# -*- coding: utf-8 -*-
# Copyright 2016 Novo Nordisk Foundation Center for Biosustainability,
# Technical University of Denmark.
#
# 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.
"""Helper functions that are used all over the memote package."""
from __future__ import absolute_import
import logging
import re
from builtins import dict
from collections import defaultdict
from six import iteritems, itervalues
from sympy import expand
LOGGER = logging.getLogger(__name__)
[docs]def find_transported_elements(rxn):
"""
Return a dictionary showing the amount of transported elements of a rxn.
Collects the elements for each metabolite participating in a reaction,
multiplies the amount by the metabolite's stoichiometry in the reaction and
bins the result according to the compartment that metabolite is in. This
produces a dictionary of dictionaries such as this
``{'p': {'C': -1, 'H': -4}, c: {'C': 1, 'H': 4}}`` which shows the
transported entities. This dictionary is then simplified to only include
the non-zero elements of one single compartment i.e. showing the precise
elements that are transported.
Parameters
----------
rxn : cobra.Reaction
Any cobra.Reaction containing metabolites.
"""
element_dist = defaultdict()
# Collecting elements for each metabolite.
for met in rxn.metabolites:
if met.compartment not in element_dist:
# Multiplication by the metabolite stoichiometry.
element_dist[met.compartment] = \
{k: v * rxn.metabolites[met]
for (k, v) in iteritems(met.elements)}
else:
x = {k: v * rxn.metabolites[met] for (k, v) in
iteritems(met.elements)}
y = element_dist[met.compartment]
element_dist[met.compartment] = \
{k: x.get(k, 0) + y.get(k, 0) for k in set(x) | set(y)}
delta_dict = defaultdict()
# Simplification of the resulting dictionary of dictionaries.
for elements in itervalues(element_dist):
delta_dict.update(elements)
# Only non-zero values get included in the returned delta-dict.
delta_dict = {k: abs(v) for (k, v) in iteritems(delta_dict) if v != 0}
return delta_dict
[docs]def find_transport_reactions(model):
"""
Return a list of all transport reactions.
Parameters
----------
model : cobra.Model
The metabolic model under investigation.
Notes
-----
A transport reaction is defined as follows:
1. It contains metabolites from at least 2 compartments and
2. at least 1 metabolite undergoes no chemical reaction, i.e.,
the formula stays the same on both sides of the equation.
This function will not identify transport via the PTS System.
"""
transport_reactions = []
for rxn in model.reactions:
# Collecting criteria to classify transporters by.
rxn_reactants = set([met.formula for met in rxn.reactants])
rxn_products = set([met.formula for met in rxn.products])
# Looking for formulas that stay the same on both side of the reaction.
transported_mets = \
[formula for formula in rxn_reactants if formula in rxn_products]
# Collect information on the elemental differences between
# compartments in the reaction.
delta_dicts = find_transported_elements(rxn)
non_zero_array = [v for (k, v) in iteritems(delta_dicts) if v != 0]
# Weeding out reactions such as oxidoreductases where no net
# transport of Hydrogen is occurring, but rather just an exchange of
# electrons or charges effecting a change in protonation.
if set(transported_mets) != set('H') and list(
delta_dicts.keys()
) == ['H']:
pass
# All other reactions for which the amount of transported elements is
# not zero, which are not part of the model's exchange nor
# biomass reactions, are defined as transport reactions.
# This includes reactions where the transported metabolite reacts with
# a carrier molecule.
elif sum(non_zero_array) and rxn not in model.exchanges and \
rxn not in find_biomass_reaction(model):
transport_reactions.append(rxn)
return transport_reactions
[docs]def find_converting_reactions(model, pair):
"""
Find reactions which convert a given metabolite pair.
Parameters
----------
model : cobra.Model
The metabolic model under investigation.
pair: tuple or list
A pair of metabolite identifiers without compartment suffix.
Returns
-------
frozenset
The set of reactions that have one of the pair on their left-hand
side and the other on the right-hand side.
"""
met_ids = [m.id for m in model.metabolites]
first = set(model.metabolites.get_by_id(m)
for m in met_ids if m.startswith(pair[0]))
second = set(model.metabolites.get_by_id(m)
for m in met_ids if m.startswith(pair[1]))
hits = list()
for rxn in model.reactions:
if len(first & set(rxn.reactants)) > 0 and len(
second & set(rxn.products)) > 0:
hits.append(rxn)
elif len(first & set(rxn.products)) > 0 and len(
second & set(rxn.reactants)) > 0:
hits.append(rxn)
return frozenset(hits)
[docs]def find_biomass_reaction(model):
"""
Return a list of the biomass reaction(s) of the model.
