Constrained Allocation Flux Balance Analysis

TL;DR

Constrained Allocation Flux Balance Analysis (CAFBA) is a novel method that integrates proteomic constraints into metabolic modeling, accurately predicting bacterial growth behaviors and metabolite excretion with minimal parameters.

Contribution

This paper introduces CAFBA, a new approach that combines mass balance and proteomic constraints to improve metabolic modeling of bacteria.

Findings

CAFBA predicts a shift from respiratory to fermentative states with increasing growth rate.

It accurately estimates acetate excretion and growth yield using only three empirical parameters.

CAFBA bridges regulation and metabolism through proteome allocation constraints.

Abstract

New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an "ensemble averaging" procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws.