Optimal Fluxes, Reaction Replaceability, and Response to Enzymopathies in the Human Red Blood Cell

Martino, Andrea De; Granata, Donatella; Marinari, Enzo; Martelli, Carlotta; Kerrebroeck, Valery Van

doi:10.1155/2010/415148

Cited by 7 publications

(29 citation statements)

References 34 publications

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“…This definition of essentiality is identical to the one used in early work on constraint-based models 26 as well as more recently in ref. 27 , but differs from non-standard topological approaches 6 and the flux surplus rather than flux balance model 28 .…”

Section: Resultsmentioning

confidence: 99%

An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models

Chindelevitch

Trigg²,

Regev

et al. 2014

Nat Commun

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Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations.

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Section: Resultsmentioning

confidence: 99%

An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models

Chindelevitch

Trigg²,

Regev

et al. 2014

Nat Commun

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show abstract

“…• according to [20], the net flux of all reactions is in the forward direction, except R5PI (which is found to be operating bidirectionally), and PGI and ApK (which are found to have a net backward flux).…”

Section: Exploring the Gibbs Energy Landscape Of The Hrbc Metabolic Nmentioning

confidence: 95%

“…As applications, we focus on two metabolic networks of rather different complexity. First, we shall obtain a detailed reconstruction of the Gibbs energy landscape underlying metabolic activity in the human red blood cell (hRBC) starting from the flux maps obtained in [19] , [20] . Then, the metabolic network of Escherichia coli , iAF1260 [21] , will be analyzed to eliminate infeasible cycles from randomly generated flux configurations.…”

Section: Introductionmentioning

confidence: 99%

A Scalable Algorithm to Explore the Gibbs Energy Landscape of Genome-Scale Metabolic Networks

et al. 2012

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The integration of various types of genomic data into predictive models of biological networks is one of the main challenges currently faced by computational biology. Constraint-based models in particular play a key role in the attempt to obtain a quantitative understanding of cellular metabolism at genome scale. In essence, their goal is to frame the metabolic capabilities of an organism based on minimal assumptions that describe the steady states of the underlying reaction network via suitable stoichiometric constraints, specifically mass balance and energy balance (i.e. thermodynamic feasibility). The implementation of these requirements to generate viable configurations of reaction fluxes and/or to test given flux profiles for thermodynamic feasibility can however prove to be computationally intensive. We propose here a fast and scalable stoichiometry-based method to explore the Gibbs energy landscape of a biochemical network at steady state. The method is applied to the problem of reconstructing the Gibbs energy landscape underlying metabolic activity in the human red blood cell, and to that of identifying and removing thermodynamically infeasible reaction cycles in the Escherichia coli metabolic network (iAF1260). In the former case, we produce consistent predictions for chemical potentials (or log-concentrations) of intracellular metabolites; in the latter, we identify a restricted set of loops (23 in total) in the periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility in a large sample ( ) of flux configurations generated randomly and compatibly with the prior information available on reaction reversibility.

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“…Work performed along these lines for the bacterium Escherichia coli [40,41] has shown that environment selection restricts the feasible states according to (42) to flux configurations that both reproduce well the available empirical evidence on E.coli's metabolic fluxes and guarantee that the correct physiological task (in that case, growth or biomass production) is carried out by the cell without the need of additional ad hoc functional constraints. We want to add here further evidence supporting the relevance of Von Neumann's observations in the context of cell metabolism.…”

Section: Application To Cellular Metabolismmentioning

confidence: 99%

“…dissimilar) the two configurations are. Likewise, we define the overlap between the vectors c that correspond to the production profiles in each solution of (42). The distributions of these overlaps are displayed in Figure 5.…”

Section: Application To Cellular Metabolismmentioning

confidence: 99%

Von Neumann’s growth model: Statistical mechanics and biological applications

Martino

Marinari

Romualdi

2012

Eur. Phys. J. Spec. Top.

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We review recent work on the statistical mechanics of Von Neumann's growth model and discuss its application to cellular metabolic networks. In this context, we present a detailed analysis of the physiological scenario underlying optimalityà la Von Neumann in the metabolism of the bacterium E. coli, showing that optimal solutions are characterized by a considerable microscopic flexibility accompanied by a robust emergent picture for the key physiological functions. This suggests that the ideas behind optimal economic growth in Von Neumann's model can be helpful in uncovering functional organization principles of cell energetics. arXiv:1205.2769v1 [cond-mat.dis-nn]

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Optimal Fluxes, Reaction Replaceability, and Response to Enzymopathies in the Human Red Blood Cell

Cited by 7 publications

References 34 publications

An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models

An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models

A Scalable Algorithm to Explore the Gibbs Energy Landscape of Genome-Scale Metabolic Networks

Von Neumann’s growth model: Statistical mechanics and biological applications

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