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.
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08 Jun 2014
1 citations
Cites background from "Network analysis of intermediary me..."
...3 amount of experimental work needed, and that made these models organism and context specific [8]....
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TL;DR: Sorbitol and glycerol were not used as carbon sources for the fermentation and were considered as effective protective agents to increase cells' resistance ability against environmental changes and maintain key enzymes activities.
Abstract: Corynebacterium glutamicum is widely used in glutamate fermentation. The fermentation feature of the strain varies sometimes. These variations may lead to the reduction in the ability of the strain to resist environmental changes and to synthesize glutamate, resulting in abnormal glutamate fermentations. In the abnormal glutamate fermentations, glutamate accumulation stopped after glucose feeding and the final glutamate concentration was at a lower level (50 to 60 g/L). The r
NAD
+/r
NADH ratio was lower than that in normal batch which was reflected by lower oxidation-reduction potential (ORP) value. The abnormal fermentation performance was improved when glucose was co-fed with sorbitol/glycerol at a weight ratio of 5:1 or adding 10 to 15 g/L of sorbitol/glycerol in the initial medium. Under these conditions, glutamate synthesis continued after substrate(s) feeding and final glutamate concentration was restored to normal levels (≥72 g/L). r
NAD
+/rNADH ratio, ORP, and pyruvate dehydrogenase (PDH), isocitrate dehydrogenase (ICDH), and cytochrome c oxidase (CcO) activities were maintained at higher levels. Sorbitol and glycerol were not used as carbon sources for the fermentation. They were considered as effective protective agents to increase cells' resistance ability against environmental changes and maintain key enzymes activities.
1 citations
Cites background from "Network analysis of intermediary me..."
...In these cases, less NADH was accumulated in vivo and it was desirable for maintaining cellular activities [21]....
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01 Jan 2017
TL;DR: In this paper, a bilevel programming model of Synechocystis sp. PCC 6803 was proposed to study ethanol photosynthetic production under carbon limiting conditions with restricted photon flux.
Abstract: In this work, we propose a genomic scale metabolic network model of the genetically engineered Synechocystis sp. PCC 6803 within a bilevel programming framework to study ethanol photosynthetic production. The model is studied under carbon limiting conditions with restricted photon flux. Maximum biomass and ethanol theoretical productions are obtained using flux balance analysis for the decoupled case. Furthermore, we formulate a bilevel programming problem, reformulated into a mixed integer linear problem (MILP), to study the possibility of coupling cell growth with ethanol production. Models are formulated within an equation-oriented framework in GAMS. Numerical results provide useful insights on ethanol production by this strain within the context of genomic-scale cyanobacterial metabolism.
1 citations
TL;DR: A multi-objective model of cancer metabolism with algorithms depicting approximate Pareto surfaces and incorporating multiple omics datasets is developed and identified a list of metabolic targets essential for cancer cell proliferation and the Warburg effect, and further demonstrated their close association with cancer patient survival.
Abstract: Computational modeling of the genome-wide metabolic network is essential for designing new therapeutics targeting cancer-associated metabolic disorder, which is a hallmark of human malignancies. However, previous studies generally assumed that metabolic fluxes of cancer cells are subjected to the maximization of biomass production, despite the wide existence of trade-offs among multiple metabolic objectives. To address this issue, we developed a multi-objective model of cancer metabolism with algorithms depicting approximate Pareto surfaces and incorporating multiple omics datasets. To validate this approach, we built individualized models for NCI-60 cancer cell lines, and accurately predicted cell growth rates and other biological consequences of metabolic perturbations in these cells. By analyzing the landscape of approximate Pareto surface, we identified a list of metabolic targets essential for cancer cell proliferation and the Warburg effect, and further demonstrated their close association with cancer patient survival. Finally, metabolic targets predicted to be essential for tumor progression were validated by cell-based experiments, confirming this multi-objective modelling method as a novel and effective strategy to identify cancer-associated metabolic vulnerabilities.
1 citations
Cites background from "Network analysis of intermediary me..."
...…of non-malignant cells(Folger et al., 2011; Yizhak et al., 2014b), (3) minimization of total abundance of metabolic enzymes, which is an analogue of the solvent capacity constraint(Shlomi et al., 2011; Vazquez et al., 2010), and (4) minimization of total carbon uptake(Savinell and Palsson, 1992)....
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References
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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