Network analysis of intermediary metabolism using linear optimization. I. Development of mathematical formalism.
TL;DR: Analysis of metabolic networks using linear optimization theory allows one to quantify and understand the limitations imposed on the cell by its metabolic stoichiometry, and to understand how the flux through each pathway influences the overall behavior of metabolism.
About: This article is published in Journal of Theoretical Biology.The article was published on 1992-02-21 and is currently open access. It has received 255 citations till now.
Citations
More filters
TL;DR: It is demonstrated that the structural constraints of the metabolic network together with data on condition-specific flux phenotypes can be effectively used to dissect metabolic regulation on a system-wide level.
Abstract: Perturbations in environmental and intracellular conditions often lead to changes across all cellular layers, from transcription to metabolism. Regulatory mechanisms are key to mediating these changes to maintain homeostasis and to ensure viability. Since changes in metabolic reaction rates are partly due to perturbations in metabolite concentrations, it is expected that metabolites with large effect on those reaction rates which govern metabolic functionality are tightly regulated. The extent of metabolic regulation has been quantified by the sensitivity of an individual metabolic function to changes in metabolite concentrations, in particular by shadow prices in the constraint-based modeling framework. However, the system-wide characterization of the extent to which metabolite concentrations are regulated in the more realistic scenario of multiple contending tasks remains elusive. Here we examine multi-objective shadow prices for the central carbon metabolism of Escherichia coli whose reaction rates are shaped by several contending metabolic functions. We determine shadow prices for sampled solutions of the Pareto front, which characterizes the space of multi-objective optima, for three contending metabolic functions that provide the best agreement with (13)C-labeling experiments. By analyzing the parts of the Pareto front closest to the experimentally determined flux phenotypes, we show that E. coli operates in the vicinity of an area of the Pareto front which facilitates robust and efficient regulation. In addition, we find significant associations between features of the transcriptional regulatory network and the sensitivity of E. coli's metabolic functionality to changes in metabolite concentrations. We demonstrate that the structural constraints of the metabolic network together with data on condition-specific flux phenotypes can be effectively used to dissect metabolic regulation on a system-wide level.
7 citations
TL;DR: A novel combination of 2 genome-scale methods and data regarding single-nucleotide polymorphism frequency and distribution in the genomes of Tibetans identified reactions that would be critical to hypoxia tolerance in the human heart.
Abstract: Background— Any reduction in myocardial oxygen delivery relative to its demands can impair cardiac contractile performance. Understanding the mitochondrial metabolic response to hypoxia is key to understanding ischemia tolerance in the myocardium. We used a novel combination of 2 genome-scale methods to study key processes underlying human myocardial hypoxia tolerance. In particular, we hypothesized that computational modeling and evolution would identify similar genes as critical to human myocardial hypoxia tolerance.
Methods and Results— We analyzed a reconstruction of the cardiac mitochondrial metabolic network using constraint-based methods, under conditions of simulated hypoxia. We used flux balance analysis, random sampling, and principal component analysis to explore feasible steady-state solutions. Hypoxia blunted maximal ATP (−17%) and heme (−75%) synthesis and shrank the feasible solution space. Tricarboxylic acid and urea cycle fluxes were also reduced in hypoxia, but phospholipid synthesis was increased. Using mathematical optimization methods, we identified reactions that would be critical to hypoxia tolerance in the human heart. We used data regarding single-nucleotide polymorphism frequency and distribution in the genomes of Tibetans (whose ancestors have resided in persistent high-altitude hypoxia for several millennia). Six reactions were identified by both methods as being critical to mitochondrial ATP production in hypoxia: phosphofructokinase, phosphoglucokinase, complex II, complex IV, aconitase, and fumarase.
Conclusions— Mathematical optimization and evolution converged on similar genes as critical to human myocardial hypoxia tolerance. Our approach is unique and completely novel and demonstrates that genome-scale modeling and genomics can be used in tandem to provide new insights into cardiovascular genetics.
7 citations
Additional excerpts
...10 AKGDm (15), ALASm, OCOAT1m† akg(c) 0....
[...]
TL;DR: This article introduces a quantitative approach to the same flux coupling problem named quantitative flux coupling analysis (QFCA), and designs a simple algorithm to efficiently identify these flux coupling equations which scales up to the genome-scale metabolic networks with thousands of reactions and metabolites in an effective way.
