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@ARTICLE{Nh:57502,
author = {Nöh, K. and Grönke, K. and Luo, B. and Takors, R. and
Oldiges, M. and Wiechert, W.},
title = {{M}etabolic flux analysis at ultra short time scale:
{I}sotopically non-stationary 13{C} labeling experiments},
journal = {Journal of biotechnology},
volume = {129},
issn = {0168-1656},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {PreJuSER-57502},
pages = {249 - 267},
year = {2007},
note = {Record converted from VDB: 12.11.2012},
abstract = {A novel approach to (13)C metabolic flux analysis (MFA) is
presented using cytosolic metabolite pool sizes and their
(13)C labeling data from an isotopically non-stationary
(13)C labeling experiment (INST-CLE). The procedure is
demonstrated with an E. coli wild type strain grown at fed
batch conditions. The intra cellular labeling dynamics are
excited by a sudden step increase of the (13)C portion in
the substrate feed. Due to unchanged saturation of the
substrate uptake system, the metabolic fluxes remain
constant during the following sampling time period of only
16s, in which 20 samples are taken by an automated rapid
sampling device immediately stopping metabolism by methanol
quenching. Subsequent cell disruptive sample preparation and
LC-MS/MS enabled simultaneous determination of pool sizes
and mass isotopomers of intra cellular metabolites requiring
detection limits in the nM range. Based on this data the new
computational flux analysis tool 13CFLUX/INST is used to
determine the intra cellular fluxes based on a complex
carbon labeling network model. The measured data is in good
agreement with the model predictions, thus proving the
applicability of the new isotopically non-stationary (13)C
metabolic flux analysis (INST-(13)C-MFA) concept. Moreover,
it is shown that significant new information with respect to
flux identifiability, non-measurable pool sizes, data
consistency, or large storage pools can be taken from the
novel kind of experimental data. This offers new insight
into the biological operation of the metabolic network in
vivo.},
keywords = {Bioreactors / Carbon: metabolism / Carbon Isotopes:
metabolism / Chromatography, Liquid / Computational Biology:
methods / Computer Simulation / Escherichia coli: metabolism
/ Fermentation: physiology / Metabolic Networks and
Pathways: physiology / Models, Biological / Tandem Mass
Spectrometry / Carbon Isotopes (NLM Chemicals) / Carbon (NLM
Chemicals) / J (WoSType)},
cin = {IBT-2},
ddc = {540},
cid = {I:(DE-Juel1)VDB56},
pnm = {Biotechnologie},
pid = {G:(DE-Juel1)FUEK410},
shelfmark = {Biotechnology $\&$ Applied Microbiology},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:17207877},
UT = {WOS:000246097000007},
doi = {10.1016/j.jbiotec.2006.11.015},
url = {https://juser.fz-juelich.de/record/57502},
}