Literature DB >> 24686285

Metabolic flux analysis of Escherichia coli knockouts: lessons from the Keio collection and future outlook.

Christopher P Long1, Maciek R Antoniewicz2.   

Abstract

Cellular metabolic and regulatory systems are of fundamental interest to biologists and engineers. Incomplete understanding of these complex systems remains an obstacle to progress in biotechnology and metabolic engineering. An established method for obtaining new information on network structure, regulation and dynamics is to study the cellular system following a perturbation such as a genetic knockout. The Keio collection of all viable Escherichia coli single-gene knockouts is facilitating a systematic investigation of the regulation and metabolism of E. coli. Of all omics measurements available, the metabolic flux profile (the fluxome) provides the most direct and relevant representation of the cellular phenotype. Recent advances in (13)C-metabolic flux analysis are now permitting highly precise and accurate flux measurements for investigating cellular systems and guiding metabolic engineering efforts.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 24686285      PMCID: PMC5842030          DOI: 10.1016/j.copbio.2014.02.006

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  68 in total

1.  Metabolic flux response to phosphoglucose isomerase knock-out in Escherichia coli and impact of overexpression of the soluble transhydrogenase UdhA.

Authors:  F Canonaco; T A Hess; S Heri; T Wang; T Szyperski; U Sauer
Journal:  FEMS Microbiol Lett       Date:  2001-11-13       Impact factor: 2.742

2.  Prediction of dynamic behavior of mutant strains from limited wild-type data.

Authors:  Hyun-Seob Song; Doraiswami Ramkrishna
Journal:  Metab Eng       Date:  2012-03       Impact factor: 9.783

3.  Effect of iclR and arcA deletions on physiology and metabolic fluxes in Escherichia coli BL21 (DE3).

Authors:  Hendrik Waegeman; Jo Maertens; Joeri Beauprez; Marjan De Mey; Wim Soetaert
Journal:  Biotechnol Lett       Date:  2011-10-19       Impact factor: 2.461

4.  Response of the central metabolism of Escherichia coli to modified expression of the gene encoding the glucose-6-phosphate dehydrogenase.

Authors:  Cécile Nicolas; Patrick Kiefer; Fabien Letisse; Jens Krömer; Stéphane Massou; Philippe Soucaille; Christoph Wittmann; Nic D Lindley; Jean-Charles Portais
Journal:  FEBS Lett       Date:  2007-07-03       Impact factor: 4.124

Review 5.  Parallel labeling experiments and metabolic flux analysis: Past, present and future methodologies.

Authors:  Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2012-12-14       Impact factor: 9.783

6.  Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS.

Authors:  Eliane Fischer; Uwe Sauer
Journal:  Eur J Biochem       Date:  2003-03

7.  Modeling and simulation of the main metabolism in Escherichia coli and its several single-gene knockout mutants with experimental verification.

Authors:  Tuty Asmawaty Abdul Kadir; Ahmad A Mannan; Andrzej M Kierzek; Johnjoe McFadden; Kazuyuki Shimizu
Journal:  Microb Cell Fact       Date:  2010-11-19       Impact factor: 5.328

8.  Responses of the central metabolism in Escherichia coli to phosphoglucose isomerase and glucose-6-phosphate dehydrogenase knockouts.

Authors:  Qiang Hua; Chen Yang; Tomoya Baba; Hirotada Mori; Kazuyuki Shimizu
Journal:  J Bacteriol       Date:  2003-12       Impact factor: 3.490

9.  A genome-scale computational study of the interplay between transcriptional regulation and metabolism.

Authors:  Tomer Shlomi; Yariv Eisenberg; Roded Sharan; Eytan Ruppin
Journal:  Mol Syst Biol       Date:  2007-04-17       Impact factor: 11.429

10.  Systematic phenome analysis of Escherichia coli multiple-knockout mutants reveals hidden reactions in central carbon metabolism.

Authors:  Kenji Nakahigashi; Yoshihiro Toya; Nobuyoshi Ishii; Tomoyoshi Soga; Miki Hasegawa; Hisami Watanabe; Yuki Takai; Masayuki Honma; Hirotada Mori; Masaru Tomita
Journal:  Mol Syst Biol       Date:  2009-09-15       Impact factor: 11.429

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  22 in total

1.  Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring.

Authors:  Christopher P Long; Jacqueline E Gonzalez; Adam M Feist; Bernhard O Palsson; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-09-23       Impact factor: 9.783

Review 2.  Methods and advances in metabolic flux analysis: a mini-review.

Authors:  Maciek R Antoniewicz
Journal:  J Ind Microbiol Biotechnol       Date:  2015-01-23       Impact factor: 3.346

3.  Complete genome sequence, metabolic model construction and phenotypic characterization of Geobacillus LC300, an extremely thermophilic, fast growing, xylose-utilizing bacterium.

Authors:  Lauren T Cordova; Christopher P Long; Keerthi P Venkataramanan; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2015-09-21       Impact factor: 9.783

4.  Genome-Scale Fluxome of Synechococcus elongatus UTEX 2973 Using Transient 13C-Labeling Data.

Authors:  John I Hendry; Saratram Gopalakrishnan; Justin Ungerer; Himadri B Pakrasi; Yinjie J Tang; Costas D Maranas
Journal:  Plant Physiol       Date:  2018-12-14       Impact factor: 8.340

5.  Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis.

Authors:  Jacqueline E Gonzalez; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-11-11       Impact factor: 9.783

6.  Dissecting the genetic and metabolic mechanisms of adaptation to the knockout of a major metabolic enzyme in Escherichia coli.

Authors:  Christopher P Long; Jacqueline E Gonzalez; Adam M Feist; Bernhard O Palsson; Maciek R Antoniewicz
Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-18       Impact factor: 11.205

7.  13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252.

Authors:  Lauren T Cordova; Robert M Cipolla; Adti Swarup; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-10-14       Impact factor: 9.783

8.  Metabolism of the fast-growing bacterium Vibrio natriegens elucidated by 13C metabolic flux analysis.

Authors:  Christopher P Long; Jacqueline E Gonzalez; Robert M Cipolla; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-10-16       Impact factor: 9.783

9.  Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli.

Authors:  Scott B Crown; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2015-01-14       Impact factor: 9.783

10.  Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system.

Authors:  Scott B Crown; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-06-04       Impact factor: 9.783

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