dFBApkg¶

dFBAPkg()¶

This class defines and executes dynamic FBA simulations of COBRA models:

from modelseedpy.community import dFBAPkg
dfba = dFBAPkg(model, modelseed_db_path, solver = 'glpk', warnings = True, verbose = False, printing = False, jupyter = False)

model cobra.core.model.Model: the CobraKBase model that will be simulated. The conversion from standard COBRA models to CobraKBase models is facilitated by the cobrakbase package.
modelseed_db_path str: specifies the path to a local version of the ModelSEED Database.
solver str: specifies which linear programmating algorithm will be used to simulate the FBA model. The glpk solver is selected by default since it is free and universally accessible.
warnings, verbose, & printing bool: specifies whether simulation warnings, details and calculations, or results will be printed, respectively. These options are valuable for troubleshooting.
jupyter bool: specifies whether simulation is being conducted in a Jupyter notebook, in which case the printed DataFrames will be expressed with the display() function.

simulate()¶

A cobrakbase model is simulated with the parameterized kinetics data over the defined time and conditions:

dfba.simulate(kinetics_path = None, initial_concentrations_M: dict = {}, total_time = 200, timestep = 20, export_name = None,
              export_directory = None, kinetics_data = {}, temperature = 25, p_h = 7, cellular_dry_mass_fg = 222, cellular_fL = 1,
              figure_title = 'Metabolic perturbation', included_metabolites = [], labeled_plots = True, visualize = True, export = True)

kinetics_path & kinetics_data str & dict: either the path to a JSON file that can be imported or a dictionary argument that provide the kinetics data that will constrain the model in the simulation. The JSON structure in both means of providing the data, and possesses the following nesting: <reaction> -> <source> -> substituted_rate_law + initial_concentrations_M + optional keys (such as metadata). The substituted_rate_law key must contain the mathematically valid rate law expression as a string that can be evaluated through the eval() built-in function of Python, where each metabolite in the rate law is represented by a single letter variable that is defined with a ModelSEED Compound ID in the met_id key. The concentrations of the initial_concentrations_M key must be provided in units of Molar and defined for the rate law variable letters.

{
  "R_3OAS140": {
      "source_1": {
          "substituted_rate_law": "(68.0*A*B)/(50.0*0.34*C+360.0*B+0.34*A+A*B*C)",
          "initial_concentrations_M": {
              "A": 0.0200,
              "C": 0.022,
              "B": 0.0014
          },
          "met_id": {
              "A": "cpd11468",
              "B": "cpd00067",
              "C": "cpd11492"
          }
      }
  },
  "rxn2": {
      "source_1": {
          "substituted_rate_law": "(A*B)/(50.0*0.34*C+3*B+0.34*A+C)",
          "initial_concentrations_M": {
              "A": 0.0200,
              "C": 0.022,
              "B": 0.0012
          },
          "met_id": {
              "A": "cpd11468",
              "B": "cpd00011",
              "C": "cpd11492"
          }
      }
  }
}

The additional keys can provide provenance of the datum source:

