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General Information info

Manuscript title Integration of in vivo and in silico metabolic fluxes for improvement of recombinant protein production.
PubMed ID 22115737
Journal Metabolic Engineering
Year 2012
Authors Habib Driouch, Guido Melzer, Christoph Wittmann
Affiliations Institute of Biochemical Engineering, Technische Universitat Braunschweig, Gaussstrasse 17, Braunschweig, Germany
Keywords Aspergillus niger, 13C metabolic flux, fructofuranosidase
Full text article Downloadarticle Driouch_2012.pdf
Project name not specified

Experiment Description info

Organism Aspergillus niger
Strain SKANip8 (W.T.) and SKAn1015
Data type flux measurements
Data units (mmol/gh)
Execution date not specified

Experimental Details info

Temperature (0C) 37.0
pH 5.0
Carbon source glucose,
Culture mode batch
Process condition aerobic
Dilution rate (h-1)
Working volume (L) 0.025
Biomass concentration (g/L) not specified
Medium composition

Medium contained per litre: 15 g glucose, 20 mL salt solution (50× with 180 g/L NaNO3, 10 g/L KCI, 30 g/L KH2PO4, 10 g/L MgSO4.7H2O) and 1 mL trace element solution (1000× with 10 g/L EDTA, 4.4 g/L ZnSO4·7H2O, 1.5 g/L MnCl2.4H2O, 0.32 g/L CuSO4.5H2O, 7.5 g/L FeSO4·7H2O, 0.32 g/L CoCl2·6H2O, 1.47 g/L CaCl2·2H2O and 0.22 g/L (NH4)6Mo7O24.4H2O). In 13C-labeling experiments, glucose was replaced by an equimolar amount of 13C-labeled glucose. To resolve the metabolic fluxes of interest two parallel set-ups were chosen for the labeling studies (Wittmann and Heinzle 2002). This included one set-up with [1-13C] glucose (99%, Cambridge Isotope Laboratories, Andover, USA) and one set-up with a 1:1 mixture of [13C6] glucose (99%, Cambridge Isotope Laboratories, Andover, USA) and naturally labeled glucose. See manuscript for more details.

General protocol information Flux analysis method: 13C constrained MFA

Platform: GC-MS

Methods description - Notes

Labeling analysis of proteinogenic amino acids by GC–MS - cells of A. niger were harvested during mid-exponential growth by filtration of 5mL culture broth through a cellulose acetatefilter (pore size 20 µm, Sartorius, Goettingen, Germany). After removal of excess medium by two washing steps with sterile 0.9% NaCI solution, the cells were frozen in liquid nitrogen and then lyophilized at -60 ºC (Alpha 1-4 LD, Christ GmbH, Osterode, Germany). For protein hydrolysis 10mg of lyophilized biomass was incubated in 400 mL of 6M HCl at 100 ºC for 24h. After pH adjustment to 7.0 by 6M NaOH, the hydrolysate was clarified (0.2 µm, Ultrafree MC, Millipore, Bedford, MA, USA) and again lyophilized. The contained proteinogenic amino acids were then converted into t-butyl-di-methyl-silyl derivates [1]. Their labeling pattern was quantified by GC–MS (HP6890, M5973, Agilent Technologies, Waldbronn, Germany) as described previously [2]. All samples were measured first in scan mode, there with excluding isobaric overlay [3]. The relative fractions of the mass isotopomers of interest were then determined in duplicate in selective ion monitoring (SIM) mode.
Metabolic reaction network - a compartmented metabolic network model of A. niger was constructed on basis of validated models recently described [4-7].
Metabolic flux calculation - the estimation of metabolic fluxes was performed with the MATLAB-based program FiatFLUX 1.67, which was kindly provided by the authors [8].

-----------------References---------------
[1] Wittmann, C., Heinzle,E., 2002.Genealogy profiling through strain improvement using metabolic network analysis: metabolic flux genealogy of several generations of lysine-producing corynebacteria. Appl. Environ. Microbiol. 68, 5843–5859. http://doi.org/c3qcbr
[2] Kiefer, P., Heinzle,E., Zelder,O., Wittmann,C., 2004. Comparative metabolic flux analysis oflysine-producing Corynebacterium glutamicum cultured on glucose or fructose. Appl. Environ. Microbiol. 70, 229–239. http://doi.org/cg63zq
[3] Wittmann, C., 2007. Fluxome analysis using GC–MS. Microb. Cell Fact. 6, 6. http://doi.org/cfph95
[4] Andersen, M.R.,Nielsen,M.L.,Nielsen,J., 2008. Metabolic model integration of the bibliome, genome, metabolome and reactome of Aspergillus niger. Mol. Syst. Biol. 4, 178. http://doi.org/b3wcr4
[5] Jouhten, P., Pitkanen, E., Pakula,T., Saloheimo,M., Penttila, M., Maaheimo,H., 2009. 13C-metabolic flux ratio and novel carbon path analyses confirmed that Trichoderma reesei uses primarily the respirative pathway also on the preferred carbon source glucose. BMC Syst. Biol. 3, 104. http://doi.org/bc7zd6
[6] Meijer, S., Otero,J., Olivares,R., Andersen,M.R., Olsson, L., Nielsen, J., 2009. Overexpression of isocitrate lyase-glyoxylate by pass influence on metabolism in Aspergillus niger. Metab.Eng. 11, 107–116. http://doi.org/cn7bbd
[7] Melzer, G., Esfandabadi,M.E., Franco-Lara,E., Wittmann, C., 2009. Flux design: in silico design of cell factories based on correlation of pathway fluxes to desired properties. BMC. Syst. Biol. 3, 120. http://doi.org/cf9n8n
[8] Zamboni, N., Fischer,E., Sauer,E., 2005. FiatFlux — a software for metabolic flux analysis from13C-glucose experiments. BMC Bioinform. 6, 209. http://doi.org/bj2zk2

Data file
Downloadfluxes KIMODATAID72_v0.xlsx
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KIMODATAID72_wt_reaction_SBtab.csv
KIMODATAID72_producer_reaction_SBtab.csv
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Entered by Administrator KiMoSysFirst name: Administrator
Affiliation: INESC-ID/IST
Homepage: http://kdbio.inesc-id.pt/kimosys
Interests: mathematical modeling, accessible data, use of data

Created 2013-06-22 14:35:53 UTC

Updated 2014-06-13 16:40:38 UTC

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Status (reviewed) 2013-12-06 17:17:38 UTC




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