ecoli.processes.polypeptide_elongation
Polypeptide Elongation
This process models the polymerization of amino acids into polypeptides by ribosomes using an mRNA transcript as a template. Elongation terminates once a ribosome has reached the end of an mRNA transcript. Polymerization occurs across all ribosomes simultaneously and resources are allocated to maximize the progress of all ribosomes within the limits of the maximum ribosome elongation rate, available amino acids and GTP, and the length of the transcript.
- class ecoli.processes.polypeptide_elongation.BaseElongationModel(parameters, process)[source]
Bases:
object
Base Model: Request amino acids according to upcoming sequence, assuming max ribosome elongation.
- elongation_rate(states)[source]
Sets ribosome elongation rate accordint to the media; returns max value of 22 amino acids/second.
- ecoli.processes.polypeptide_elongation.MICROMOLAR_UNITS = 1.0 [umol/L]
Units used for all concentrations.
- class ecoli.processes.polypeptide_elongation.PolypeptideElongation(parameters=None)[source]
Bases:
PartitionedProcess
Polypeptide Elongation PartitionedProcess
- defaults:
proteinIds: array length n of protein names
- calculate_request(timestep, states)[source]
Set ribosome elongation rate based on simulation medium environment and elongation rate factor which is used to create single-cell variability in growth rate The maximum number of amino acids that can be elongated in a single timestep is set to 22 intentionally as the minimum number of padding values on the protein sequence matrix is set to 22. If timesteps longer than 1.0s are used, this feature will lead to errors in the effective ribosome elongation rate.
-
defaults: Dict[str, Any]
{ 'KD_RelA': 0.26, 'KI_SpoT': 20.0, 'KMaa': 100.0, 'KMtf': 1.0, 'aaNames': [ 'L-ALPHA-ALANINE[c]', 'ARG[c]', 'ASN[c]', 'L-ASPARTATE[c]', 'CYS[c]', 'GLT[c]', 'GLN[c]', 'GLY[c]', 'HIS[c]', 'ILE[c]', 'LEU[c]', 'LYS[c]', 'MET[c]', 'PHE[c]', 'PRO[c]', 'SER[c]', 'THR[c]', 'TRP[c]', 'TYR[c]', 'L-SELENOCYSTEINE[c]', 'VAL[c]'], 'aaWeightsIncorporated': array([], dtype=float64), 'aa_enzymes': [], 'aa_exchange_names': [ 'L-ALPHA-ALANINE[c]', 'ARG[c]', 'ASN[c]', 'L-ASPARTATE[c]', 'CYS[c]', 'GLT[c]', 'GLN[c]', 'GLY[c]', 'HIS[c]', 'ILE[c]', 'LEU[c]', 'LYS[c]', 'MET[c]', 'PHE[c]', 'PRO[c]', 'SER[c]', 'THR[c]', 'TRP[c]', 'TYR[c]', 'L-SELENOCYSTEINE[c]', 'VAL[c]'], 'aa_exporters': [], 'aa_from_synthetase': array([], shape=(1, 0), dtype=float64), 'aa_from_trna': array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]), 'aa_importers': [], 'aa_supply_in_charging': False, 'aa_supply_scaling': <function PolypeptideElongation.<lambda> at 0x7f82414920c0>, 'adjust_timestep_for_charging': False, 'amino_acid_export': None, 'amino_acid_import': None, 'amino_acid_synthesis': None, 'amino_acids': [ 'L-ALPHA-ALANINE[c]', 'ARG[c]', 'ASN[c]', 'L-ASPARTATE[c]', 'CYS[c]', 'GLT[c]', 'GLN[c]', 'GLY[c]', 'HIS[c]', 'ILE[c]', 'LEU[c]', 'LYS[c]', 'MET[c]', 'PHE[c]', 'PRO[c]', 'SER[c]', 'THR[c]', 'TRP[c]', 'TYR[c]', 'L-SELENOCYSTEINE[c]', 'VAL[c]'], 'basal_elongation_rate': 22.0, 'cellDensity': 1100.0 [g/L], 'charged_trna_names': [], 'charging_molecule_names': [], 'charging_stoich_matrix': array([], shape=(1, 0), dtype=float64), 'degradation_index': 1, 'disable_ppgpp_elongation_inhibition': False, 'elong_rate_by_ppgpp': 0, 'elongation_max': 22.0 [amino_acid/s], 'emit_unique': False, 'endWeight': array([2.99146113e-08]), 'get_pathway_enzyme_counts_per_aa': None, 'gtpPerElongation': 4.2, 'import_constraint_threshold': 0, 'import_threshold': 1e-05, 'kS': 100.0, 'k_RelA': 75.0, 'k_SpoT_deg': 0.23, 'k_SpoT_syn': 2.6, 'krta': 1.0, 'krtf': 500.0, 'make_elongation_rates': <function PolypeptideElongation.