Repository » Data AccessID 35

Detail View - Data AccessID 35

Backimage Back

General Information info

Manuscript title Multiple High-Throughput Analyses Monitor the Response of E. coli to Perturbations.
PubMed ID 17379776
Journal Science
Year 2007
Authors Nobuyoshi Ishii, Kenji Nakahigashi, Tomoya Baba, Martin Robert, Tomoyoshi Soga, Akio Kanai, Takashi Hirasawa, Miki Naba, Kenta Hirai, Aminul Hoque, Pei Yee Ho, Yuji Kakazu, Kaori Sugawara, Saori Igarashi, Satoshi Harada, Takeshi Masuda, Naoyuki Sugiyama, Takashi Togashi, Miki Hasegawa, Yuki Takai, Katsuyuki Yugi, Kazuharu Arakawa, Nayuta Iwata, Yoshihiro Toya, Yoichi Nakayama, Takaaki Nishioka, Kazuyuki Shimizu, Hirotada Mori, Masaru Tomita
Affiliations Institute for Advanced Biosciences, Keio University
Keywords Escherichia coli, perturbations response, chemostat, single knockouts
Full text article no file uploaded
Project name not specified

Experiment Description info

Organism Escherichia coli
Strain WT K-12 BW25113 and mutants
Data type flux measurements
Data units (mmol/gDW/h)
Execution date not specified

Experimental Details info

Temperature (0C) 37.0
pH 7.0
Carbon source glucose,
Culture mode chemostat
Process condition aerobic
Dilution rate (h-1) 0.1, 0.2, 0.4, 0.5 and 0.7
Working volume (L) 1.0
Biomass concentration (g/L) See Supplementary files of the original article (Tabel S3).
Medium composition

Synthetic medium: 48mM Na2HPO4, 22mM KH2PO4, 10mM NaCl, 45mM (NH4)2SO4, 4g/L glucose, 1mM MgSO4, 1mg/L thiamin.HCL, 5.6 mg/L CaCl2, 8 mg/L FeCl3, 1 mg/L MnCl2.4H2O, 1.7 mg/L ZnCl2, 0.43 mg/L CuCl2.2H2O, 0.6 mg/L CoCl2.2H2O and 0.6 mg/L Na2MoO4.2H2O

General protocol information Flux analysis method: 13C constrained MFA

Platform: GC-MS

Methods description - Notes

13C-labeling experiment - for metabolic flux analysis, 13C-labeling experiments were initiated after taking samples for transcriptome, proteome and metabolome analysis. For experiments with gene disruptants, the feed medium containing 4 g/l of natural glucose was replaced by an identical medium containing 0.4 g/l of [1-13C] glucose, 0.4 g/l of uniformly labeled [U-13C] glucose and 3.2 g/l of natural glucose. For experiments examining the effect of changes in dilution rate on flux distributions, the composition of glucose in the feed medium was changed to 0.8 g/l of [1-13C] glucose, 0.8 g/l of [U-13C] glucose and 2.4 g/l of natural glucose. After two residence times, for gas chromatography-mass spectrometry (GC-MS) analysis, E. coli cells were harvested by centrifugation.
GC-MS analysis - the cells obtained from about 250 ml of culture were suspended in 4 ml of 6 M HCl and then hydrolyzed at 105 ºC for 16 h. After cooling, HCl was evaporated with a centrifugal evaporator (CVE-3100, Tokyo Rikakikai Co., Ltd., Japan). The dried hydrolysate was resuspended in water and then filtrated through a 0.22-μm pore size filter (Millipore Co., USA). The filtrate was dried again and redissolved in 1.5 ml of acetonitrile. For derivatization, the resulting 80 μl of biomass hydrolysate dissolved in acetonitrile was mixed with an equal volume of N-methyl-N-(tert-butyldimethylsilyl)-trifluoroacetamide and then incubated at 110 ºC for 30 min. After cooling, the derivatized sample was used for the GC-MS analysis using a TurboMass Gold mass spectrometer (Perkin Elmer, USA). In the present study, two fragment ions, [M-57]+ and [M-159]+, of tert-butyldimethylsilylated (TBDMS-) amino acids (Ala, Gly, Val, Ile, Pro, Ser, Met, Phe, Asp, Glu and Tyr) were monitored. The analytical conditions for GC-MS were as described by Zhao et al [1].
Estimation of metabolic flux distribution - for metabolic flux analysis, we constructed a basic stoichiometric reaction model for the main metabolic pathways including glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, the glyoxylate shunt and the anaplerotic pathway. The biomass content reported by Li et al. [2] was used for calculations.

--------------------References---------------
[1] J. Zhao, K. Shimizu, J. Biotechnol. 101, 101 (2003). http://doi.org/cdjhrn
[2] M. Li, P. Y. Ho, S. Yao, K. Shimizu, J. Biotechnol. 122, 254 (2006). http://doi.org/cr7qpd

Data file
Downloadfluxes KIMODATAID35_v3.xlsx
Alternative format(s)
no file uploaded
Cite|Share

Organism


Related Data: AccessID 30 | 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 108 | 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 2013-04-22 11:42:01 UTC

Updated 2015-06-30 15:27:42 UTC

Version 3

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




Associated Models


Here we can find relevant models associated with Data EntryID 35:

Model
EntryID
Model name Category Model Type Data used for Access Json
36
Authors: Ali Khodayari, Ali R. Zomorrodi, James C.Liao, Costas D. Maranas

Original paper: A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data.

