From 8224a47b905713b283d8b50119f90fa947cc148b Mon Sep 17 00:00:00 2001 From: coltonlloyd Date: Tue, 21 Nov 2017 17:08:46 -0800 Subject: [PATCH 1/3] Fix gam/ngam bug --- .gitignore | 1 + BOFdat/maintenance.py | 12 ++++++++---- Example_usage/maintenance.csv | 19 ++++++++++++++----- 3 files changed, 23 insertions(+), 9 deletions(-) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..0d20b64 --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +*.pyc diff --git a/BOFdat/maintenance.py b/BOFdat/maintenance.py index 63dc4cf..ec426bf 100644 --- a/BOFdat/maintenance.py +++ b/BOFdat/maintenance.py @@ -88,12 +88,17 @@ def calculate_gam(model,data,show_GAM): biomass.lower_bound = 0. biomass.objective_coefficient = 0. + # remove GAM from biomass function + for key, value in biomass.metabolites.items(): + if abs(value) > 50: + biomass.add_metabolites({key: -value}) #Set carbon sources to 0 ''' Will need to prepare the model to run the simulations ''' #model.reactions.EX_glc_LPAREN_e_RPAREN_.lower_bound = 0 #Optimize for ATP maintenance + model.reactions.ATPM.lower_bound = 0 model.reactions.ATPM.objective_coefficient = 1. #model.reactions.EX_o2_LPAREN_e_RPAREN_.lower_bound = -1000 @@ -182,14 +187,12 @@ def calculate_gam(model,data,show_GAM): return raw_GAM def show_gam(raw_GAM): - import seaborn as sns import numpy as np import matplotlib.pyplot as plt x = raw_GAM['Growth_rate'] y = raw_GAM['ATP'] - #Fit with np.polyfit m, b = np.polyfit(x, y, 1) @@ -202,9 +205,10 @@ def show_gam(raw_GAM): print('R2=', correlation ** 2) plt.scatter(raw_GAM['Growth_rate'], raw_GAM['ATP']) # plt.scatter(filtered_data['GR'],filtered_data['ATP'], color=filtered_data['color'], marker=filtered_data['marker'].tolist()) - plt.show() + plt.xlim([0, 1.1]) - plt.ylim([0, 90]) + plt.ylim([0, 110]) + plt.show() #plt.savefig('all_data.png') #plt.savefig('all_data.svg') plt.close() diff --git a/Example_usage/maintenance.csv b/Example_usage/maintenance.csv index 65d7154..3958a40 100644 --- a/Example_usage/maintenance.csv +++ b/Example_usage/maintenance.csv @@ -4,11 +4,9 @@ experiment_3,EX_glc__D_e,0.98,0.02,13.51,1.15,0,0,8.43,2.17,0,0,0,0,0,0,0,0 experiment_4,EX_glc__D_e,0.96,0.01,12.19,0.68,0,0,7.89,1.88,0,0,0,0,0,0,0,0 experiment_5,EX_glc__D_e,0.93,0.01,12.77,0.85,0,0,7.11,1.51,0,0,0,0,0,0,0,0 experiment_6,EX_glc__D_e,1.01,0.04,13.13,1.29,0,0,5.12,0.57,0,0,0,0,0,0,0,0 -experiment_7,EX_glc__D_e,0.97,0.01,11.01,0.79,0,0,3.97,0.98,0,0,0,0,0,0,0,0 -experiment_8,EX_glc__D_e,0.92,0.02,10.43,0.62,0,0,2.36,0.54,0,0,0,0,0,0,0,0 -experiment_9,EX_glc__D_e,0.89,0.01,12.59,1.01,0,0,5.05,0.4,0,0,0,0,0,0,0,0 -experiment_10,EX_glc__D_e,0.92,0.02,13.13,0.59,0,0,6.99,0.48,0,0,0,0,0,0,0,0 -experiment_11,EX_glc__D_e,0.95,0.01,13.98,1.11,0,0,9.27,1.76,0,0,0,0,0,0,0,0 +experiment_8,EX_glc__D_e,0.89,0.01,12.59,1.01,0,0,5.05,0.4,0,0,0,0,0,0,0,0 +experiment_9,EX_glc__D_e,0.92,0.02,13.13,0.59,0,0,6.99,0.48,0,0,0,0,0,0,0,0 +experiment_10,EX_glc__D_e,0.95,0.01,13.98,1.11,0,0,9.27,1.76,0,0,0,0,0,0,0,0 acetate_1,EX_ac_e,0.223,0.011,12.14,0.629,0,0,0,0,0,0,0,0,0,0,0,0 acetate_2,EX_ac_e,0.418,0.013,20.346,0.564,0,0,0,0,0,0,0,0,0,0,0,0 acetate_3,EX_ac_e,0.43,0.01,23.016,0.02,0,0,0,0,0,0,0,0,0,0,0,0 @@ -19,3 +17,14 @@ xylose_2,EX_xyl__D_e,0.734,0.013,12.722,0.199,0,0,5.013,0.288,0,0,0,0,0,0,0,0 xylose_3,EX_xyl__D_e,0.728,0.006,11.413,0.026,0,0,1.813,0.155,0,0,0,0,0,0,0,0 xylose_4,EX_xyl__D_e,0.724,0.003,12.202,0.258,0,0,5.739,0.203,0,0,0,0,0,0,0,0 xylose_5,EX_xyl__D_e,0.76,0.011,13.179,0.154,0,0,3.209,0.112,0,0,0,0,0,0,0,0 +monk_1,EX_glc__D_e,0.73,0.01,9.67,0.27,0,0,3.49,0.5,0,0,0,0,0,0,0,0 +monk_2,EX_glc__D_e,0.46,0.02,16.69,0.24,0,0,11.71,1.14,0,0,22.17,1.69,11.22,0.6,1.86,0.04 +WT_Feist,EX_glyc_e,0.442,0.002,11.178,0.039,0,0,0,0,0,0,0,0,0,0,0,0 +WT_McCloskey_aer_1,EX_glc__D_e,0.59,0.01,7.81,0.27,0,0,3.26,0.23,0,0,0,0.33,0.12,0,0,0 +WT_McCloskey_aer_2,EX_glc__D_e,0.61,0.02,7.54,0.56,0,0,2.72,0.24,0,0,0,0.82,0.25,0,0,0 +WT_McCloskey_anaer_1,EX_glc__D_e,0.38,0,15.07,2.78,1.56,0.36,9.61,0.5,0.1,0.16,19.03,0.59,12.1,0.93,1.46,0.14 +WT_McCloskey_anaer_2_fix,EX_glc__D_e,0.38,0,16.2,2.11,1.39,0.11,12.04,0.18,0.33,0.07,22.41,0.28,11.4,1.86,2.01,0.11 +Glyc_1,EX_glyc_e,0.733,0.003,18.398,0.378,0,0,5.141,0.139,0,0,0,0,0,0,0,0 +Glyc_2,EX_glyc_e,0.73,0.018,18.579,0.738,0,0,5.256,0.118,0,0,0,0,0,0,0,0 +Glyc_3,EX_glyc_e,0.767,0.003,17.984,0.08,0,0,3.098,0.018,0,0,0,0,0,0,0,0 +Glyc_4,EX_glyc_e,0.749,0.005,18.484,1.028,0,0,3.248,0.12,0,0,0,0,0,0,0,0 From 719c1d6cac973df0348fca4c96e6b468eaca4683 Mon Sep 17 00:00:00 2001 From: coltonlloyd Date: Tue, 21 Nov 2017 17:12:17 -0800 Subject: [PATCH 2/3] Clean up repository --- .gitignore | 3 +++ BOFdat.egg-info/PKG-INFO | 10 ---------- BOFdat.egg-info/SOURCES.txt | 14 -------------- BOFdat.egg-info/dependency_links.txt | 1 - BOFdat.egg-info/requires.txt | 2 -- BOFdat.egg-info/top_level.txt | 1 - BOFdat/__init__.pyc | Bin 448 -> 0 bytes BOFdat/dna.pyc | Bin 4175 -> 0 bytes BOFdat/lipid.pyc | Bin 8584 -> 0 bytes BOFdat/maintenance.pyc | Bin 6301 -> 0 bytes BOFdat/metabolite.pyc | Bin 10799 -> 0 bytes BOFdat/protein.pyc | Bin 7657 -> 0 bytes BOFdat/rna.pyc | Bin 9068 -> 0 bytes BOFdat/update.pyc | Bin 1979 -> 0 bytes 14 files changed, 3 insertions(+), 28 deletions(-) delete mode 100644 BOFdat.egg-info/PKG-INFO delete mode 100644 BOFdat.egg-info/SOURCES.txt delete mode 100644 BOFdat.egg-info/dependency_links.txt delete mode 100644 BOFdat.egg-info/requires.txt delete mode 100644 BOFdat.egg-info/top_level.txt delete mode 100644 BOFdat/__init__.pyc delete mode 100644 BOFdat/dna.pyc delete mode 100644 BOFdat/lipid.pyc delete mode 100644 BOFdat/maintenance.pyc delete mode 100644 BOFdat/metabolite.pyc delete mode 100644 BOFdat/protein.pyc delete mode 100644 BOFdat/rna.pyc delete mode 100644 BOFdat/update.pyc diff --git a/.gitignore b/.gitignore index 0d20b64..166fbe0 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,4 @@ *.pyc +*.egg-info +gurobi.log +*.swp diff --git a/BOFdat.egg-info/PKG-INFO b/BOFdat.egg-info/PKG-INFO deleted file mode 100644 index a9202fb..0000000 --- a/BOFdat.egg-info/PKG-INFO +++ /dev/null @@ -1,10 +0,0 @@ -Metadata-Version: 1.0 -Name: BOFdat -Version: 0.3 -Summary: Package to generate biomass objective function stoichiometric coefficients from experimental data -Home-page: https://github.com/jclachance/BOFdat/ -Author: Jean-Christophe Lachance -Author-email: jelachance@eng.ucsd.edu -License: MIT -Description: UNKNOWN -Platform: UNKNOWN diff --git a/BOFdat.egg-info/SOURCES.txt b/BOFdat.egg-info/SOURCES.txt deleted file mode 100644 index cc6d080..0000000 --- a/BOFdat.egg-info/SOURCES.txt +++ /dev/null @@ -1,14 +0,0 @@ -setup.py -BOFdat/__init__.py -BOFdat/dna.py -BOFdat/lipid.py -BOFdat/maintenance.py -BOFdat/metabolite.py -BOFdat/protein.py -BOFdat/rna.py -BOFdat/update.py -BOFdat.egg-info/PKG-INFO -BOFdat.egg-info/SOURCES.txt -BOFdat.egg-info/dependency_links.txt -BOFdat.egg-info/requires.txt -BOFdat.egg-info/top_level.txt \ No newline at end of file diff --git a/BOFdat.egg-info/dependency_links.txt b/BOFdat.egg-info/dependency_links.txt deleted file mode 100644 index 8b13789..0000000 --- a/BOFdat.egg-info/dependency_links.txt +++ /dev/null @@ -1 +0,0 @@ - diff --git a/BOFdat.egg-info/requires.txt b/BOFdat.egg-info/requires.txt deleted file mode 100644 index 01dd35e..0000000 --- a/BOFdat.egg-info/requires.txt +++ /dev/null @@ -1,2 +0,0 @@ -cobra -BioPython diff --git a/BOFdat.egg-info/top_level.txt b/BOFdat.egg-info/top_level.txt deleted file mode 100644 index cee1f4a..0000000 --- a/BOFdat.egg-info/top_level.txt +++ /dev/null @@ -1 +0,0 @@ -BOFdat diff --git a/BOFdat/__init__.pyc b/BOFdat/__init__.pyc deleted file mode 100644 index 3e875f73ee4f4417deb68e32aa73d2bc9c8f64e6..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 448 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b/BOFdat/update.pyc deleted file mode 100644 index 4c0c11cf9aa725afc935ec14f55e5d30a0de4389..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1979 zcmcIlQE${n5T5nrE{Wkn38g41s{8=b@j&jahzL+c1Fb4Gl^h}@1TsE*FSnPo_wepT zM9Mv-0{X}s&-|wTlm3AAoADjoNfl4Q@{ZR#>)Dxaz8N?EX@?(gwV!1)yA+;3VYn+0 zIngsnMSo(VC=Y1A(_rOYi11*Xr(TEmk?7fUlbvY)Z`ihDm+OG~iQk++R4ZArqpvxE1xGTA?>Y(*~UebgJk~(R77Q@d`5lO%;?g)=+GSN+Cx*0CqBwe=8Y}W>IBZR zg`II)rG=~~wx2A1yc4Ah`y<GXu|D42Gikfu<>sVozxbe6T5U=0QvIGL}zBr@j0iiwA)sMP2pm>8W zpcVW$ZPM$P9Pv$cfiRrq~Hah&70PZ=zb4D%f zaGoplNaS%{RNPnmCjtUc!