Identification of flux trade-offs in metabolic networks

Seirana Hashemi,Zoran Nikoloski,Zahra Razaghi-Moghadam

doi:10.1038/s41598-021-03224-9

Seirana Hashemi, Zoran Nikoloski + Show 1 more

Open Access

https://doi.org/10.1038/s41598-021-03224-9

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Abstract

Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. Yet, trade-offs between fluxes of biochemical reactions in a metabolic network have not been formally studied. Here, we introduce the concept of absolute flux trade-offs and devise a constraint-based approach, termed FluTO, to identify and enumerate flux trade-offs in a given genome-scale metabolic network. By employing the metabolic networks of Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the flux trade-offs are specific to carbon sources provided but that reactions involved in the cofactor and prosthetic group biosynthesis are present in trade-offs across all carbon sources supporting growth. We also show that absolute flux trade-offs depend on the biomass reaction used to model the growth of Arabidopsis thaliana under different carbon and nitrogen conditions. The identified flux trade-offs reflect the tight coupling between nitrogen, carbon, and sulphur metabolisms in leaves of C3 plants. Altogether, FluTO provides the means to explore the space of alternative metabolic routes reflecting the constraints imposed by inherent flux trade-offs in large-scale metabolic networks.

Highlights

Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism
The trade-off between the rate and yield of adenosine triphosphate (ATP) production has been used to explain why evolution may work to select a less efficient pathway when cells compete for a shared resource[2]
The Y-model indicates that the traits can be considered to be in trade-off if: (i) they show some level of phenotypic plasticity, i.e., different expressions under different environments, and (ii) if there exists a non-negative linear combination that corresponds to a resource

Summary

Introduction

Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. The growth rate-yield trade-off has been studied by using different modelling approaches, including: (i) elementary flux modes, combined with enzyme-cost e stimations[3], (ii) fine-grained genome-scale models of metabolism and gene expression[4], and (iii) constraint-allocation flux balance analysis[5], combining mass balance and proteomic constraints. A recent study has uncovered a universal trade-off between growth rate and adaptability in E. coli, Bacillus subtilis, and Saccharomyces cerevisiae[7] These examples indicate that trade-offs between multiple traits often arise due to the optimization of multiple objectives; these traits may be recovered by considering the extreme points of a convex hull in a principal component space containing observed phenotypes[1]. Since metabolites participate in multiple reactions and enzymes can catalyse several reactions[11], the fluxes in a metabolic network may be shaped by trade-offs that arise due to competition for these molecular resources. There is no constraint-based approach that utilizes constraints from a given metabolic network structure with additional constraints on nutrient uptake to determine trade-offs between metabolic fluxes

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