Gap-filling#
Homology-based draft models tend to have many gaps: missing reactions that break a pathway needed to produce biomass macromolecules. The pathway is likely functional in the template, but getBlast and getModelFromHomology cannot always find a homolog for every gene, leaving the pathway incomplete. Gap-filling identifies and resolves these gaps so the draft becomes a functional model.
RAVEN's fillGaps adds the smallest set of reactions from the template models needed to support flux through the draft.
Forcing biomass production#
Gap-filling is set up to support growth on glycerol as carbon source with biomass production as objective. The model is forced to carry a small non-zero biomass flux, and glycerol uptake is raised so the fluxes stay above the MILP solver tolerance:
model = setParam(model, 'obj', 'r_4041', 1);
model = setParam(model, 'lb', 'r_4041', 0.01); % force biomass production
model = setParam(model, 'lb', 'r_1808', -10); % allow glycerol uptake
Preparing the template models#
Gaps should be resolved with enzymatic and transport reactions, and not with new exchange reactions. New exchange reactions could, for example, introduce other carbon sources. All exchange reactions, and the biomass pseudoreactions, are therefore removed from the template copies used as the reaction source. Reactions already shared between the two templates are also dropped to shrink the MILP search space:
modelSce2 = removeReactions(modelSce, getExchangeRxns(modelSce, 'both'), true, true, true);
modelRhto2 = removeReactions(modelRhto, getExchangeRxns(modelRhto, 'both'), true, true, true);
rxns = intersect(modelSce2.rxns, modelRhto2.rxns);
modelRhto2 = removeReactions(modelRhto2, rxns);
Running fillGaps#
[~, ~, addedRxns, model] = fillGaps(model, {modelSce2, modelRhto2}, false, true);
Setting allowNetProduction to false prevents additional exchange reactions, and useModelConstraints to true ensures that the glycerol-to-biomass flux is gap-filled. Verify that the model grows, then scale the lipids and restore the carbon-uptake bounds:
sol = solveLP(model, 1);
printFluxes(model, sol.x);
model = scaleLipids(model, 'tails');
model = setParam(model, 'lb', 'r_1808', -1); % carbon source back to 1 mmol/gDCW/h
model = setParam(model, 'lb', 'r_4041', 0);
model = deleteUnusedGenes(model);
After gap-filling, the model produces all the macromolecules that constitute H. polymorpha biomass.
Semi-automatic gap analysis#
RAVEN has functions to find gaps: canExchange (net synthesis or consumption of metabolites, 'produce' or 'consume'), checkProduction (smallest set of metabolites needing net synthesis), getAllSubGraphs (disconnected subnetworks) and haveFlux (reactions that can or cannot carry flux). Absence of a biomass macromolecule from canExchange(model, 'produce') indicates a gap.