(B>tRGvZ0CRK$pT0F>KoSPR8rK39Ea{L-plJ9dY&F^8e zZ_1_0NlZCU{Y|LdCIkgrs--qiotuqKJlkrorXCX@-eAE$hL|yqnavCAWLV=*5uBs* zd~Dri=Kh9QaSS0{SYKIhuCH!xT!g3WffRm{ Date: Tue, 21 Nov 2017 17:16:39 -0800 Subject: [PATCH 3/3] More cleanup --- .gitignore | 2 + .../Example-checkpoint.ipynb | 752 ------------------ .../Figures-checkpoint.ipynb | 6 - .../.~lock.lipidomic_conversion.csv# | 1 - .../.~lock.new_lipidomic_abundances.csv# | 1 - .../.~lock.new_lipidomic_conversion.csv# | 1 - 6 files changed, 2 insertions(+), 761 deletions(-) delete mode 100644 Example_usage/.ipynb_checkpoints/Example-checkpoint.ipynb delete mode 100644 Example_usage/.ipynb_checkpoints/Figures-checkpoint.ipynb delete mode 100644 Example_usage/.~lock.lipidomic_conversion.csv# delete mode 100644 Example_usage/.~lock.new_lipidomic_abundances.csv# delete mode 100644 Example_usage/.~lock.new_lipidomic_conversion.csv# diff --git a/.gitignore b/.gitignore index 166fbe0..5ac5d3e 100644 --- a/.gitignore +++ b/.gitignore @@ -2,3 +2,5 @@ *.egg-info gurobi.log *.swp +.ipynb_checkpoints +*.csv# diff --git a/Example_usage/.ipynb_checkpoints/Example-checkpoint.ipynb b/Example_usage/.ipynb_checkpoints/Example-checkpoint.ipynb deleted file mode 100644 index d61bed6..0000000 --- a/Example_usage/.ipynb_checkpoints/Example-checkpoint.ipynb +++ /dev/null @@ -1,752 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# BOFdat usage example" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Make sure dependencies are installed\n", - "import cobra\n", - "import BOFdat as bd\n", - "import pandas as pd\n", - "from Bio import SeqIO\n", - "from cobra.util.solver import linear_reaction_coefficients" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Generating stoichiometric coefficients for the biomass objective function of *E.coli* genome-scale model *i*ML1515\n", - "\n", - "The weight percentage and abundance of each molecule in the cell may vary from an organism to another and vary between growth conditions for a given organism [1,2]. BOFdat allows to incorporate macromolecular cell composition obtained from literature or new experiments to generate new stoichiometric coefficients for your model's biomass objective function (BOF). Once weight percentages are obtained, OMIC data can be incorporated to buff the coefficients and fit to experimental reality. \n", - "\n", - "#### Steps\n", - "\n", - "The following example will lead you through all the necessary steps for the generation of the BOF stoichiometric coefficients (BOFsc) for *E.coli* K12 MG1655 GEM *i*ML1515 [3]. \n", - "\n", - "1. Obtain the macromolecular composition of the organism\n", - "\n", - "2. Obtain OMICs experimental data\n", - "\n", - "3. Generate BOFsc\n", - "\n", - "4. Generate NGAM and GAM\n", - "\n", - "5. Update BOF (BOFdat!)\n", - "\n", - "\n", - "#### Sources\n", - "\n", - "[1] Dennis P. Patrick and Bremmer Hans. (1974) Macromolecular composition during steady-state growth of *Escherichia coli* B/r. Journal of bacteriology\n", - "\n", - "\n", - "[2] Benjamin Volkmer and Matthias Heinemann. (2011) Condition-Dependent Cell Volume and Concentration of Escherichia coli to Facilitate Data Conversion for Systems Biology Modeling. PLoS One\n", - "\n", - "\n", - "[3] Jonathan M Monk, Colton J Lloyd, Elizabeth Brunk, Nathan Mih, Anand Sastry, Zachary King, Rikiya Takeuchi, Wataru Nomura, Zhen Zhang, Hirotada Mori, Adam M Feist and Bernhard O Palsson. (2017) *i*ML1515, a knowledgebase that computes Escherichia coli traits. Nat. Biotech.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 1. Obtain the macromolecular compositon of the organism\n", - "\n", - "*E.coli* has been characterized thoroughly in literature. The BOFsc used in *i*AF1260 [4] are the same in *i*ML1515 [3] and were obtained from Neidhart *et. al* [5].\n", - "\n", - "**Note:** The package also provides the option to include the percentage of each type of RNA molecule in the cell (ribosomal, transfer and messenger). The default values are rRNA: 0.9, tRNA 0.05 and mRNA: 0.05.