<lambda> at 0x7f8241492020>, 'max_time_step': 2.0, 'mechanistic_aa_transport': False, 'mechanistic_supply': False, 'mechanistic_translation_supply': False, 'n_avogadro': 6.02214076e+23 [1/mol], 'next_aa_pad': 1, 'ppgpp': 'ppGpp', 'ppgpp_degradation_reaction': 'PPGPPSYN-RXN', 'ppgpp_reaction_metabolites': [], 'ppgpp_reaction_names': [], 'ppgpp_reaction_stoich': array([], shape=(1, 0), dtype=float64), 'ppgpp_regulation': False, 'ppgpp_synthesis_reaction': 'GDPPYPHOSKIN-RXN', 'proteinIds': array([], dtype=float64), 'proteinLengths': array([], dtype=float64), 'proteinSequences': array([], shape=(1, 0), dtype=float64), 'proton': 'PROTON', 'rela': 'RELA', 'ribosome30S': 'ribosome30S', 'ribosome50S': 'ribosome50S', 'ribosomeElongationRate': 17.388824902723737, 'ribosomeElongationRateDict': { 'minimal': 17.388824902723737 [amino_acid/s]}, 'seed': 0, 'spot': 'SPOT', 'synthesis_index': 0, 'synthetase_names': [], 'time_step': 1, 'translation_aa_supply': {'minimal': array([], dtype=float64)}, 'translation_supply': False, 'trna_charging': False, 'uncharged_trna_names': array([], dtype=float64), 'unit_conversion': 0, 'variable_elongation': False, 'water': 'H2O'}
- evolve_state(timestep, states)[source]
Set ribosome elongation rate based on simulation medium environment and elongation rate factor which is used to create single-cell variability in growth rate The maximum number of amino acids that can be elongated in a single timestep is set to 22 intentionally as the minimum number of padding values on the protein sequence matrix is set to 22. If timesteps longer than 1.0s are used, this feature will lead to errors in the effective ribosome elongation rate.
- name = 'ecoli-polypeptide-elongation'
-
topology
{ 'active_ribosome': ('unique', 'active_ribosome'), 'boundary': ('boundary',), 'bulk': ('bulk',), 'bulk_total': ('bulk',), 'environment': ('environment',), 'listeners': ('listeners',), 'polypeptide_elongation': ('process_state', 'polypeptide_elongation'), 'timestep': ('timestep',)}
- ecoli.processes.polypeptide_elongation.REMOVED_FROM_CHARGING = {'L-SELENOCYSTEINE[c]'}
Amino acids to remove from charging when running with
steady_state_trna_charging
- class ecoli.processes.polypeptide_elongation.SteadyStateElongationModel(parameters, process)[source]
Bases:
TranslationSupplyElongationModel
Steady State Charging Model: Requests amino acids based on the Michaelis-Menten competitive inhibition model.
- distribution_from_aa(n_aa, n_trna, limited=False)[source]
Distributes counts of amino acids to tRNAs that are associated with each amino acid. Uses self.process.aa_from_trna mapping to distribute from amino acids to tRNA based on the fraction that each tRNA species makes up for all tRNA species that code for the same amino acid.
