ThermOptFlux Tutorial

ThermOptFlux

ThermOptFlux (TOF) is a post-processing algorithm designed to eliminate thermodynamically infeasible loops from flux distributions generated by any flux analysis methods like, flux balance analysis (FBA) or flux sampling methods. These loops can arise due to the presence of TICs, even in thermodynamically consistent models. TOF ensures that the final flux distribution is thermodynamically feasible, providing more accurate and biologically meaningful predictions. This is essential for various applications, such as predicting metabolic fluxes under different conditions, simulating growth phenotypes, and designing metabolic engineering strategies. TOF takes a flux distribution and the corresponding TICs (identified by TOE) as inputs. It outputs a corrected flux distribution that is free of thermodynamically infeasible loops, ensuring consistency with the laws of thermodynamics. This tutorial implies TOF on a flux distribution obtained from flux balance analysis (FBA).

Reading the COBRA model (The model should have the following fields: S, lb, ub, rxns)

fileName = 'iAF1260.mat';

model = readCbModel(fileName);

Each model.subSystems{x} is a character array, and this format is retained.

Obtaining the TICs for the given input model

[TICs,Direction,TIC_Rxns,modModel] = ThermOptEnumMILP(model);

Note that all the flux analysis methods have to be implied on the modModel rather than model. modModel is similar to that of the model except that the reverse irreversible reactions (ub <=0) are updated to forward irreversible reactions.

% FBA on the model

sol = optimizeCbModel(modModel);

flux = sol.v;

[Looplessflux] = ThermOptFlux(modModel,flux,TICs,Direction);

The obtained variable Looplessflux is flux distribution without any loops in it.