\n", - "\n", - "#### Sources\n", - "\n", - "[4] Adam M Feist, Christopher S Henry, Jennifer L Reed, Markus Krummenacker, Andrew R Joyce, Peter D Karp, Linda J Broadbelt, Vassily Hatzimanikatis and Bernhard Ø Palsson. (2007) A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol. Syst. Bio. \n", - "\n", - "[5] Neidhardt FC, Ingraham JL, Schaechter M (1990) Physiology of the Bacterial Cell: a Molecular Approach. Sinauer Associates: Sunderland, Mass" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Set parameters based on dry weight composition\n", - "DNA_RATIO = 0.031\n", - "RNA_RATIO = 0.205\n", - "PROTEIN_RATIO = 0.55\n", - "LIPID_RATIO = 0.1\n", - "METABOLITE_RATIO = 0.1" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 2. Obtain OMICs experimental data\n", - "\n", - "Your genome should have a GenBank annotated file. This file should be provided in a BioPython supported format (.gb, .gbff). \n", - "\n", - "Search in literature allowed to find multiple OMICs dataset for different macromolecules that can be used to generate stoichiometric coefficients [6,7,8]. The data should be converted into a 2 column csv file. \n", - "The genome file should be provided in a standard BioPython supported format (.faa or .fna) and is used to calculate the abundance of each base in the genome.\n", - "\n", - "Transcriptomic and proteomic files are 2 column csv files where the first column is the **gene identifier ** and the second column is the relative abundance of each of these genes in the cell. \n", - "\n", - "Unlike DNA, RNA and proteins that are standard amongst every known life form, the lipid and metabolites in different organisms may vary. Hence a conversion file is required. This first column of this file is the original name of the compound and the second is the target identifier that this compound should have in your model. The first column of the abundance file gives the compound identifier in the model and the second column gives the abundance of that compound in the OMIC dataset.\n", - "\n", - "#### Sources\n", - "\n", - "[6] Sang Woo Seo, Donghyuk Kim, Haythem Latif, Edward J. O’Brien, Richard Szubin & Bernhard O. Palsson. (2014) Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli. Nat. Comm. \n", - "\n", - "\n", - "[7] Alexander Schmidt, Karl Kochanowski, Silke Vedelaar, Erik Ahrné, Benjamin Volkmer, Luciano Callipo, Kèvin Knoops, Manuel Bauer, Ruedi Aebersold and Matthias Heinemann. (2016) The quantitative and condition-dependent *Escherichia coli* proteome. Nat. Biotech. \n", - "\n", - "\n", - "[8] Kian-Kai Cheng, Baek-Seok Lee, Takeshi Masuda, Takuro Ito, Kazutaka Ikeda, Akiyoshi Hirayama, Lingli Deng, Jiyang Dong, Kazuyuki Shimizu, Tomoyoshi Soga, Masaru Tomita, Bernhard O. Palsson and Martin Robert. (2014) Global metabolic network reorganization by adaptive mutations allows fast growth of Escherichia coli on glycerol. Nat Comm." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Give the path to each file as function parameters\n", - "#Genome file in BioPython supported format (.faa, .fna) and GenBank file \n", - "#also in BioPython supported format (.gb, .gbff)\n", - "genome = 'Ecoli_DNA.fna'\n", - "genbank = 'Ecoli_K12_MG1655.gbff'\n", - "\n", - "#OMICs data as a 2 column csv file, gene and abundance\n", - "transcriptomic = 'trasncriptomic.csv'\n", - "proteomic = 'proteomic.csv'\n", - "\n", - "#Lipidomic abundances and conversion to model identifier\n", - "lipidomic_abundances = 'lipidomic_abundances.csv'\n", - "lipidomic_conversion = 'lipidomic_conversion.csv'\n", - "\n", - "#Metabolomic abundances and conversion to model identifier\n", - "metabolomic_abundances = 'metabolomic_abundances.csv'\n", - "metabolomic_conversion = 'metabolomic_conversion.csv'\n", - "\n", - "#The model for which the coefficients are generated\n", - "model = 'iML1515.json'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 3. Generate BOFsc\n", - "\n", - "BOFdat operates with a single get_coefficient function for each macromolecule used. Input the parameters determined above as function parameters. Each function outputs a dictionary of metabolite and stoichiometric coefficients. The dictionary can be used to update the BOF (Step 5)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Call