Literature DB >> 17411014

Sampling for metabolome analysis of microorganisms.

Christoph J Bolten1, Patrick Kiefer, Fabien Letisse, Jean-Charles Portais, Christoph Wittmann.   

Abstract

In the present work we investigated the most commonly applied methods used for sampling of microorganisms in the field of metabolomics in order to unravel potential sources of error previously ignored but of utmost importance for accurate metabolome analysis. To broaden the significance of our study, we investigated different Gram-negative and Gram-positive bacteria, i.e., Bacillus subtilis, Corynebacterium glutamicum, Escherichia coli, Gluconobacter oxydans, Pseudomonas putida, and Zymononas mobilis, and analyzed metabolites from different catabolic and anabolic intracellular pathways. Quenching of cells with cold methanol prior to cell separation and extraction led to drastic loss (>60%) of all metabolites tested due to unspecific leakage. Using fast filtration, Gram-negative bacteria also revealed a significant loss (>80%) when inappropriate washing solutions with low ionic strength were applied. Adapting the ionic strength of the washing solution to that of the cultivation medium could almost completely avoid this problem. Gram-positive strains did not show significant leakage independent of the washing solution. Fast filtration with sampling times of several seconds prior to extraction appears to be a suitable approach for metabolites with relatively high intracellular level and low turnover such as amino acids or TCA cycle intermediates. Comparison of metabolite levels in the culture supernatant and the cell interior revealed that the common assumption of whole broth quenching protocols attributing the metabolites found exclusively to the intracellular pools may not be valid in many cases. In such cases a differential approach correcting for medium-contained metabolites is required.

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Year:  2007        PMID: 17411014     DOI: 10.1021/ac0623888

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  91 in total

1.  Time-resolved metabolic footprinting for nonlinear modeling of bacterial substrate utilization.

Authors:  Volker Behrends; Tim M D Ebbels; Huw D Williams; Jacob G Bundy
Journal:  Appl Environ Microbiol       Date:  2009-02-13       Impact factor: 4.792

2.  Analysing overexpression of L-valine biosynthesis genes in pyruvate-dehydrogenase-deficient Corynebacterium glutamicum.

Authors:  Tobias Bartek; Enrico Zönnchen; Bianca Klein; Robert Gerstmeir; Pia Makus; Siegmund Lang; Marco Oldiges
Journal:  J Ind Microbiol Biotechnol       Date:  2009-12-11       Impact factor: 3.346

3.  Capillary LC-MS for high sensitivity metabolomic analysis of single islets of Langerhans.

Authors:  Qihui Ni; Kendra R Reid; Charles F Burant; Robert T Kennedy
Journal:  Anal Chem       Date:  2008-04-10       Impact factor: 6.986

4.  Fast sampling method for mammalian cell metabolic analyses using liquid chromatography-mass spectrometry.

Authors:  Giuseppe Martano; Nathanaël Delmotte; Patrick Kiefer; Philipp Christen; David Kentner; Dirk Bumann; Julia A Vorholt
Journal:  Nat Protoc       Date:  2014-12-04       Impact factor: 13.491

5.  Multiple Optimal Phenotypes Overcome Redox and Glycolytic Intermediate Metabolite Imbalances in Escherichia coli pgi Knockout Evolutions.

Authors:  Douglas McCloskey; Sibei Xu; Troy E Sandberg; Elizabeth Brunk; Ying Hefner; Richard Szubin; Adam M Feist; Bernhard O Palsson
Journal:  Appl Environ Microbiol       Date:  2018-09-17       Impact factor: 4.792

6.  Formation of N-ethylmaleimide (NEM)-glutathione conjugate and N-ethylmaleamic acid revealed by mass spectral characterization of intracellular and extracellular microbial metabolites of NEM.

Authors:  Elmer-Rico E Mojica; Sungpyo Kim; Diana S Aga
Journal:  Appl Environ Microbiol       Date:  2007-11-02       Impact factor: 4.792

7.  Metabolomic and transcriptomic stress response of Escherichia coli.

Authors:  Szymon Jozefczuk; Sebastian Klie; Gareth Catchpole; Jedrzej Szymanski; Alvaro Cuadros-Inostroza; Dirk Steinhauser; Joachim Selbig; Lothar Willmitzer
Journal:  Mol Syst Biol       Date:  2010-05-11       Impact factor: 11.429

8.  Evolution of allosteric citrate binding sites on 6-phosphofructo-1-kinase.

Authors:  Aleksandra Usenik; Matic Legiša
Journal:  PLoS One       Date:  2010-11-23       Impact factor: 3.240

9.  Stability of metabolic correlations under changing environmental conditions in Escherichia coli--a systems approach.

Authors:  Jedrzej Szymanski; Szymon Jozefczuk; Zoran Nikoloski; Joachim Selbig; Victoria Nikiforova; Gareth Catchpole; Lothar Willmitzer
Journal:  PLoS One       Date:  2009-10-15       Impact factor: 3.240

10.  Metabolite profiling uncovers plasmid-induced cobalt limitation under methylotrophic growth conditions.

Authors:  Patrick Kiefer; Markus Buchhaupt; Philipp Christen; Björn Kaup; Jens Schrader; Julia A Vorholt
Journal:  PLoS One       Date:  2009-11-13       Impact factor: 3.240

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