The Problem of Futile Cycles in Metabolic Flux Modeling: Flux Space Characterization and Practical Approaches to Its Solution

Abstract

A metabolic flux model of an organism can be developed from the genome-scale metabolic network (GEM) for quantitatively understanding and simulating the phenotypes of metabolic systems. For the development of the flux model, the GEM serves as a framework that integrate all of the massive "omics" data derived from systems biology research, comprising (i) gene detection (genomics), (ii) gene expression (transcriptomics), (iii) protein expression and modifications (proteomics), (iv) primary and secondary metabolites production (metabolomics), (v) measurement and estimation reaction rates (fluxes) for a network of reactions that occur in an organism (fluxomics) [1], and (vi) large-scale literature mining (bibliomics) [1][2][3].Due to the advances in the high-throughput "omics" technologies and computer capabilities, there has been an exponential increase in GEMs reconstructed for a wide variety of organisms since the first GEM was built in 1999 [4]. As the GEMs intend to include as large part of the cell metabolism as possible and as much biological information as possible [5], they provide a detailed representation of biological reaction networks and their functional states [6], and can be used as analysis platforms for computational systems approaches such as constraint-based modeling [3], to characterize the flux profiles of the microbial phenotypes. This type of analysis can generate new knowledge that facilitates metabolic engineering of interesting biotechnological processes at the whole-cell level and can overcome the difficulties experienced in reductionist investigative strategies. Therefore, using in silico modeling approaches to develop strains has been considered as a promising area in the field of systems biology.

Reconciliation and evolution ofPenicillium rubensGenome-Scale Metabolic Networks – What about specialised metabolism?

“…77 Nevertheless, without additional constraints, the model seems insensitive to carbon sources, either the high metabolic robustness of the fungus or the presence of extreme pathways such as futile cycles. 78,79 Indeed, with the only required uptake minima (i.e. a source of nitrogen, thiamine, iron, sulphur, oxygen and inorganic phosphate), there is nevertheless a production of Dglyceraldehyde 3-phosphate inducing the synthesis of fructose-6-phosphate which is, then redistributed among the different sugars present in the network.…”

Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data

“…In fact, before reframing the model, the fluxes of some reactions (usually more than 500 mmol/gDW/h) were not reasonable. As discussed by Verwoerd and Mao [30], unreasonable flux is often caused by futile cycles, which may be overcome by minimizing total flux. As depicted in Fig.…”