get_coefficient() for each macromolecule category\n", - "dna_coefficients = BOFdat.DNA.get_coefficients()\n", - "rna_coefficients = BOFdat.RNA.get_coefficients()\n", - "prot_coefficients = BOFdat.protein.get_coefficients()\n", - "lipid_coefficients = BOFdat.lipid.get_coefficients()\n", - "metab_coefficients = BOFdat.metabolite.get_coefficients()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### 4. Generate GAM and NGAM\n", - "\n", - "Growth-associated maintenance (GAM) is the ATP cost related to growth. This includes the polymerization cost of each macromolecule. This cost is unaccounted for in the BOF because the model synthesizes the building blocks of each macromolecule in sufficient quantity to reflect the cell composition but not the cost of assembling those building blocks together. The GAM can be calculated experimentally by growing the bacteria on different sources of carbon at different starting concentrations. The carbon source should be the sole source of carbon in the media and its concentration should be measured after a given time. These remaining concentrations along with the excretion products are used by the package to constrain the model and calculate the ATP cost of growth. \n", - "\n", - "The file format is shown in the image below:\n", - "\n", - "\n", - "\n", - "\n", - "The carbon sources are in the first column. The second column entails \n", - "Non growth-associated maintenance (NGAM) is the ATP cost of sustaining life without providing and " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## *E. coli* parameters\n", - "\n", - "The *E. coli* cell grown in 40 min at 37C in glucose minimal media is chosen in this study.\n", - "The \n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Set-up parameters for the cell\n", - "#Parameters are issued from \n", - "CELL_density = 1.105\n", - "CELL_VOLUME = 3.0\n", - "CELL_WEIGHT = 2.8\n", - "PROTEIN_RATIO = 0.55\n", - "DNA_RATIO = 0.031\n", - "TOTAL_RNA_RATIO = 0.205" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Get the GenBank annotation file\n", - "genbank_path = '/home/jean-christophe/Documents/Maitrise_UCSD/GenBank_files/Ecoli_K12_MG1655.gbff'" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Get the transcriptomic data\n", - "transcriptomic = pd.read_csv('K12_RNAseq_wt_glc.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "transcriptomic_final = pd.DataFrame({'gene_ID':transcriptomic['Unnamed: 0'],'Mean':transcriptomic.mean(axis=1)},\n", - " columns=['gene_ID','Mean'])\n", - "transcriptomic_final.to_csv('/home/jean-christophe/Documents/Maitrise_UCSD/biomass/test_ecoli/transcriptomic_wt.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Get the proteomic data\n", - "proteomic = pd.read_csv('proteomic_final.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Get the model\n", - "model = cobra.io.load_json_model('iML1515.json')" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Reaction identifierEc_biomass_iML1515_WT_75p37M
NameE. coli biomass objective function (iML1515) - WT - with 75.37 GAM estimate
Memory address0x07f9c2b669450
Stoichiometry\n", - "

0.000223 10fthf_c + 0.000223 2dmmql8_c + 2.5e-05 2fe2s_c + 0.000248 4fe4s_c + 0.000223 5mthf_c + 0.000279 accoa_c + 0.000223 adocbl_c + 0.499149 ala__L_c + 0.000223 amet_c + 0.28742 arg__L_c + 0.234232 asn__L_c + 0.234232 asp__L_c + 226.48169 atp_c + 2e-06 btn_c + 0.004952 ca2_c + 0.000223 chor_c + 0.004952 cl_c + 0.002944 clpn160_p + 0.00229 clpn161_p + 0.00118 clpn181_p + 0.000168 coa_c + 2.4e-05 cobalt2_c + 0.008151 colipa_e + 0.129799 ctp_c + 0.000674 cu2_c + 0.088988 cys__L_c + 0.024805 datp_c + 0.025612 dctp_c + 0.025612 dgtp_c + 0.024805 dttp_c + 0.000223 enter_c + 0.000223 fad_c + 0.006388 fe2_c + 0.007428 fe3_c + 0.255712 gln__L_c + 0.255712 glu__L_c + 0.595297 gly_c + 0.154187 glycogen_c + 0.000223 gthrd_c + 0.209121 gtp_c + 70.028756 h2o_c + 0.000223 hemeO_c + 0.092056 his__L_c + 0.282306 ile__L_c + 0.18569 k_c + 0.437778 leu__L_c + 3e-06 lipopb_c + 0.333448 lys__L_c + 3.1e-05 malcoa_c + 0.149336 met__L_c + 0.008253 mg2_c + 0.000223 mlthf_c + 0.000658 mn2_c + 7e-06 mobd_c + 7e-06 mococdp_c + 7e-06 mocogdp_c + 0.000223 mql8_c + 