Gsmm Builder

Overview

The gsmm-builder skill constructs or loads genome-scale metabolic models (GSMMs) in the COBRApy framework. It is the entry point for every metabolic flux analysis pipeline. Output is a validated COBRApy Model object serialized to a JSON file ready for downstream FBA and flux analysis.

GSMMs encode every known metabolic reaction in an organism as a stoichiometric matrix. Constraints (reaction bounds, medium composition, objective function) turn the model into a solvable linear program.

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Workflow

Step 1, Decide: Load Existing or Build from Scratch

Option A: Load a curated BIGG model

import cobra
import cobra.io

# Load E. coli iJO1366 from a local SBML file
model = cobra.io.read_sbml_model("iJO1366.xml")

# Or load from a pre-downloaded JSON file
model = cobra.io.load_json_model("iJO1366.json")

print(f"Loaded {model.id}: {len(model.reactions)} reactions, "
      f"{len(model.metabolites)} metabolites, {len(model.genes)} genes")

Key BIGG model IDs:

• iJO1366, E. coli K-12 MG1655 (2583 reactions)
• Recon3D, Homo sapiens (13543 reactions)
• iMM904, S. cerevisiae (1577 reactions)
• iNJ661, M. tuberculosis (1049 reactions)

Option B: Build a minimal model from scratch

from cobra import Model, Metabolite, Reaction

model = Model("toy_glycolysis")

# Define metabolites with compartments and formula
glc_e = Metabolite("glc__D_e", formula="C6H12O6", name="D-Glucose",
                   compartment="e")
glc_c = Metabolite("glc__D_c", formula="C6H12O6", name="D-Glucose",
                   compartment="c")
atp_c = Metabolite("atp_c",  formula="C10H12N5O13P3", name="ATP",
                   compartment="c")
biomass = Metabolite("biomass", formula="", name="Biomass", compartment="c")

# Build reactions
ex_glc = Reaction("EX_glc__D_e")
ex_glc.lower_bound = -10.0  # uptake (negative = import)
ex_glc.upper_bound = 0.0
ex_glc.add_metabolites({glc_e: 1.0})