Abstract: Flux coupling analysis (FCA) aims to describe the functional dependencies among reactions in a metabolic network. Currently studied coupling relations are qualitative in the sense that they identify pairs of reactions for which the activity of one reaction necessitates the activity of the other one, but without giving any numerical bounds relating the possible activity rates. The potential applications of FCA are heavily investigated, however apart from some trivial cases there is no clue of what bottleneck in the metabolic network causes each dependency. In this article, we introduce a quantitative approach to the same flux coupling problem named quantitative flux coupling analysis (QFCA). It generalizes the current concepts as we show that all the qualitative information provided by FCA is readily available in the quantitative flux coupling equations of QFCA, without the need for any additional analysis. Moreover, we design a simple algorithm to efficiently identify these flux coupling equations which scales up to the genome-scale metabolic networks with thousands of reactions and metabolites in an effective way. Furthermore, this framework enables us to quantify the "strength" of the flux coupling relations. We also provide different biologically meaningful interpretations, including one which gives an intuitive certificate of precisely which metabolites in the network enforce each flux coupling relation. Eventually, we conclude by suggesting the probable application of QFCA to the metabolic gap-filling problem, which we only begin to address here and is left for future research to further investigate.
7 citations
TL;DR: An improved enterocyte-specific model was shown to be a suitable platform to study effects of dietary interventions on enterocytes metabolism, and provided novel and deeper insights into enterocyte metabolism.
Abstract: The small intestine serves as gatekeeper at the interface between body and diet and is thought to play an important role in the etiology of obesity and associated metabolic disorders. A computational modelling approach was used to improve our understanding of the metabolic responses of epithelial cells to different diets. A constraint based, mouse-specific enterocyte metabolic model (named mmu_ENT717) was constructed to describe the impact of four fully characterized semi-purified diets, that differed in lipid and carbohydrate composition, on uptake, metabolism, as well as secretion of carbohydrates and lipids. Our simulation results predicted luminal sodium as a limiting factor for active glucose absorption; necessity of apical localization of glucose transporter GLUT2 for absorption of all glucose in the postprandial state; potential for gluconeogenesis in enterocytes; and the requirement of oxygen for the formation of endogenous cholesterol needed for chylomicron formation under luminal cholesterol-free conditions. In addition, for a number of enzymopathies related to intestinal carbohydrate and lipid metabolism it was found that their effects might be ameliorated through dietary interventions. In conclusion, our improved enterocyte-specific model was shown to be a suitable platform to study effects of dietary interventions on enterocyte metabolism, and provided novel and deeper insights into enterocyte metabolism.
7 citations
References
More filters
Book•
01 Jan 1984
TL;DR: Strodiot and Zentralblatt as discussed by the authors introduced the concept of unconstrained optimization, which is a generalization of linear programming, and showed that it is possible to obtain convergence properties for both standard and accelerated steepest descent methods.
Abstract: This new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve a problem. This was a major theme of the first edition of this book and the fourth edition expands and further illustrates this relationship. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. It is possible to go directly into Parts II and III omitting Part I, and, in fact, the book has been used in this way in many universities.New to this edition is a chapter devoted to Conic Linear Programming, a powerful generalization of Linear Programming. Indeed, many conic structures are possible and useful in a variety of applications. It must be recognized, however, that conic linear programming is an advanced topic, requiring special study. Another important topic is an accelerated steepest descent method that exhibits superior convergence properties, and for this reason, has become quite popular. The proof of the convergence property for both standard and accelerated steepest descent methods are presented in Chapter 8. As in previous editions, end-of-chapter exercises appear for all chapters.From the reviews of the Third Edition: this very well-written book is a classic textbook in Optimization. It should be present in the bookcase of each student, researcher, and specialist from the host of disciplines from which practical optimization applications are drawn. (Jean-Jacques Strodiot, Zentralblatt MATH, Vol. 1207, 2011)
4,908 citations
TL;DR: Analysis of oxidative pathways of glutamine and glutamate showed that extramitochondrial malate is oxidized almost quantitatively to pyruvate + CO2 by NAD(P)+-linked malic enzyme, present in the mitochondria of all tumors tested, but absent in heart, liver, and kidney mitochondria.
374 citations