- Parameters:
n_aa (ndarray[Any, dtype[int64]]) – counts of each amino acid to distribute to each tRNA
n_trna (ndarray[Any, dtype[int64]]) – counts of each tRNA to determine the distribution
limited (bool) – optional, if True, limits the amino acids distributed to each tRNA to the number of tRNA that are available (n_trna)
- Returns:
Distributed counts for each tRNA
- Return type:
- class ecoli.processes.polypeptide_elongation.TranslationSupplyElongationModel(parameters, process)[source]
Bases:
BaseElongationModel
Translation Supply Model: Requests minimum of 1) upcoming amino acid sequence assuming max ribosome elongation (ie. Base Model) and 2) estimation based on doubling the proteome in one cell cycle (does not use ribosome elongation, computed in Parca).
- ecoli.processes.polypeptide_elongation.calculate_trna_charging(synthetase_conc, uncharged_trna_conc, charged_trna_conc, aa_conc, ribosome_conc, f, params, supply=None, time_limit=1000, limit_v_rib=False, use_disabled_aas=False)[source]
Calculates the steady state value of tRNA based on charging and incorporation through polypeptide elongation. The fraction of charged/uncharged is also used to determine how quickly the ribosome is elongating. All concentrations are given in units of
MICROMOLAR_UNITS
.- Parameters:
synthetase_conc (Unum) – concentration of synthetases associated with each amino acid
uncharged_trna_conc (Unum) – concentration of uncharged tRNA associated with each amino acid
charged_trna_conc (Unum) – concentration of charged tRNA associated with each amino acid
aa_conc (Unum) – concentration of each amino acid
ribosome_conc (Unum) – concentration of active ribosomes
f (Unum) – fraction of each amino acid to be incorporated to total amino acids incorporated
params (dict[str, Any]) – parameters used in charging equations
supply (Callable | None) – function to get the rate of amino acid supply (synthesis and import) based on amino acid concentrations. If None, amino acid concentrations remain constant during charging
time_limit (float) – time limit to reach steady state
limit_v_rib (bool) – if True, v_rib is limited to the number of amino acids that are available
use_disabled_aas (bool) – if False, amino acids in
REMOVED_FROM_CHARGING
are excluded from charging
- Returns:
5-element tuple containing
new_fraction_charged: fraction of total tRNA that is charged for each amino acid species
v_rib: ribosomal elongation rate in units of uM/s
total_synthesis: the total amount of amino acids synthesized during charging in units of MICROMOLAR_UNITS. Will be zeros if supply function is not given.
total_import: the total amount of amino acids imported during charging in units of MICROMOLAR_UNITS. Will be zeros if supply function is not given.
total_export: the total amount of amino acids exported during charging in units of MICROMOLAR_UNITS. Will be zeros if supply function is not given.
- Return type:
- ecoli.processes.polypeptide_elongation.dcdt_jit(t, c, n_aas_masked, n_aas, mask, kS, synthetase_conc, KMaa, KMtf, f, krta, krtf, max_elong_rate, ribosome_conc, limit_v_rib, aa_rate_limit, v_rib_max)
- ecoli.processes.polypeptide_elongation.get_charging_supply_function(supply_in_charging, mechanistic_supply, mechanistic_aa_transport, amino_acid_synthesis, amino_acid_import, amino_acid_export, aa_supply_scaling, counts_to_molar, aa_supply, fwd_enzyme_counts, rev_enzyme_counts, dry_mass, importer_counts, exporter_counts, aa_in_media)[source]
Get a function mapping internal amino acid concentrations to the amount of amino acid supply expected.