{
   "2-Oxogluterate dehydrogenase": {
       "55199": {
           "RateLaw": "Vmax*S/(Km+S)",
           "initial_concentrations_M": {
               "S": 1.6e-08
           },
           "metadata": {
               "Buffer": "[50 mm Mops, 8 mm TCEP, 50 mm Mops, 8 mm TCEP]",
               "Enzyme Variant": "wildtype",
               "KineticMechanismType": "Michaelis-Menten",
               "Organism": "Pisum sativum",
               "Pathway": null,
               "Product": "NADH;H+;Oxidized N-alpha-(benzyloxycarbonyl)-N-omega-(D,L-1,2-dithiolane-3-pentanoyl)-L-lysine",
               "Publication": "Neuburger M, Polidori AM, Pi\u00e8tre E, Faure M, Jourdain A, Bourguignon J, Pucci B, Douce R: Interaction between the lipoamide-containing H-protein and the lipoamide dehydrogenase (L-protein) of the glycine decarboxylase multienzyme system. 1. Biochemical studies., Eur J Biochem 2000 (267) , 2882-9",
               "Temperature": "30.0",
               "annotations": {
                   "ECNumber": "1.8.1.4",
                   "KeggReactionID": null,
                   "PubMedID": 10806385.0,
                   "SabioReactionID": 13969
               },
               "pH": "7.5",
               "reaction_string": " <-> Nicotinamide adenine dinucleotide-reduced + H+"
           },
           "substituted_parameters": {
               "Km": {
                   "comment": "-",
                   "deviat.": "10",
                   "end val.": "-",
                   "species": "N-alpha-(benzyloxycarbonyl)-N-omega-(D,L-1,2-dithiolane-3-pentanoyl)-L-lysine",
                   "start val.": "170.0",
                   "type": "Km",
                   "unit": "\u00b5M"
               },
               "Vmax": {
                   "comment": "-",
                   "deviat.": "7",
                   "end val.": "-",
                   "species": "-",
                   "start val.": "90.0",
                   "type": "Vmax",
                   "unit": "nmol/min"
               }
           },
           "substituted_rate_law": "1.5000000000000002e-09*S/(0.00016999999999999999+S)",
           "variables_molar": {
               "Km": "0.00016999999999999999",
               "Vmax": "1.5000000000000002e-09"
           },
           "variables_name": {
               "Km": "N-alpha-(benzyloxycarbonyl)-N-omega-(D,L-1,2-dithiolane-3-pentanoyl)-L-lysine",
               "S": "N-alpha-(benzyloxycarbonyl)-N-omega-(D,L-1,2-dithiolane-3-pentanoyl)-L-lysine",
               "Vmax": "-"
           }
       }
   }
}

initial_concentrations_M dict: specifies initial concentrations of the simulated metabolites that supplant values from the kinetics data. Every metabolite in this dictionary must be defined in the model, and the concentrations in units of molar must be assigned according to the metabolite’s ModelSEED Compound ID:

{
   "cpd00002":0.0200,
   "cpd00008":0.0014
}

total_time & timestep float: specify the total time and the timstep of the simulation in minutes.
export_name & export_directory str: specify the folder name and directory to which the simulation content will be exported, where None defaults to a unique folder name in the current working directory.
temperature & p_h float: optionally specify the temperature and pH at which the simulation will occur, respective, which allows the most closely matched datum to be parameterized, where multiple datum exist for the same reaction.
cellular_dry_mass_fg & cellular_fL float: The dry mass and volume of the simulated cell, in base units of femto- grams and liters, respectively. These values can be sourced from literature, and the standard values may approximate prokaryotic cells.
figure_title, included_metabolites, & labeled_plots str, list, & bool: specify the title of the simulation Figure, the metabolites that will be plotted in the simulation Figure, and where each plot will be labeled with text to clarify its identity.
visualize & export bool: specifies whether the simulation results will be visually depicted or exported to a specified folder, respectively.

Accessible content¶

A multitude of values are stored within the dFBA object, and can be subsequently used in a workflow. The complete list of content within the dFBA object can be printed through the built-in dir() function in the following example sequence:

# conduct a dFBA simulation
from dfbapy import dFBA
dfba = dFBA(model)
dfba.simulate(reaction_kinetics, None, total_time, timestep)

# evaluate the dFBA simulation contents
print(dir(dfba))

The following list highlights stored content in the dFBA object after a simulation:

model cobra.core.model.Model: The cobrakbase model that is simulated.
concentrations & fluxes pandas.core.frame.DataFrame: Pandas DataFrames that contain the mM concentrations (or changes thereof) for each metabolite and mmol/g_(dw)/hr fluxes for each reaction, respectively.
kinetics_data dict: A dictionary of the kinetics data constrains the model.
timestep_value float: The simulation timestep in minutes.
compound_ids dict: A dictionary of all ModelSEED IDs with their names as values, which is loaded from the ModelSEED Database via the parameterized path.
cell_dry_mass & cell_liters float: The mass and volume of the simulated cell.
changed & unchanged set: The exclusive sets of metabolites whose concentrations either changed or did not change over the simulation, respectively.
constrained OrderedDict: A dictionary with reaction names as the keys and their respective kinetic constraints as the values.
solutions list: A list of the Cobra solutions from each timestep that constitute the columns of the fluxes DataFrame.

dFBApkg¶

dFBAPkg()¶

simulate()¶

Accessible content¶

ModelSEEDpy

Navigation

Related Topics