Parameters
----------
model : cobra.Model
The metabolic model under investigation.
"""
return [rxn for rxn in model.reactions if "biomass" in rxn.id.lower()]
[docs]def df2dict(df):
"""Turn a `pandas.DataFrame` into a `dict` of lists."""
blob = dict((key, df[key].tolist()) for key in df.columns)
blob["index"] = df.index.tolist()
return blob
[docs]def find_demand_reactions(model):
u"""
Return a list of demand reactions.
Parameters
----------
model : cobra.Model
A cobrapy metabolic model
Notes
-----
[1] defines demand reactions as:
-- 'unbalanced network reactions that allow the accumulation of a compound'
-- reactions that are chiefly added during the gap-filling process
-- as a means of dealing with 'compounds that are known to be produced by
the organism [..] (i) for which no information is available about their
fractional distribution to the biomass or (ii) which may only be produced
in some environmental conditions
-- reactions with a formula such as: 'met_c -> '
Demand reactions differ from exchange reactions in that the metabolites
are not removed from the extracellular environment, but from any of the
organism's compartments.
References
----------
.. [1] Thiele, I., & Palsson, B. Ø. (2010, January). A protocol for
generating a high-quality genome-scale metabolic reconstruction.
Nature protocols. Nature Publishing Group.
http://doi.org/10.1038/nprot.2009.203
"""
demand_and_exchange_rxns = set(model.exchanges)
return [rxn for rxn in demand_and_exchange_rxns
if not rxn.reversibility and not
any(c in rxn.get_compartments() for c in ['e'])]
[docs]def find_sink_reactions(model):
u"""
Return a list of sink reactions.
Parameters
----------
model : cobra.Model
A cobrapy metabolic model
Notes
-----
[1] defines sink reactions as:
-- 'similar to demand reactions' but reversible, thus able to supply the
model with metabolites
-- reactions that are chiefly added during the gap-filling process
-- as a means of dealing with 'compounds that are produced by nonmetabolic
cellular processes but that need to be metabolized'
-- reactions with a formula such as: 'met_c <-> '
Sink reactions differ from exchange reactions in that the metabolites
are not removed from the extracellular environment, but from any of the
organism's compartments.
References
----------
.. [1] Thiele, I., & Palsson, B. Ø. (2010, January). A protocol for
generating a high-quality genome-scale metabolic reconstruction.
Nature protocols. Nature Publishing Group.
http://doi.org/10.1038/nprot.2009.203
"""
demand_and_exchange_rxns = set(model.exchanges)
return [rxn for rxn in demand_and_exchange_rxns
if rxn.reversibility and not
any(c in rxn.get_compartments() for c in ['e'])]
[docs]def find_exchange_rxns(model):
u"""
Return a list of exchange reactions.
Parameters
----------
model : cobra.Model
A cobrapy metabolic model
Notes
-----
[1] defines exchange reactions as:
-- reactions that 'define the extracellular environment'
-- 'unbalanced, extra-organism reactions that represent the supply to or
removal of metabolites from the extra-organism "space"'
-- reactions with a formula such as: 'met_e -> ' or ' -> met_e' or
'met_e <=> '
Exchange reactions differ from demand reactions in that the metabolites
are removed from or added to the extracellular environment only. With this
the uptake or secretion of a metabolite is modeled, respectively.
References
----------
.. [1] Thiele, I., & Palsson, B. Ø. (2010, January). A protocol for
generating a high-quality genome-scale metabolic reconstruction.
Nature protocols. Nature Publishing Group.
http://doi.org/10.1038/nprot.2009.203
"""
demand_and_exchange_rxns = set(model.exchanges)
return [rxn for rxn in demand_and_exchange_rxns
if any(c in rxn.get_compartments() for c in ['e'])]
[docs]def find_functional_units(gpr_str):
"""
Return an iterator of gene IDs grouped by boolean rules from the gpr_str.
The gpr_str is first transformed into an algebraic expression, replacing
the boolean operators 'or' with '+' and 'and' with '*'. Treating the
gene IDs as sympy.symbols this allows a mathematical expansion of the
algebraic expression. The expanded form is then split again producing sets
of gene IDs that in the gpr_str had an 'and' relationship.
Parameters
----------
gpr_str : string
A string consisting of gene ids and the boolean expressions 'and'
and 'or'
"""
algebraic_form = re.sub('[Oo]r', '+', re.sub('[Aa]nd', '*', gpr_str))
expanded = str(expand(algebraic_form))
for unit in expanded.replace('+', ',').split(' , '):
yield unit.split('*')
