Repository » Data AccessID 108

Detail View - Data AccessID 108

Backimage Back

General Information info

Manuscript title Metabolic flux analysis of Escherichia coli K12 grown on 13C-labeled acetate and glucose using GC-MS and powerful flux calculation method.
PubMed ID 12568740
Journal Journal of Biotechnology
Year 2003
Authors Jiao Zhao, Kazuyuki Shimizu
Affiliations Institute for Advanced Biosciences, Keio University, Yamagata 997-0017, Japan
Keywords Mass isotopomer analysis, Metabolic flux analysis, Carbon source, Genetic algorithm, Levenberg-Marquardt algorithm, Escherichia coli K12
Full text article no file uploaded
Project name not specified

Experiment Description info

Organism Escherichia coli
Strain K-12
Data type flux measurements
Data units (mmol/g.h)
Execution date not specified

Experimental Details info

Temperature (0C) 37
pH 7.0
Carbon source glucose,
Culture mode chemostat
Process condition aerobic
Dilution rate (h-1) 0.11 and 0.22
Working volume (L) 0.9
Biomass concentration (g/L) not specified
Medium composition

Minimal medium: 2 g of sodium acetate or 4 g of glucose per liter, 48 mM Na2HPO4, 22 mM KH2PO4, 10 mM NaCl, and 30 mM (NH4)2SO4. The following components were sterilized separately and then added (per liter of final medium): 1 ml of 1 M MgSO4, 1 ml of 0.1 mM CaCl2, 1 ml of 1 mg of vitamin B1 per liter (filter sterilized), and 10 ml of trace element solution containing (per liter) 0.55 g of CaCl2, 1 g of FeCl3, 0.1 g of MnCl2·4H2O, 0.17 g of ZnCl2, 0.043 g of CuCl2·2H2O, 0.06 g of CoCl2·6H2O, and 0.06 g of Na2MoO4·2H2O.

General protocol information Flux analysis method: 13C constrained MFA

Platform: GC-MS

Methods description - Notes

Labeling experiments were initiated after the culture reached a steady state, which was inferred from the stable oxygen and carbon dioxide concentrations in the fermentor off-gas and stable optical density in the effluent medium for at least twice as long as the residence time. The feed medium containing 2 g of unlabeled sodium acetate per liter was then replaced by an identical medium containing 1.8 g of sodium acetate labeled by natural abundance per liter and 0.2 g of [2-13C] sodium acetate (Wako Co., Osaka, Japan) per liter. In the case where glucose was used as a sole carbon source, the mixture of 0.3 g uniformly labeled glucose [U-13C], 0.3 g first carbon labeled glucose [1-13C] and 3.4 g of naturally labeled glucose per liter was used to replace the initial feed medium containing 4 g l−1 unlabeled glucose. Biomass samples for GC-MS analysis were taken after one residence time, and the labeling measurements were corrected for the remaining original (nonlabeled) biomass that was still present even at the end of the labeling experiment [1]. Sample preparation for analysis:
Samples were taken from the cultivation for the determination of absorbance at 600 nm using a spectrophotometer (V-530, JASCO Co., Japan). Thereafter, centrifugation of the remaining sample volume was carried out at 4 °C, 10 000 rpm for 10 min, and the filtrate was frozen at −30 °C for later use in extracellular metabolites analyses. After this, the cell pellet was resuspended in distilled water and centrifuged again. For the analysis of the fractional labeling of intracellular metabolites, about 20 mg of wet biomass was transferred to 1 ml of 6 M HCl. The closed tube was heated for 24 h at 110 °C for complete hydrolysis and, after cooling to room temperature, the solvent was evaporated under a stream of air. After this, about 1 ml of distilled water was added to the dried hydrolytes, which was then filtered through a 0.2 μm-pore-size filter for separation of the cell debris. The filtrate was dried again under a stream of air and redissolved in 0.5 ml of acetonitrile (chromatographic grade) for later GC-MS analysis. GC-MS analysis: Hundred microliter acetonitrile containing biomass hydrolysate was added to 100 μl of N-(tert-butyldimethylsilyl)-N-methyl-trifluoroacetamide (MTBST-FA) (derivatization grade, Aldrich, USA). The mixture was incubated for 60 min at 110 °C for complete derivatization. After cooling to room temperature, aliquots of the solution containing the derivatives were used directly for GC. GC-MS analysis was carried out using AutoSystem XL GC (PerkinElmer Co., USA) equipped with a DB-5MS column (30 m×0.25 mm×0.25 μm, Agilent Co., USA) which was directly connected to a TurboMass Gold mass spectrometer (PerkinElmer Co.). The injection volume was 1 μl with flow mode in split control. The carrier gas flow was set at 1-ml min−1 helium. The oven temperature was initially held at 80 °C for 2 min. Hereafter, the temperature was raised with a gradient of 8 °C min−1 until the temperature reached to 290 °C. This temperature, 290 °C, was held for 3 min. Other settings were as follows: 250 °C interface temperature, 200 °C ion source temperature, and electron impact ionization (EI) at 70 eV. Mass spectra were analyzed by both full scan mode and selected ion monitoring (SIM) mode. Raw MS data were processed using the program TurboMass Gold V4.3 (PerkinElmer Co.) to obtain a purified spectrum by removing residual background contaminants, partially eluting peaks, and column bleed from the spectrum. Skewing effects of natural isotopes were corrected by developing a program using matlab language (Mathwork Co., USA).Please see more details in the original publication. -----------------------------------References---------------------------------
[1] M Dauner, J.E Bailey, U Sauer. Biotechnol. Bioeng., 76 (2001), pp. 144-156. http://doi.org/db9x4v