- Parameters:
supply_in_charging (bool) – True if using aa_supply_in_charging option
mechanistic_supply (bool) – True if using mechanistic_translation_supply option
mechanistic_aa_transport (bool) – True if using mechanistic_aa_transport option
amino_acid_synthesis (Callable) – function to provide rates of synthesis for amino acids based on the internal state
amino_acid_import (Callable) – function to provide import rates for amino acids based on the internal and external state
amino_acid_export (Callable) – function to provide export rates for amino acids based on the internal state
aa_supply_scaling (Callable) – function to scale the amino acid supply based on the internal state
counts_to_molar (Unum) – conversion factor for counts to molar (
MICROMOLAR_UNITS
)aa_supply (ndarray[Any, dtype[float64]]) – rate of amino acid supply expected
fwd_enzyme_counts (ndarray[Any, dtype[int64]]) – enzyme counts in forward reactions for each amino acid
rev_enzyme_counts (ndarray[Any, dtype[int64]]) – enzyme counts in loss reactions for each amino acid
dry_mass (Unum) – dry mass of the cell with mass units
importer_counts (ndarray[Any, dtype[int64]]) – counts for amino acid importers
exporter_counts (ndarray[Any, dtype[int64]]) – counts for amino acid exporters
aa_in_media (ndarray[Any, dtype[bool_]]) – True for each amino acid that is present in the media
- Returns:
Function that provides the amount of supply (synthesis, import, export) for each amino acid based on the internal state of the cell
- Return type:
Callable[[ndarray[Any, dtype[float64]]], Tuple[Unum, Unum, Unum]] | None
- ecoli.processes.polypeptide_elongation.ppgpp_metabolite_changes(uncharged_trna_conc, charged_trna_conc, ribosome_conc, f, rela_conc, spot_conc, ppgpp_conc, counts_to_molar, v_rib, charging_params, ppgpp_params, time_step, request=False, limits=None, random_state=None)[source]
Calculates the changes in metabolite counts based on ppGpp synthesis and degradation reactions.
- Parameters:
uncharged_trna_conc (Unum) – concentration (
MICROMOLAR_UNITS
) of uncharged tRNA associated with each amino acidcharged_trna_conc (Unum) – concentration (
MICROMOLAR_UNITS
) of charged tRNA associated with each amino acidribosome_conc (Unum) – concentration (
MICROMOLAR_UNITS
) of active ribosomesf (ndarray[Any, dtype[float64]]) – fraction of each amino acid to be incorporated to total amino acids incorporated
rela_conc (Unum) – concentration (
MICROMOLAR_UNITS
) of RelAspot_conc (Unum) – concentration (
MICROMOLAR_UNITS
) of SpoTppgpp_conc (Unum) – concentration (
MICROMOLAR_UNITS
) of ppGppcounts_to_molar (Unum) – conversion factor from counts to molarity (
MICROMOLAR_UNITS
)v_rib (Unum) – rate of amino acid incorporation at the ribosome (units of uM/s)
charging_params (dict[str, Any]) – parameters used in charging equations
ppgpp_params (dict[str, Any]) – parameters used in ppGpp reactions
time_step (float) – length of the current time step
request (bool) – if True, only considers reactant stoichiometry, otherwise considers reactants and products. For use in calculateRequest. GDP appears as both a reactant and product and the request can be off the actual use if not handled in this manner.
limits (ndarray[Any, dtype[float64]] | None) – counts of molecules that are available to prevent negative total counts as a result of delta_metabolites. If None, no limits are placed on molecule changes.
random_state (RandomState | None) – random state for the process
- Returns:
7-element tuple containing
delta_metabolites: the change in counts of each metabolite involved in ppGpp reactions
n_syn_reactions: the number of ppGpp synthesis reactions
n_deg_reactions: the number of ppGpp degradation reactions
v_rela_syn: rate of synthesis from RelA per amino acid tRNA species
v_spot_syn: rate of synthesis from SpoT
v_deg: rate of degradation from SpoT
v_deg_inhibited: rate of degradation from SpoT per amino acid tRNA species
- Return type:
tuple[ndarray[Any, dtype[int64]], int, int, Unum, Unum, Unum, Unum]