Flux-based hierarchical organization of Escherichia coli’s metabolic network

Abstract

<jats:title>Abstract</jats:title><jats:p>Biological networks across scales exhibit hierarchical organization that may constrain network function. Yet, understanding how these hierarchies arise due to the operational constraint of the networks and whether they impose limits to molecular phenotypes remains elusive. Here we show that metabolic networks include a hierarchy of reactions based on a natural flux ordering that holds for every steady state. We find that the hierarchy of reactions is reflected in experimental measurements of transcript, protein and flux levels of <jats:italic>Escherichia coli</jats:italic> under various growth conditions as well as in the catalytic rate constants of the corresponding enzymes. Our findings point at resource partitioning and a fine-tuning of enzyme levels in <jats:italic>E. coli</jats:italic> to respect the constraints imposed by the network structure at steady state. Since reactions in upper layers of the hierarchy impose an upper bound on the flux of the reactions downstream, the hierarchical organization of metabolism due to the flux ordering has direct applications in metabolic engineering.</jats:p>

Transcriptional Mechanisms of Thermal Acclimation in Prochlorococcus

“…Finally, we normalized count data using the default DESeq2 v.3.15 count normalization workflow ( 80 ). All analyses were assisted with customized Python code ( 87 ) available at https://github.com/Robaina/prochlorococcus ( 88 ).…”

The hidden simplicity of metabolic networks is revealed by multireaction dependencies

“…In parallel with the detailed modeling of metabolic networks for specific biological systems, principles underlying the organization of metabolic reactions in metabolic networks that support steady states have also been determined. For instance, metabolic networks have been shown to exhibit bow tie structure, where few metabolites act as intermediates between a large number of precursors (i.e., nutrients) transformed in multiple building blocks of biomass ( 5 ); the bow tie structure is, in turn, reflected in the power law distribution of the number of reactions in which metabolites participate ( 6 ), in the minimal path between precursors and biomass components ( 7 ), and in the hierarchical ordering of steady-state reaction fluxes ( 8 , 9 ). In addition, pairs of metabolic reactions have been grouped into different classes based on the relationships that their fluxes exhibit in every steady state that the network supports ( 10 , 11 ), providing means to study the modular organization of metabolic networks ( 12 , 13 ) under operational constraints.…”