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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19 Dec 2002TL;DR: A model of citric acid production in the mold Aspergillus niger is used as a useful model for optimization of biochemical systems theory and Maximization of ethanol and carbohydrate production in Saccharomyces cerevisiae.
Abstract: Facility in the targeted manipulation of the genetic and metabolic composition of organisms, combined with unprecedented computational power, is forging a niche for a new subspecialty of biotechnology called metabolic engineering. First published in 2002, this book introduces researchers and advanced students in biology and engineering to methods of optimizing biochemical systems of biotechnological relevance. It examines the development of strategies for manipulating metabolic pathways, demonstrates the need for effective systems models, and discusses their design and analysis, while placing special emphasis on optimization. The authors propose power-law models and methods of biochemical systems theory toward these ends. All concepts are derived from first principles, and the text is richly illustrated with numerous graphs and examples throughout. Special features include: nontechnical and technical introductions to models of biochemical systems; a review of basic methods of model design and analysis; concepts of optimization; and detailed case studies.
190 citations
TL;DR: The results show that genome-scale in silico metabolic models can describe the end point of adaptive evolution a priori and can be used to gain insight into the adaptive evolutionary process for E. coli.
Abstract: Genome-scale in silico metabolic networks of Escherichia coli have been reconstructed. By using a constraint-based in silico model of a reconstructed network, the range of phenotypes exhibited by E. coli under different growth conditions can be computed, and optimal growth phenotypes can be predicted. We hypothesized that the end point of adaptive evolution of E. coli could be accurately described a priori by our in silico model since adaptive evolution should lead to an optimal phenotype. Adaptive evolution of E. coli during prolonged exponential growth was performed with M9 minimal medium supplemented with 2 g of α-ketoglutarate per liter, 2 g of lactate per liter, or 2 g of pyruvate per liter at both 30 and 37°C, which produced seven distinct strains. The growth rates, substrate uptake rates, oxygen uptake rates, by-product secretion patterns, and growth rates on alternative substrates were measured for each strain as a function of evolutionary time. Three major conclusions were drawn from the experimental results. First, adaptive evolution leads to a phenotype characterized by maximized growth rates that may not correspond to the highest biomass yield. Second, metabolic phenotypes resulting from adaptive evolution can be described and predicted computationally. Third, adaptive evolution on a single substrate leads to changes in growth characteristics on other substrates that could signify parallel or opposing growth objectives. Together, the results show that genome-scale in silico metabolic models can describe the end point of adaptive evolution a priori and can be used to gain insight into the adaptive evolutionary process for E. coli.
156 citations
Cites background from "Network analysis of intermediary me..."
...and are available to analyze the properties of metabolic networks (11, 16, 24, 28, 34, 36)....
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TL;DR: It is shown that protein content, DNA content, and protein synthesis per cell are proportional to the cell volume, and that larger cells proliferate slower than smaller cells, and in addition to cell volume and/or biomarkers of protein synthesis may predict response to drugs targeting cancer metabolism.
Abstract: Although cells require nutrients to proliferate, most nutrient exchange rates of the NCI60 panel of cancer cell lines correlate poorly with their proliferation rate. Here, we provide evidence indicating that this inconsistency is rooted in the variability of cell size. We integrate previously reported data characterizing genome copy number variations, gene expression, protein expression and exchange fluxes with our own measurements of cell size and protein content in the NCI60 panel of cell lines. We show that protein content, DNA content, and protein synthesis per cell are proportional to the cell volume, and that larger cells proliferate slower than smaller cells. We estimate the metabolic fluxes of these cell lines and show that their magnitudes are proportional to their protein synthesis rate and, after correcting for cell volume, to their proliferation rate. At the level of gene expression, we observe that genes expressed at higher levels in smaller cells are enriched for genes involved in cell cycle, while genes expressed at higher levels in large cells are enriched for genes expressed in mesenchymal cells. The latter finding is further corroborated by the induction of those same genes following treatment with TGFβ, and the high vimentin but low E-cadherin protein levels in the larger cells. We also find that aromatase inhibitors, statins and mTOR inhibitors preferentially inhibit the in vitro growth of cancer cells with high protein synthesis rates per cell. The NCI60 cell lines display various metabolic activities, and the type of metabolic activity that they possess correlates with their cell volume and protein content. In addition to cell proliferation, cell volume and/or biomarkers of protein synthesis may predict response to drugs targeting cancer metabolism.
152 citations
Cites background from "Network analysis of intermediary me..."
...01/h [24], again supporting the validity of the theoretical line (Equation 1)....
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TL;DR: Metabolic network reconstruction and assessment of metabolic profiles of fecal samples might be used to identify patients with IBD likely to achieve clinical remission following anti-TNF therapy and increase the understanding of the heterogeneity of IBD.
151 citations
TL;DR: The need for accounting for amino acids liberated from peptides is demonstrated in order to accurately estimate pathway fluxes in Chinese hamster ovary cells grown in a complex (hydrolysate containing) medium.
Abstract: Metabolic flux analysis is a useful tool for unraveling relationships between metabolism and cell function. Material balancing can be used to provide estimates of major metabolic pathway fluxes, provided all significant metabolite uptake and production rates are measured. Potential sources of metabolizable material in many serum-free media formulations are low molecular weight digests of biological material such as yeast extracts and plant or animal tissue hydrolysates. These digests typically contain large amounts of peptides, which may be utilized as amino acids. This article demonstrates the need for accounting for amino acids liberated from peptides in order to accurately estimate pathway fluxes in Chinese hamster ovary cells grown in a complex (hydrolysate containing) medium. A simplified model of central carbon metabolism provides the framework for analyzing external metabolite measurements. Redundant measurements are included to ensure the consistency of data and assumed biochemistry by comparing redundant measurements with their predicted values from a minimum data set, and by expressing the degree of agreement using a statistical "consistency index." The consistency index tests whether redundancies are satisfied within expected experimental error. For chemostat steady states of CHO cultures grown in a hydrolysate-supplemented medium, consistent data were obtained only when amino acids liberated from peptides were taken into account.
138 citations
References
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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