0.001345 murein3p3p_p + 0.000605 murein3px4p_p + 0.005381 murein4p4p_p + 0.005448 murein4px4p_p + 0.000673 murein4px4px4p_p + 0.001787 nad_c + 4.5e-05 nadh_c + 0.000112 nadp_c + 0.000335 nadph_c + 0.012379 nh4_c + 0.000307 ni2_c + 0.044164 pe160_p + 0.03435 pe161_p + 0.017704 pe181_p + 0.010599 pg160_p + 0.008244 pg161_p + 0.004249 pg181_p + 0.180021 phe__L_c + 0.000223 pheme_c + 0.214798 pro__L_c + 0.03327 ptrc_c + 0.000223 pydx5p_c + 0.000223 q8h2_c + 0.000223 ribflv_c + 0.209684 ser__L_c + 0.000223 sheme_c + 0.004126 so4_c + 0.006744 spmd_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.246506 thr__L_c + 0.055234 trp__L_c + 0.133993 tyr__L_c + 5.5e-05 udcpdp_c + 0.140101 utp_c + 0.411184 val__L_c + 0.000324 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.749831 ppi_c

\n", - "

0.000223 10-Formyltetrahydrofolate + 0.000223 2-Demethylmenaquinol 8 + 2.5e-05 [2Fe-2S] iron-sulfur cluster + 0.000248 [4Fe-4S] iron-sulfur cluster + 0.000223 5-Methyltetrahydrofolate + 0.000279 Acetyl-CoA + 0.000223 Adenosylcobalamin + 0.499149 L-Alanine + 0.000223 S-Adenosyl-L-methionine + 0.28742 L-Arginine + 0.234232 L-Asparagine + 0.234232 L-Aspartate + 226.48169 ATP + 2e-06 Biotin + 0.004952 Calcium + 0.000223 chorismate + 0.004952 Chloride + 0.002944 cardiolipin (tetrahexadecanoyl, n-C16:0) + 0.00229 cardiolipin (tetrahexadec-9-enoyl, n-C16:1) + 0.00118 cardiolipin (tetraoctadec-11-enoyl, n-C18:1) + 0.000168 Coenzyme A + 2.4e-05 Co2+ + 0.008151 core oligosaccharide lipid A + 0.129799 CTP + 0.000674 Cu2+ + 0.088988 L-Cysteine + 0.024805 dATP + 0.025612 dCTP + 0.025612 dGTP + 0.024805 dTTP + 0.000223 Enterochelin + 0.000223 Flavin adenine dinucleotide oxidized + 0.006388 Fe2+ + 0.007428 Fe3+ + 0.255712 L-Glutamine + 0.255712 L-Glutamate + 0.595297 Glycine + 0.154187 glycogen + 0.000223 Reduced glutathione + 0.209121 GTP + 70.028756 H2O + 0.000223 Heme O + 0.092056 L-Histidine + 0.282306 L-Isoleucine + 0.18569 potassium + 0.437778 L-Leucine + 3e-06 lipoate (protein bound) + 0.333448 L-Lysine + 3.1e-05 Malonyl-CoA + 0.149336 L-Methionine + 0.008253 magnesium + 0.000223 5,10-Methylenetetrahydrofolate + 0.000658 Mn2+ + 7e-06 Molybdate + 7e-06 molybdopterin cytosine dinucleotide + 7e-06 molybdopterin guanine dinucleotide + 0.000223 Menaquinol 8 + 0.001345 two linked disacharide tripeptide murein units (uncrosslinked, middle of chain) + 0.000605 two disacharide linked murein units, tripeptide crosslinked tetrapeptide (A2pm->D-ala) (middle of chain) + 0.005381 two linked disacharide tetrapeptide murein units (uncrosslinked, middle of chain) + 0.005448 two disacharide linked murein units, tetrapeptide corsslinked tetrapeptide (A2pm->D-ala) (middle of chain) + 0.000673 three disacharide linked murein units (tetrapeptide crosslinked tetrapeptide (A2pm->D-ala) & tetrapeptide corsslinked tetrapeptide (A2pm->D-ala)) (middle of chain) + 0.001787 Nicotinamide adenine dinucleotide + 4.5e-05 Nicotinamide adenine dinucleotide - reduced + 0.000112 Nicotinamide adenine dinucleotide phosphate + 0.000335 Nicotinamide adenine dinucleotide phosphate - reduced + 0.012379 Ammonium + 0.000307 nickel + 0.044164 phosphatidylethanolamine (dihexadecanoyl, n-C16:0) + 0.03435 phosphatidylethanolamine (dihexadec-9enoyl, n-C16:1) + 0.017704 phosphatidylethanolamine (dioctadec-11-enoyl, n-C18:1) + 0.010599 Phosphatidylglycerol (dihexadecanoyl, n-C16:0) + 0.008244 Phosphatidylglycerol (dihexadec-9-enoyl, n-C16:1) + 0.004249 Phosphatidylglycerol (dioctadec-11-enoyl, n-C18:1) + 0.180021 L-Phenylalanine + 0.000223 Protoheme + 0.214798 L-Proline + 0.03327 Putrescine + 0.000223 Pyridoxal 5'-phosphate + 0.000223 Ubiquinol-8 + 0.000223 Riboflavin + 0.209684 L-Serine + 0.000223 Siroheme + 0.004126 Sulfate + 0.006744 Spermidine + 9.8e-05 Succinyl-CoA + 0.000223 5,6,7,8-Tetrahydrofolate + 0.000223 Thiamine diphosphate + 0.246506 L-Threonine + 0.055234 L-Tryptophan + 0.133993 L-Tyrosine + 5.5e-05 Undecaprenyl diphosphate + 0.140101 UTP + 0.411184 L-Valine + 0.000324 Zinc --> 75.37723 ADP + 75.37723 H+ + 75.37323 Phosphate + 0.749831 Diphosphate

\n", - "
GPR
Lower bound0
Upper bound1000