Kinetic model of Escherichia coli core metabolism Metabolism ordinary differential equations Model building and Model validation Visto4 {"affiliation":"Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA","article_file_name":null,"authors":"Ali Khodayari, Ali R. Zomorrodi, James C.Liao, Costas D. Maranas","biomodels_id":"","category":"Metabolism","combine_archive_content_type":null,"combine_archive_file_name":null,"combine_archive_file_size":null,"combine_archive_updated_at":null,"comments":"","control":null,"dilution_rate":"","id":36,"journal":"Metabolic Engineering","keywords":"ensemble modeling, kinetic modeling, metabolic network","main_organism":"Escherichia coli","manuscript_title":"A kinetic model of Escherichia coli core metabolism satisfying multiple sets of mutant flux data.","model_name":"Kinetic model of Escherichia coli core metabolism","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"24928774","review_journal_id":null,"sbml_file_name":"Khodayari_2014.pdf","software":"http://www.matlab.com (MATLAB)","used_for":"---\n- Model building\n- Model validation\n","year":2014} Administrator KiMoSys
38
Authors: Nusrat Jahan, Kazuhiro Maeda, Yu Matsuoka, Yurie Sugimoto and Hiroyuki Kurata

Original paper: Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli

E. coli Central Carbon Metabolism Metabolism ordinary differential equations Model building and Model validation Visto4 {"affiliation":"Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680\u20114 Kawazu, Iizuka, Fukuoka 820\u20118502, Japan","article_file_name":null,"authors":"Nusrat Jahan, Kazuhiro Maeda, Yu Matsuoka, Yurie Sugimoto and Hiroyuki Kurata","biomodels_id":"","category":"Metabolism","combine_archive_content_type":"application/octet-stream","combine_archive_file_name":"COMBINE_KIMOMODELID38.omex","combine_archive_file_size":6603649,"combine_archive_updated_at":"2018-07-23T21:38:00Z","comments":"MATLAB version of the model is available at http://www.cadlive.jp/cadlive_main/Softwares/KineticModel/Ecolimetabolism.html. ","control":"2018-07-20T16:47:46Z","dilution_rate":"0.2, 0.4, 0.5 and 0.7","id":38,"journal":"Microbial Cell Factories","keywords":"Systems biology, Rational design, Dynamic model, Enzyme kinetics, Transcription factor, Signal transduction, Allosteric enzyme","main_organism":"Escherichia coli","manuscript_title":"Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli","model_name":"E. coli Central Carbon Metabolism","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"27329289","review_journal_id":null,"sbml_file_name":"Jahan_2016.pdf","software":"MATLAB2007 or higher","used_for":"---\n- Model building\n- Model validation\n","year":2016} Administrator KiMoSys
41
Authors: Hiroyuki Kurata and Yurie Sugimoto

Original paper: Improved kinetic model of Escherichia coli central carbon metabolism in batch and continuous cultures

Continuous kinetic model of Escherichia coli Metabolism ordinary differential equations Model building and Model validation Visto4 {"affiliation":"Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680 -4 Kawazu, Iizuka, Fukuoka 820 -8502, Japan","article_file_name":null,"authors":"Hiroyuki Kurata and Yurie Sugimoto","biomodels_id":"","category":"Metabolism","combine_archive_content_type":null,"combine_archive_file_name":null,"combine_archive_file_size":null,"combine_archive_updated_at":null,"comments":"Kinetic model source: http://www.cadlive.jp/cadlive_main/Softwares/KineticModel/Ecolimetabolism.html.","control":"2018-07-24T15:46:04Z","dilution_rate":"0.2, 0.4, 0.5 and 0.7","id":41,"journal":"Journal of Bioscience and Bioengineering","keywords":"Kinetic model, Synthetic biology, Central carbon metabolism, Dynamic simulation, Escherichia coli","main_organism":"Escherichia coli","manuscript_title":"Improved kinetic model of Escherichia coli central carbon metabolism in batch and continuous cultures","model_name":"Continuous kinetic model of Escherichia coli","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"29054464","review_journal_id":null,"sbml_file_name":"Kurata_2018.pdf","software":"MATLAB (MathWorks)","used_for":"---\n- Model building\n- Model validation\n","year":2018} Administrator KiMoSys
42
Authors: Ahmad A. Mannan, Yoshihiro Toya, Kazuyuki Shimizu, Johnjoe McFadden, Andrzej M. Kierzek , Andrea Rocco

Original paper: Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.

kinetic model of the central carbon metabolism of E. coli Metabolism ordinary differential equations Model building Visto4 {"affiliation":"Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom ","article_file_name":null,"authors":"Ahmad A. Mannan, Yoshihiro Toya, Kazuyuki Shimizu, Johnjoe McFadden, Andrzej M. Kierzek , Andrea Rocco","biomodels_id":"","category":"Metabolism","combine_archive_content_type":null,"combine_archive_file_name":null,"combine_archive_file_size":null,"combine_archive_updated_at":null,"comments":"For the analysis and evaluation of the kinetic model, the solver ode15s was used.","control":null,"dilution_rate":"0.2","id":42,"journal":"Plos One","keywords":"E. coli, Bistability, Central Metabolism","main_organism":"Escherichia coli","manuscript_title":"Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism.","model_name":"kinetic model of the central carbon metabolism of E. coli ","model_type":"ordinary differential equations","organism_id":null,"project_name":"","pubmed_id":"26469081","review_journal_id":null,"sbml_file_name":"Mannan_2015.PDF","software":"MATLAB\u00ae R2007b (version 7.5.0)","used_for":"---\n- Model building\n","year":2015} Administrator KiMoSys



Associate models to data

- Several models can be associated.

Add New Model



Backimage Back | Top