def add_m_model_content(me_model, m_model, complex_metabolite_ids=None):
"""
Add metabolite and reaction attributes to me_model from m_model. Also
creates StoichiometricData objects for each reaction in m_model, and adds
reactions directly to me_model if they are exchanges or demands.
Parameters
----------
me_model : :class:`cobrame.core.model.MEModel`
The MEModel object to which the content will be added
m_model : :class:`cobra.core.model.Model`
The m_model which will act as the source of metabolic content for
MEModel
complex_metabolite_ids : list
List of complexes which are 'metabolites' in the m-model reaction
matrix, but should be treated as complexes
"""
if not complex_metabolite_ids:
complex_metabolite_ids = []
for met in m_model.metabolites:
if met.id in complex_metabolite_ids:
new_met = cobrame.Complex(met.id)
elif met.id.startswith("RNA"):
raise ValueError('Processed M-model should not contain RNAs (%s)' %
met.id)
else:
new_met = cobrame.Metabolite(met.id)
new_met.name = met.name
new_met.formula = met.formula
new_met.compartment = met.compartment
new_met.charge = met.charge
new_met.annotation = met.annotation
new_met.notes = met.notes
me_model.add_metabolites(new_met)
for reaction in m_model.reactions:
if reaction.id.startswith("EX_") or reaction.id.startswith("DM_"):
new_reaction = cobrame.MEReaction(reaction.id)
me_model.add_reaction(new_reaction)
new_reaction.lower_bound = reaction.lower_bound
new_reaction.upper_bound = reaction.upper_bound
for met, stoichiometry in iteritems(reaction.metabolites):
new_reaction.add_metabolites(
{me_model.metabolites.get_by_id(met.id): stoichiometry})
else:
reaction_data = cobrame.StoichiometricData(reaction.id, me_model)
reaction_data.lower_bound = reaction.lower_bound
reaction_data.upper_bound = reaction.upper_bound
reaction_data._stoichiometry = {
k.id: v
for k, v in iteritems(reaction.metabolites)
}
def update_metabolite_formulas(m_model):
# Formulas of metabolites not included in metabolites.txt
# 3a1hac1p_c has a typo in the formula in metabolites.txt
formulas = [('4fe4s_c', 'Fe4S4'), ('2fe2s_c', 'Fe2S2'),
('LI_c', 'Li'), ('3a1hac1p_c', 'C3H7NO5P'),
]
for met, formula in formulas:
try:
met_obj = m_model.metabolites.get_by_id(met)
except KeyError:
warn('Creating new metabolite (%s)' % met)
met_obj = cobrame.Metabolite(met)
m_model.add_metabolites([met_obj])
met_obj.formula = formula
def add_iron_sulfur_modifications(me_model):
for name, complexes in generic_fes_transfer_complexes.items():
generic_fes_transfer = cobrame.GenericData(name, me_model, complexes)
generic_fes_transfer.create_reactions()
for fes in ['2fe2s_c', '4fe4s_c']:
me_model.add_metabolites([cobrame.Metabolite(fes)])
for name in fes_transfer.values():
rxn = cobrame.MEReaction('_'.join([name, fes, 'unloading']))
me_model.add_reactions([rxn])
rxn.add_metabolites({
name + '_mod_1:' + fes.replace('_c', ''): -1,
fes: 1,
name: 1
})
# add fes transfer enzymes to proper modification data
mod_2fe2s = me_model.process_data.mod_2fe2s_c
mod_2fe2s.enzyme = 'generic_2fe2s_transfer_complex'
mod_2fe2s.stoichiometry = {'2fe2s_c': -1.}
mod_4fe4s = me_model.process_data.mod_4fe4s_c
mod_4fe4s.enzyme = 'generic_4fe4s_transfer_complex'
mod_4fe4s.stoichiometry = {'4fe4s_c': -1.}
mod_3fe4s = me_model.process_data.mod_3fe4s_c
mod_3fe4s.enzyme = 'generic_4fe4s_transfer_complex'
mod_3fe4s.stoichiometry = {'4fe4s_c': -1., 'fe2_c': 1}
mod_3fe4s._element_contribution = {'Fe': 3, 'S': 4}
for chaperone in set(fes_chaperones.values()):
new_mod = cobrame.SubreactionData('mod_2fe2s_c_' + chaperone, me_model)
new_mod.enzyme = [chaperone, 'generic_2fe2s_transfer_complex']
new_mod.stoichiometry = {'2fe2s_c': -1.}
for cplx_data in me_model.process_data.get_by_id(
'mod_2fe2s_c').get_complex_data():
cplx_id = cplx_data.id.split('_mod')[0]
if cplx_id in fes_chaperones:
cplx_data.subreactions['mod_2fe2s_c_' + fes_chaperones[
cplx_id]] = \
cplx_data.subreactions.pop('mod_2fe2s_c')
def get_remaining_complex_elements(model, complex, modification_formulas):
