Curation of lipid reactions

After the biomass composition is adjusted, the reactions that are known to differ in the target organism are curated. The SLIME formalism (Split Lipids Into Measurable Entities) describes lipid metabolism, and it requires curated lipid reactions that match the lipids in the biomass reaction.

Order of curation and gap-filling

Curation can also follow gap-filling. Curated lipid reactions change the gap-filling result, so the protocol curates first.

The SLIME formalism

SLIME captures the flexibility of lipid metabolism and accepts measurements of lipid classes and of acyl chains. Each lipid species in the biomass composition is split into pseudometabolites for its backbone and its acyl chains, and these are gathered into the measured entities:

phosphatidylcholine (1–16:0, 2–18:0) → phosphatidylcholine backbone
                                       + C16:0 chain + C18:0 chain
phosphatidylcholine backbone + triglyceride backbone + … → lipid backbone
C16:0 chain + C18:0 chain + C18:1 chain + …             → lipid chain
lipid backbone + lipid chain                            → lipid

Applying the template reactions

The data/reconstruction/ folder of the repository provides template reactions. The protocol reads the templates and applies them with addLipidReactions and addSLIMEreactions. In outline, the calls add the lipid and transport reactions and the SLIME split reactions:

model = addLipidReactions(template, model, modelSce);   % lipid + transport reactions
model = addSLIMEreactions(template, model, modelSce);   % SLIME split reactions

The full script reads three template files (lipidTemplates.txt, lipidTransport.txt and SLIMERtemplates.txt) and reorganises them into a template structure. It first removes the pre-existing matching reactions and SLIME rxn reactions, and the curated set replaces them. A subset of the possible acyl-chain distributions is included, to reduce complexity.

Scaling the acyl chains

After gap-filling, the provided levels of acyl chains and lipid classes turn out to be incompatible, and one of the two must be scaled for a functional model. The protocol assumes that the lipid-class measurements are technically more reliable. Scale the acyl-chain data:

model = scaleLipids(model, 'tails');

After the scaling, the model has the lipid reactions that support a flux towards lipid biosynthesis.

The next page is Gap-filling.