Data file
Downloadfluxes KIMODATAID108_v1.xlsx
Alternative format(s)
no file uploaded
Cite|Share

Organism


Related Data: AccessID 30 | AccessID 35 | AccessID 41 | AccessID 44 | AccessID 51 | AccessID 54 | AccessID 63 | AccessID 64 | AccessID 65 | AccessID 67 | AccessID 68 | AccessID 74 | AccessID 75 | AccessID 78 | AccessID 79 | AccessID 80 | AccessID 86 | AccessID 87 | AccessID 92 | AccessID 96 | AccessID 101 | AccessID 102 | AccessID 103 | AccessID 104 | AccessID 105 | AccessID 106 | AccessID 107 | AccessID 109 | AccessID 110 | AccessID 112 | AccessID 116 | AccessID 118 | AccessID 119 | AccessID 125 | AccessID 126


Submission and curation info

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 2018-07-23 10:04:17 UTC

Updated 2018-07-26 15:23:39 UTC

Version 1

Status (reviewed) 2018-07-23 10:04:51 UTC




Associated Models


Here we can find relevant models associated with Data EntryID 108:

Model
EntryID
Model name Category Model Type Data used for Access Json
43
Authors: Vivek Kumar Singh and Indira Ghosh

Original paper: Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets

Singh2006_TCA_Ecoli_acetate Metabolism ordinary differential equations Model validation Visto4 {"affiliation":"Bioinformatics Centre, University of Pune, India","article_file_name":null,"authors":"Vivek Kumar Singh and Indira Ghosh","biomodels_id":"BIOMD0000000221","category":"Metabolism","combine_archive_content_type":"application/octet-stream","combine_archive_file_name":"COMBINE_KIMOMODELID43.omex","combine_archive_file_size":253672,"combine_archive_updated_at":"2018-07-27T10:28:17Z","comments":"Original model source: in BioModels database.","control":null,"dilution_rate":"","id":43,"journal":"Theoretical Biology and Medical Modelling","keywords":"Tuberculosis, Steady State Flux, Glyoxylate Bypass, Metabolic Control Analysis, Experimental Flux","main_organism":"Escherichia coli","manuscript_title":"Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets","model_name":"Singh2006_TCA_Ecoli_acetate","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"16887020","review_journal_id":null,"sbml_file_name":"Singh_2006.pdf","software":"Jarnac 2.14 (http://jdesigner.sourceforge.net/Site/Jarnac.html)","used_for":"---\n- Model validation\n","year":2006} Administrator KiMoSys
44
Authors: Vivek Kumar Singh and Indira Ghosh

Original paper: Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets

Singh2006_TCA_Ecoli_glucose Metabolism ordinary differential equations Model validation Visto4 {"affiliation":"Bioinformatics Centre, University of Pune, India","article_file_name":null,"authors":"Vivek Kumar Singh and Indira Ghosh","biomodels_id":"BIOMD0000000222","category":"Metabolism","combine_archive_content_type":null,"combine_archive_file_name":null,"combine_archive_file_size":null,"combine_archive_updated_at":null,"comments":"Original model source: in BioModels database.","control":null,"dilution_rate":"","id":44,"journal":"Theoretical Biology and Medical Modelling","keywords":"Tuberculosis, Steady State Flux, Glyoxylate Bypass, Metabolic Control Analysis, Experimental Flux","main_organism":"Escherichia coli","manuscript_title":"Kinetic modeling of tricarboxylic acid cycle and glyoxylate bypass in Mycobacterium tuberculosis, and its application to assessment of drug targets","model_name":"Singh2006_TCA_Ecoli_glucose","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"16887020","review_journal_id":null,"sbml_file_name":"Singh_2006.pdf","software":"Jarnac 2.14 (http://jdesigner.sourceforge.net/Site/Jarnac.html)","used_for":"---\n- Model validation\n","year":2006} Administrator KiMoSys



Associate models to data

- Several models can be associated.

Add New Model



Backimage Back | Top