarios_for_optimization,
threshold=(.1) / 1000, print_result=True)
import ec_model_2019_06_25_data_set_up_model
import cobra
model = ec_model_2019_06_25_data_set_up_model.set_up_ec_model_with_sbml(
"ec_model_2019_06_25_output_optimization/iJO1366_sMOMENT_2019_06_25_STANDARD_EXCHANGE_SCENARIO_MANUAL_CHANGES.xml",
.095)
reactions_to_change = [
# Acetate
"FLDR2",
"ACKr_TG_forward",
"ACtex_TG_forward",
"POR5_TG_reverse",
"PTAr_TG_reverse",
# Glycerol
"GLYK",
"TRDR",
"G3PD2_TG_forward",
"GLYCtex_TG_forward",
"GTHOr_TG_forward",
# Oxoglutarate
"AKGt2rpp_TG_forward",
"AKGtex_TG_forward",
# L-Alanine
"ASPT",
"DAAD",
"PROD2",
"ALAR_TG_forward",
"ALATA_L_TG_forward",
"ALAtex_TG_forward",
"GLUDy_TG_forward",
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""ec_model_original_generate_comparable_model.py"""
import cobra
from ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
from autopacmen.submodules.helper_create_model import get_irreversible_model
model = set_up_ec_model_with_sbml(
"./iJO1366star/ec_model_2019_06_25_input/iJO1366.xml", .225)
model = get_irreversible_model(model, "_TG_")
cobra.io.write_sbml_model(
model,
"./iJO1366star/ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions.xml"
)
model = set_up_ec_model_with_sbml(
"./iJO1366star/ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions.xml",
.225)
cobra.io.write_sbml_model(
model,
"./iJO1366star/ec_model_2019_06_25_input/iJO1366_saved_by_cobrapy_and_separated_reversible_reactions_SHUT_DOWN_SCENARIO.xml"
)
#
# Copyright 2019 PSB
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""ec_model_analysis_fva_prot_pool.py
"""
from autopacmen.submodules.fva_prot_pool import fva_prot_pool
from ec_model_2019_06_25_data_set_up_model import set_up_ec_model_with_sbml
model = set_up_ec_model_with_sbml(
"./iJO1366star/ec_model_2019_06_25_output_optimization/iJO1366star.xml",
.225)
model.reactions.EX_glc__D_e.lower_bound = -1000
prot_pools = [.3]
prot_pool_metabolite = model.metabolites.prot_pool
fva_prot_pool(model, prot_pools, "")
