Literature DB >> 11991183

Metabolic flux analysis using mass spectrometry.

C Wittmann1.   

Abstract

Detailed knowledge on carbon flux distributions is crucial for the understanding and targeted optimization of cellular systems. Analytical methods to identify the topology of metabolic networks and to quantify fluxes through its different pathways are therefore in the core of metabolic engineering. An elegant approach for metabolic flux analysis is provided by tracer experiments. In such studies tracer substrates with stable isotopes such as 13C are applied and the labeling pattern of metabolites is subsequently measured. Detailed flux distributions can be obtained by a combination of tracer experiments and stoichiometric balancing. In recent years, mass spectrometry (MS) has emerged as an interesting method for labeling measurements in metabolic flux analysis and provided valuable insights into the cellular metabolism. The present review provides an overview on current experimental and modeling tools for metabolic flux analysis by MS. The application of MS for flux analysis is illustrated by examples from the literature for various biological systems, including bacteria, fungi, tissue cultures and in vivo studies in humans.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 11991183     DOI: 10.1007/3-540-45736-4_3

Source DB:  PubMed          Journal:  Adv Biochem Eng Biotechnol        ISSN: 0724-6145            Impact factor:   2.635


  21 in total

1.  Stable isotope peptide mass spectrometry to decipher amino acid metabolism in Dehalococcoides strain CBDB1.

Authors:  Ernest Marco-Urrea; Jana Seifert; Martin von Bergen; Lorenz Adrian
Journal:  J Bacteriol       Date:  2012-06-01       Impact factor: 3.490

Review 2.  Mass spectrometry-based metabolomics.

Authors:  Katja Dettmer; Pavel A Aronov; Bruce D Hammock
Journal:  Mass Spectrom Rev       Date:  2007 Jan-Feb       Impact factor: 10.946

3.  (13)C-based metabolic flux analysis.

Authors:  Nicola Zamboni; Sarah-Maria Fendt; Martin Rühl; Uwe Sauer
Journal:  Nat Protoc       Date:  2009-05-21       Impact factor: 13.491

4.  13C isotope-assisted methods for quantifying glutamine metabolism in cancer cells.

Authors:  Jie Zhang; Woo Suk Ahn; Paulo A Gameiro; Mark A Keibler; Zhe Zhang; Gregory Stephanopoulos
Journal:  Methods Enzymol       Date:  2014       Impact factor: 1.600

Review 5.  Recent advances in mapping environmental microbial metabolisms through 13C isotopic fingerprints.

Authors:  Joseph Kuo-Hsiang Tang; Le You; Robert E Blankenship; Yinjie J Tang
Journal:  J R Soc Interface       Date:  2012-08-15       Impact factor: 4.118

6.  Genome-enabled determination of amino acid biosynthesis in Xanthomonas campestris pv. campestris and identification of biosynthetic pathways for alanine, glycine, and isoleucine by 13C-isotopologue profiling.

Authors:  Sarah Schatschneider; Frank-Jörg Vorhölter; Christian Rückert; Anke Becker; Wolfgang Eisenreich; Alfred Pühler; Karsten Niehaus
Journal:  Mol Genet Genomics       Date:  2011-08-19       Impact factor: 3.291

7.  Genealogy profiling through strain improvement by using metabolic network analysis: metabolic flux genealogy of several generations of lysine-producing corynebacteria.

Authors:  Christoph Wittmann; Elmar Heinzle
Journal:  Appl Environ Microbiol       Date:  2002-12       Impact factor: 4.792

8.  Low mass MS/MS fragments of protonated amino acids used for distinction of their 13C-isotopomers in metabolic studies.

Authors:  Xin Ma; Shai Dagan; Arpád Somogyi; Vicki H Wysocki; Patricia Y Scaraffia
Journal:  J Am Soc Mass Spectrom       Date:  2013-02-27       Impact factor: 3.109

9.  The Bacillus subtilis yqjI gene encodes the NADP+-dependent 6-P-gluconate dehydrogenase in the pentose phosphate pathway.

Authors:  Nicola Zamboni; Eliane Fischer; Dietmar Laudert; Stéphane Aymerich; Hans-Peter Hohmann; Uwe Sauer
Journal:  J Bacteriol       Date:  2004-07       Impact factor: 3.490

10.  In-depth profiling of lysine-producing Corynebacterium glutamicum by combined analysis of the transcriptome, metabolome, and fluxome.

Authors:  Jens Olaf Krömer; Oliver Sorgenfrei; Kai Klopprogge; Elmar Heinzle; Christoph Wittmann
Journal:  J Bacteriol       Date:  2004-03       Impact factor: 3.490

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.