The biomass objective function

Abstract

Flux balance analysis (FBA) is a mathematical approach for analyzing the flow of metabolites through a metabolic network. To computationally predict cell growth using FBA, one has to determine the biomass objective function that describes the rate at which all of the biomass precursors are made in the correct proportions. Here we review fundamental issues associated with its formulation and use to compute optimal growth states.

Figure 1

Calculation of yield and growth rate with a metabolic reconstruction A substrate uptake rate can be utilized with a metabolic reconstruction to calculate yields (e.g., substrate-specific product yield, Y_P/S). In the absence of additional constraints on a network, the relationship between a measured uptake rate and yield is a constant (i.e., directly proportional). With the use of a biomass objective function, complete with growth and non-growth associated maintenance energies (GAM and NGAM), growth rates (μ) can be calculated based on measured substrate uptake rates (q_substrate). Prediction of accurate growth rates often requires several input fluxes to the cell, with typically one or two limiting nutrient fluxes (e.g., glucose and oxygen).

Figure 2

Information used to generate a detailed biomass objective Different types of information are utilized in generating a biomass objective function. The top box contains the necessary information needed to accurately calculate a growth rate and this content determines the bulk of metabolic activity (i.e., flux). Addition of information from the second box enables a broader coverage of metabolism and increases the accuracy of predictions of the growth rate and network essentiality. The addition of information from the bottom box allows for the generation of a ‘core’ biomass objective function that can be used for even greater accuracy of network essentiality prediction.