\n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "linear_reaction_coefficients(model).keys()[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'0.000223 10fthf_c + 0.000223 2dmmql8_c + 2.5e-05 2fe2s_c + 0.000248 4fe4s_c + 0.000223 5mthf_c + 0.000279 accoa_c + 0.000223 adocbl_c + 0.499149 ala__L_c + 0.000223 amet_c + 0.28742 arg__L_c + 0.234232 asn__L_c + 0.234232 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.004952 ca2_c + 0.000223 chor_c + 0.004952 cl_c + 0.002944 clpn160_p + 0.00229 clpn161_p + 0.00118 clpn181_p + 0.000168 coa_c + 2.4e-05 cobalt2_c + 0.008151 colipa_e + 0.129799 ctp_c + 0.000674 cu2_c + 0.088988 cys__L_c + 0.024805 datp_c + 0.025612 dctp_c + 0.025612 dgtp_c + 0.024805 dttp_c + 0.000223 enter_c + 0.000223 fad_c + 0.006388 fe2_c + 0.007428 fe3_c + 0.255712 gln__L_c + 0.255712 glu__L_c + 0.595297 gly_c + 0.154187 glycogen_c + 0.000223 gthrd_c + 0.209121 gtp_c + 70.028756 h2o_c + 0.000223 hemeO_c + 0.092056 his__L_c + 0.282306 ile__L_c + 0.18569 k_c + 0.437778 leu__L_c + 3e-06 lipopb_c + 0.333448 lys__L_c + 3.1e-05 malcoa_c + 0.149336 met__L_c + 0.008253 mg2_c + 0.000223 mlthf_c + 0.000658 mn2_c + 7e-06 mobd_c + 7e-06 mococdp_c + 7e-06 mocogdp_c + 0.000223 mql8_c + 0.001345 murein3p3p_p + 0.000605 murein3px4p_p + 0.005381 murein4p4p_p + 0.005448 murein4px4p_p + 0.000673 murein4px4px4p_p + 0.001787 nad_c + 4.5e-05 nadh_c + 0.000112 nadp_c + 0.000335 nadph_c + 0.012379 nh4_c + 0.000307 ni2_c + 0.044164 pe160_p + 0.03435 pe161_p + 0.017704 pe181_p + 0.010599 pg160_p + 0.008244 pg161_p + 0.004249 pg181_p + 0.180021 phe__L_c + 0.000223 pheme_c + 0.214798 pro__L_c + 0.03327 ptrc_c + 0.000223 pydx5p_c + 0.000223 q8h2_c + 0.000223 ribflv_c + 0.209684 ser__L_c + 0.000223 sheme_c + 0.004126 so4_c + 0.006744 spmd_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.246506 thr__L_c + 0.055234 trp__L_c + 0.133993 tyr__L_c + 5.5e-05 udcpdp_c + 0.140101 utp_c + 0.411184 val__L_c + 0.000324 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.749831 ppi_c'" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#The biomass objective function name is Ec_biomass_iML1515_core_75p37M\n", - "model.reactions.Ec_biomass_iML1515_WT_75p37M.reaction" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Generate new coefficients for DNA\n", - "CELL_density = 1.105\n", - "CELL_VOLUME = 3.0\n", - "CELL_WEIGHT = 2.8\n", - "\n", - "DNA_RATIO = 0.031\n", - "dna_ecoli = biomass.DNA()\n", - "dna_coeff = biomass.DNA.get_coefficients(dna_ecoli,'Ecoli_DNA.fna','iML1515.json',CELL_WEIGHT=CELL_WEIGHT,DNA_RATIO=DNA_RATIO)" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{: 0.015942933529341247,\n", - " : 0.0156289555189538,\n", - " : 0.015666598798418658,\n", - " : 0.017017910567671587}" - ] - }, - "execution_count": 44, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dna_coeff" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Found datp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 98 metabolites\n", - "The actual model None solves in and its biomass contains 99 metabolites\n", - "0.000223 10fthf_c + 0.000223 2dmmql8_c + 2.5e-05 2fe2s_c + 0.000248 4fe4s_c + 0.000223 5mthf_c + 0.000279 accoa_c + 0.000223 adocbl_c + 0.499149 ala__L_c + 0.000223 amet_c + 0.28742 arg__L_c + 0.234232 asn__L_c + 0.234232 asp__L_c + 226.48169 atp_c + 2e-06 btn_c + 0.004952 ca2_c + 0.000223 chor_c + 0.004952 cl_c + 0.002944 clpn160_p + 0.00229 clpn161_p + 0.00118 clpn181_p + 0.000168 coa_c + 2.4e-05 cobalt2_c + 0.008151 colipa_e + 0.129799 ctp_c + 0.000674 cu2_c + 0.088988 cys__L_c + 0.0156665987984 datp_c + 0.025612 dctp_c + 0.025612 dgtp_c + 0.024805 dttp_c + 0.000223 enter_c + 0.000223 fad_c + 0.006388 fe2_c + 0.007428 fe3_c + 0.255712 gln__L_c + 0.255712 glu__L_c + 0.595297 gly_c + 0.154187 glycogen_c + 0.000223 gthrd_c + 0.209121 gtp_c + 70.028756 h2o_c + 0.000223 hemeO_c + 0.092056 his__L_c + 0.282306 ile__L_c + 0.18569 k_c + 0.437778 leu__L_c + 3e-06 lipopb_c + 0.333448 lys__L_c + 3.1e-05 malcoa_c + 0.149336 met__L_c + 0.008253 mg2_c + 0.000223 mlthf_c + 0.000658 mn2_c + 7e-06 mobd_c + 7e-06 mococdp_c + 7e-06 mocogdp_c + 0.000223 mql8_c + 0.001345 murein3p3p_p + 0.000605 murein3px4p_p + 0.005381 murein4p4p_p + 0.005448 murein4px4p_p + 