|Step 2: Verify & Edit Pathway Model|
|1. Check relative fluxes for all reactions in the SBtab file.|
|2. Check KEGG IDs for all reactants in the model.|
|3. Check and/or edit bounds on metabolite concentrations.|
|Using eQuilibrator to Calculate the MDF|
eQuilibrator can be used to calculate the Max-min Driving Force (MDF) for your pathway of interest. This process has two steps.
It is important to fix the concentrations of cofactors like ATP, CoA and NADH because these concentrations are homeostatically maintained by host organisms. If you do not fix these concentrations to reasonable, physiologically-relevant values, the MDF optimization will choose the concentration that makes your pathway the most thermodynamically favorable. In glycolysis, for example, this would set the ATP concentration as low as allowed (e.g. 1 micromolar), making ATP synthesis and glycolysis as a whole appear much more favorable than it really is or could be. In this case the problem is obvious: maintaining a very low ATP concentration is good for producing ATP from ADP, but catastrophic for the cell because ATP-dependent reactions will operate slowly and with very little driving force.
By default, eQuilibrator uses cofactor concentrations chosen in Noor et al., PloS Comp. Bio 2014. If you wish to use different values, you can edit the SBtab file directly in Excel. You can also edit the reaction ΔrG'° values, which are recorded in the SBtab file as equilibrium constants (Keq). This may be useful if your pathway contains a reaction whose ΔrG'° eQuilibrator cannot calculate (for example iron redox reactions are problematic for eQuilibrator). When calculating the MDF, eQuilibrator verifies that the ΔrG'° are consistent with the first law of thermodynamics, i.e. that they could arise from compound formation energies ΔfG'° that are internally consistant with the stoichiometry of your pathway.
|Overview of MDF Pathway Analysis|
The Max-min Driving Force (MDF) framework was developed in Noor et al., PloS Comp. Bio 2014 and is designed to help metabolic engineers select between alternative pathways for achieving the same or similar metabolic goals. Typically, metabolic engineers must express several heterologous enzymes in a non-native host in order to establish a pathway and often choose the pathway in the absence of good data on the kinetics of pathway enzymes. In this context, traditional metabolic control analysis (MCA) is difficult to apply for two reasons:
This approach has several practical over advantages over MCA for the purposes of metabolic engineering. First, enzyme kinetic properties are laborious to measure and differ between organisms and isozymes, but no kinetic data is required to calculate the MDF. Second, as the MDF accounts for pH, ionic strength and allowed concentration ranges, it is simple to model the effect of these parameters on the MDF. Finally, as it can be difficult to control the exact expression level of enzymes within cells, the MDF helps identify pathways that are less sensitive to the levels of their constituent enzymes.