tmp_met = cobrame.Metabolite('tmp_met')
mets = model.metabolites
components = complex.id.split('_mod_')
base_complex = components[0]
elements = Counter()
# If a the completely unmodified complex is present in the model
# has a formula, initialize the elements dictionary with that
if base_complex in mets and mets.get_by_id(base_complex).formula:
elements.update(mets.get_by_id(base_complex).elements)
for component in components[1:]:
new_elements = elements.copy()
new_complex = '_mod_'.join([base_complex, component])
if new_complex in mets and mets.get_by_id(new_complex).formula:
# default to new_complex elements if both new and old exist
if base_complex in mets and mets.get_by_id(base_complex).formula:
new_elements = Counter()
formula = mets.get_by_id(new_complex).formula
tmp_met.formula = formula
new_elements.update(tmp_met.elements)
# Net effect of an SH modification is adding a Sulfur to elements
elif ':SH' in component:
new_elements['S'] += 1
# modifies O- to SH
elif component == 'cosh':
new_elements['O'] -= 1
new_elements['S'] += 1
new_elements['H'] += 1
elif component in modification_formulas:
formula = modification_formulas[component]
tmp_met.formula = formula
new_elements.update(tmp_met.elements)
elif ':' in component:
value, component = component.split(':')
if component in modification_formulas:
formula = modification_formulas[component]['formula']
elif component + '_c' in mets:
formula = mets.get_by_id(component + '_c').formula
else:
raise UserWarning('No formula found for modification (%s)' %
component)
tmp_met.formula = formula
for e, v in tmp_met.elements.items():
new_elements[e] += v * float(value)
elif 'Oxidized' in component and 'FLAVODOXIN' not in base_complex:
new_elements.update({'H': -2})
if elements == new_elements and 'FLAVODOXIN' not in base_complex:
print(complex.id, base_complex, component)
base_complex = '_mod_'.join([base_complex, component])
elements = new_elements.copy()
return elements
def process_m_model(m_model,
metabolites_file,
m_to_me_map_file,
reaction_info_file,
reaction_matrix_file,
protein_complex_file,
defer_to_rxn_matrix=set()):
m_model = m_model.copy()
met_info = pandas.read_csv(
fixpath(metabolites_file),
delimiter="\t",
header=None,
index_col=0,
names=["id", "name", "formula", "compartment", "data_source"])
met_info.rename(lambda x: x.replace('_DASH_', '__'), inplace=True)
complex_set = \
set(get_complex_subunit_stoichiometry(protein_complex_file).keys())
rxn_info = get_reaction_info_frame(reaction_info_file)
reaction_matrix_dict = get_reaction_matrix_dict(reaction_matrix_file,
complex_set=complex_set)
m_to_me_df = pandas.read_csv(fixpath(m_to_me_map_file),
index_col=0,
names=['m_name', 'me_name'])
for rxn in list(m_model.reactions):
if rxn.id.startswith('EX_') or rxn.id.startswith('DM_'):
continue
if rxn.id not in reaction_matrix_dict.keys() \
or rxn.id in defer_to_rxn_matrix:
rxn.remove_from_model(remove_orphans=True)
for rxn_id in reaction_matrix_dict:
if rxn_id in m_model.reactions:
continue
rxn_stoichiometry = reaction_matrix_dict[rxn_id]
for met in rxn_stoichiometry:
try:
met_obj = m_model.metabolites.get_by_id(met)
except KeyError:
met_obj = cobrame.Metabolite(str(met))
m_model.add_metabolites([met_obj])
met_id = remove_compartment(met_obj.id)
if met_id in met_info.index and not met_obj.formula:
met_obj.formula = met_info.loc[met_id, 'formula']
met_obj.name = met_info.loc[met_id, 'name']
rxn = cobrame.MEReaction(rxn_id)
m_model.add_reactions([rxn])
rxn.add_metabolites(rxn_stoichiometry)
reversible = rxn_info.loc[rxn_id, 'is_reversible']
rxn.lower_bound = -1000 if reversible else 0
for met in list(m_model.metabolites):
met_id = remove_compartment(met.id)
if met_id not in met_info.index and met_id in m_to_me_df.index:
met_id = m_to_me_df.loc[met.id, 'me_name']
if met_id != '' and met_id != 'N/A':
met.id = met_id
else:
met.remove_from_model()
# Add formulas not included in metabolites.txt
corrections.update_metabolite_formulas(m_model)
m_model.repair()
return m_model