ecoli.processes.metabolism
Metabolism
Encodes molecular simulation of microbial metabolism using flux-balance analysis.
This process demonstrates how metabolites are taken up from the environment and converted into other metabolites for use in other processes.
NOTE: - In wcEcoli, metabolism only runs after all other processes have completed and internal states have been updated (deriver-like, no partitioning necessary)
- class ecoli.processes.metabolism.FluxBalanceAnalysisModel(parameters, timeline, include_ppgpp=True)[source]
Bases:
object
Metabolism model that solves an FBA problem with modular_fba.
- Parameters:
- set_molecule_levels(metabolite_counts, counts_to_molar, coefficient, current_media_id, unconstrained, constrained, conc_updates, aa_uptake_package=None)[source]
Set internal and external molecule levels available to the FBA solver.
- Parameters:
metabolite_counts (ndarray[Any, dtype[int64]]) – counts for each metabolite with a concentration target
counts_to_molar (Unum) – conversion from counts to molar (counts/volume)
coefficient (Unum) – coefficient to convert from mmol/g DCW/hr to mM basis (mass*time/volume)
current_media_id (str) – ID of current media
unconstrained (set[str]) – molecules that have unconstrained import
constrained (set[str]) – molecules (keys) and their limited max uptake rates (mol / mass / time)
conc_updates (dict[str, Unum]) – updates to concentrations targets for molecules (mmol/L)
aa_uptake_package (tuple[ndarray[Any, dtype[float64]], ndarray[Any, dtype[str_]], bool] | None) – (uptake rates, amino acid names, force levels), determines whether to set hard uptake rates
- set_reaction_bounds(catalyst_counts, counts_to_molar, coefficient, gtp_to_hydrolyze)[source]
Set reaction bounds for constrained reactions in the FBA object.
- Parameters:
catalyst_counts (ndarray[Any, dtype[int64]]) – counts of enzyme catalysts
counts_to_molar (Unum) – conversion from counts to molar (counts/volume)
coefficient (Unum) – coefficient to convert from mmol/g DCW/hr to mM basis (mass*time/volume)
gtp_to_hydrolyze (float) – number of GTP molecules to hydrolyze to account for consumption in translation
- set_reaction_targets(kinetic_enzyme_counts, kinetic_substrate_counts, counts_to_molar, time_step)[source]
Set reaction targets for constrained reactions in the FBA object.
- Parameters:
kinetic_enzyme_counts (ndarray[Any, dtype[int64]]) – counts of enzymes used in kinetic constraints
kinetic_substrate_counts (ndarray[Any, dtype[int64]]) – counts of substrates used in kinetic constraints
counts_to_molar (Unum) – conversion from counts to molar (counts/volume)
time_step (Unum) – current time step (time)
- Returns:
3-element tuple containing
mean_targets: mean target for each constrained reaction
upper_targets: upper target limit for each constrained reaction
lower_targets: lower target limit for each constrained reaction
- Return type:
tuple[ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]], ndarray[Any, dtype[float64]]]
- update_external_molecule_levels(objective, metabolite_concentrations, external_molecule_levels)[source]
Limit amino acid uptake to what is needed to meet concentration objective to prevent use as carbon source, otherwise could be used as an infinite nutrient source.
- Parameters:
objective (dict[str, Unum]) – homeostatic objective for internal molecules (molecule ID: concentration in counts/volume units)
metabolite_concentrations (Unum) – concentration for each molecule in metabolite_names
external_molecule_levels (ndarray[Any, dtype[float64]]) – current limits on external molecule availability
- Returns:
Updated limits on external molecule availability
- Return type:
- TODO(wcEcoli):
determine rate of uptake so that some amino acid uptake can be used as a carbon/nitrogen source
- class ecoli.processes.metabolism.Metabolism(parameters=None)[source]
Bases:
Step
Metabolism Process
-
defaults: Dict[str, Any]
{ 'aa_exchange_names': [], 'aa_names': [], 'aa_targets_not_updated': set(), 'amino_acid_ids': {}, 'avogadro': 6.02214076e+23 [1/mol], 'base_reaction_ids': [], 'cell_density': 1100.0 [g/L], 'cell_dry_mass_fraction': 0.3, 'current_timeline': None, 'dark_atp': 33.565052868380675 [mmol/g], 'doubling_time': 44.0 [min], 'exchange_data_from_media': <function Metabolism.<lambda> at 0x7fc270e6ed40>, 'exchange_molecules': [], 'fba_reaction_ids_to_base_reaction_ids': [], 'get_biomass_as_concentrations': <function Metabolism.<lambda> at 0x7fc270e6e980>, 'get_import_constraints': <function Metabolism.<lambda> at 0x7fc270e17d80>, 'get_masses': <function Metabolism.<lambda> at 0x7fc270e6ede0>, 'get_ppGpp_conc': <function Metabolism.<lambda> at 0x7fc270e6eca0>, 'import_constraint_threshold': 0, 'imports': {}, 'include_ppgpp': False, 'linked_metabolites': None, 'mechanistic_aa_transport': False, 'media_id': 'minimal', 'metabolism': {}, 'ngam': 8.39 [mmol/g.h], 'nutrientToDoublingTime': {}, 'ppgpp_id': 'ppgpp', 'reduce_murein_objective': False, 'removed_aa_uptake': [], 'seed': 0, 'time_step': 1, 'use_trna_charging': False}
- name = 'ecoli-metabolism'
-
topology
{ 'boundary': ('boundary',), 'bulk': ('bulk',), 'bulk_total': ('bulk',), 'environment': {'_path': ('environment',), 'exchange': ('exchange',)}, 'global_time': ('global_time',), 'listeners': ('listeners',), 'next_update_time': ('next_update_time', 'metabolism'), 'polypeptide_elongation': ('process_state', 'polypeptide_elongation'), 'timestep': ('timestep',)}
- update_amino_acid_targets(counts_to_molar, count_diff, amino_acid_counts)[source]
Finds new amino acid concentration targets based on difference in supply and number of amino acids used in polypeptide_elongation. Skips updates to molecules defined in self.aa_targets_not_updated: - L-SELENOCYSTEINE: rare AA that led to high variability when updated
- update_condition(timestep, states)[source]
See
update_condition()
.
-
defaults: Dict[str, Any]