HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

J. Biol. Chem., Vol. 281, Issue 12, 8024-8033, March 24, 2006

This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: 281/12/8024    most recent M510016200v2 M510016200v1 Submit a Letter to Editor Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Fong, S. S. Articles by Sauer, U. Search for Related Content PubMed PubMed Citation Articles by Fong, S. S. Articles by Sauer, U. Social Bookmarking                      What's this?

Latent Pathway Activation and Increased Pathway Capacity Enable Escherichia coli Adaptation to Loss of Key Metabolic Enzymes^*

Stephen S. Fong¹², Annik Nanchen¹, Bernhard O. Palsson^¶, and Uwe Sauer

From the Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland, the ^¶Department of Bioengineering, University of California, San Diego, La Jolla, California 92093-0412, and the Department of Chemical and Life Science Engineering, Virginia Commonwealth University, P.O. Box 843028, Richmond, Virginia 28284-3028

The ability of biological systems to adapt to genetic and environmental perturbations is a fundamental but poorly understood process at the molecular level. By quantifying metabolic fluxes and global mRNA abundance, we investigated the genetic and metabolic mechanisms that underlie adaptive evolution of four metabolic gene deletion mutants of Escherichia coli (pgi, ppc, pta, and tpi) in parallel evolution experiments of each mutant. The initial response to the gene deletions was flux rerouting through local bypass reactions or normally latent pathways. The principal effect of evolution was improved capacity of already active pathways, whereas new flux distributions were not observed. Combinatorial changes in capacity and pathway activation, however, led to different intracellular flux states that enabled evolution in three of the four parallel cases tested. The molecular bases of the evolved phenotypes were then elucidated by global mRNA transcript analyses. Activation of latent pathways and flux changes in the tricarboxylic acid cycle were found to correlate well with molecular changes at the transcriptional level. Flux alterations in other central metabolic pathways, in contrast, were apparently not connected to changes in the transcriptional network. These results give new insight into the dynamics of the evolutionary process by demonstrating the flexibility of the metabolic network of E. coli to compensate for genetic perturbations and the utility of combining multiple high throughput data sets to differentiate between causal and noncausal mechanistic changes.

Received for publication, September 12, 2005 , and in revised form, November 28, 2005.

^* This work was supported by a scholarship from the Ecole Polytechnique Fédérale de Lausanne (to A. N.). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

The on-line version of this article (available at http://www.jbc.org) contains supplemental Tables 1–3.

¹ These two authors contributed equally to this work.

² To whom correspondence should be addressed: Dept. of Chemical and Life Science Engineering, Virginia Commonwealth University, P.O. Box 843028, Richmond, VA 23284-3028. Tel.: 804-827-7038; Fax: 804-828-3846; E-mail: ssfong{at}vcu.edu.

CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?

This article has been cited by other articles:

				N. E. Lewis, B.-K. Cho, E. M. Knight, and B. O. Palsson Gene Expression Profiling and the Use of Genome-Scale In Silico Models of Escherichia coli for Analysis: Providing Context for Content J. Bacteriol., June 1, 2009; 191(11): 3437 - 3444. [Full Text] [PDF]

				J. F. Moxley, M. C. Jewett, M. R. Antoniewicz, S. G. Villas-Boas, H. Alper, R. T. Wheeler, L. Tong, A. G. Hinnebusch, T. Ideker, J. Nielsen, et al. From the Cover: Complex Systems: From Chemistry to Systems Biology Special Feature: Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p PNAS, April 21, 2009; 106(16): 6477 - 6482. [Abstract] [Full Text] [PDF]

				E. Grafahrend-Belau, F. Schreiber, D. Koschutzki, and B. H. Junker Flux Balance Analysis of Barley Seeds: A Computational Approach to Study Systemic Properties of Central Metabolism Plant Physiology, January 1, 2009; 149(1): 585 - 598. [Abstract] [Full Text] [PDF]

				V. A. Portnoy, M. J. Herrgard, and B. O. Palsson Aerobic Fermentation of D-Glucose by an Evolved Cytochrome Oxidase-Deficient Escherichia coli Strain Appl. Envir. Microbiol., December 15, 2008; 74(24): 7561 - 7569. [Abstract] [Full Text] [PDF]

				D. Dikicioglu, P. Pir, Z. I. Onsan, K. O. Ulgen, B. Kirdar, and S. G. Oliver Integration of Metabolic Modeling and Phenotypic Data in Evaluation and Improvement of Ethanol Production Using Respiration-Deficient Mutants of Saccharomyces cerevisiae Appl. Envir. Microbiol., September 15, 2008; 74(18): 5809 - 5816. [Abstract] [Full Text] [PDF]

				A. Nanchen, A. Schicker, O. Revelles, and U. Sauer Cyclic AMP-Dependent Catabolite Repression Is the Dominant Control Mechanism of Metabolic Fluxes under Glucose Limitation in Escherichia coli J. Bacteriol., April 1, 2008; 190(7): 2323 - 2330. [Abstract] [Full Text] [PDF]

				Q. Hua, A. R. Joyce, B. O. Palsson, and S. S. Fong Metabolic Characterization of Escherichia coli Strains Adapted to Growth on Lactate Appl. Envir. Microbiol., July 15, 2007; 73(14): 4639 - 4647. [Abstract] [Full Text] [PDF]

				N. Ishii, K. Nakahigashi, T. Baba, M. Robert, T. Soga, A. Kanai, T. Hirasawa, M. Naba, K. Hirai, A. Hoque, et al. Multiple High-Throughput Analyses Monitor the Response of E. coli to Perturbations Science, April 27, 2007; 316(5824): 593 - 597. [Abstract] [Full Text] [PDF]