0.000673 murein4px4px4p_p + 0.001787 nad_c + 4.5e-05 nadh_c + 0.000112 nadp_c + 0.000335 nadph_c + 0.012379 nh4_c + 0.000307 ni2_c + 0.044164 pe160_p + 0.03435 pe161_p + 0.017704 pe181_p + 0.010599 pg160_p + 0.008244 pg161_p + 0.004249 pg181_p + 0.180021 phe__L_c + 0.000223 pheme_c + 0.214798 pro__L_c + 0.03327 ptrc_c + 0.000223 pydx5p_c + 0.000223 q8h2_c + 0.000223 ribflv_c + 0.209684 ser__L_c + 0.000223 sheme_c + 0.004126 so4_c + 0.006744 spmd_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.246506 thr__L_c + 0.055234 trp__L_c + 0.133993 tyr__L_c + 5.5e-05 udcpdp_c + 0.140101 utp_c + 0.411184 val__L_c + 0.000324 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.749831 ppi_c\n", - "Found dgtp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 98 metabolites\n", - "The actual model None solves in and its biomass contains 99 metabolites\n", - "0.000223 10fthf_c + 0.000223 2dmmql8_c + 2.5e-05 2fe2s_c + 0.000248 4fe4s_c + 0.000223 5mthf_c + 0.000279 accoa_c + 0.000223 adocbl_c + 0.499149 ala__L_c + 0.000223 amet_c + 0.28742 arg__L_c + 0.234232 asn__L_c + 0.234232 asp__L_c + 226.48169 atp_c + 2e-06 btn_c + 0.004952 ca2_c + 0.000223 chor_c + 0.004952 cl_c + 0.002944 clpn160_p + 0.00229 clpn161_p + 0.00118 clpn181_p + 0.000168 coa_c + 2.4e-05 cobalt2_c + 0.008151 colipa_e + 0.129799 ctp_c + 0.000674 cu2_c + 0.088988 cys__L_c + 0.0156665987984 datp_c + 0.025612 dctp_c + 0.015628955519 dgtp_c + 0.024805 dttp_c + 0.000223 enter_c + 0.000223 fad_c + 0.006388 fe2_c + 0.007428 fe3_c + 0.255712 gln__L_c + 0.255712 glu__L_c + 0.595297 gly_c + 0.154187 glycogen_c + 0.000223 gthrd_c + 0.209121 gtp_c + 70.028756 h2o_c + 0.000223 hemeO_c + 0.092056 his__L_c + 0.282306 ile__L_c + 0.18569 k_c + 0.437778 leu__L_c + 3e-06 lipopb_c + 0.333448 lys__L_c + 3.1e-05 malcoa_c + 0.149336 met__L_c + 0.008253 mg2_c + 0.000223 mlthf_c + 0.000658 mn2_c + 7e-06 mobd_c + 7e-06 mococdp_c + 7e-06 mocogdp_c + 0.000223 mql8_c + 0.001345 murein3p3p_p + 0.000605 murein3px4p_p + 0.005381 murein4p4p_p + 0.005448 murein4px4p_p + 0.000673 murein4px4px4p_p + 0.001787 nad_c + 4.5e-05 nadh_c + 0.000112 nadp_c + 0.000335 nadph_c + 0.012379 nh4_c + 0.000307 ni2_c + 0.044164 pe160_p + 0.03435 pe161_p + 0.017704 pe181_p + 0.010599 pg160_p + 0.008244 pg161_p + 0.004249 pg181_p + 0.180021 phe__L_c + 0.000223 pheme_c + 0.214798 pro__L_c + 0.03327 ptrc_c + 0.000223 pydx5p_c + 0.000223 q8h2_c + 0.000223 ribflv_c + 0.209684 ser__L_c + 0.000223 sheme_c + 0.004126 so4_c + 0.006744 spmd_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.246506 thr__L_c + 0.055234 trp__L_c + 0.133993 tyr__L_c + 5.5e-05 udcpdp_c + 0.140101 utp_c + 0.411184 val__L_c + 0.000324 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.749831 ppi_c\n", - "Found dttp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 98 metabolites\n", - "The actual model None solves in and its biomass contains 99 metabolites\n", - "0.000223 10fthf_c + 0.000223 2dmmql8_c + 2.5e-05 2fe2s_c + 0.000248 4fe4s_c + 0.000223 5mthf_c + 0.000279 accoa_c + 0.000223 adocbl_c + 0.499149 ala__L_c + 0.000223 amet_c + 0.28742 arg__L_c + 0.234232 asn__L_c + 0.234232 asp__L_c + 226.48169 atp_c + 2e-06 btn_c + 0.004952 ca2_c + 0.000223 chor_c + 0.004952 cl_c + 0.002944 clpn160_p + 0.00229 clpn161_p + 0.00118 clpn181_p + 0.000168 coa_c + 2.4e-05 cobalt2_c + 0.008151 colipa_e + 0.129799 ctp_c + 0.000674 cu2_c + 0.088988 cys__L_c + 0.0156665987984 datp_c + 0.025612 dctp_c + 0.015628955519 dgtp_c + 0.0159429335293 dttp_c + 0.000223 enter_c + 0.000223 fad_c + 0.006388 fe2_c + 0.007428 fe3_c + 0.255712 gln__L_c + 0.255712 glu__L_c + 0.595297 gly_c + 0.154187 glycogen_c + 0.000223 gthrd_c + 0.209121 gtp_c + 70.028756 h2o_c + 0.000223 hemeO_c + 0.092056 his__L_c + 0.282306 ile__L_c + 0.18569 k_c + 0.437778 leu__L_c + 3e-06 lipopb_c + 0.333448 lys__L_c + 3.1e-05 malcoa_c + 0.149336 met__L_c + 0.008253 mg2_c + 0.000223 mlthf_c + 0.000658 mn2_c + 7e-06 mobd_c + 7e-06 mococdp_c + 7e-06 mocogdp_c + 0.000223 mql8_c + 0.001345 murein3p3p_p + 0.000605 murein3px4p_p + 0.005381 murein4p4p_p + 0.005448 murein4px4p_p + 0.000673 murein4px4px4p_p + 0.001787 nad_c + 4.5e-05 nadh_c + 0.000112 nadp_c + 0.000335 nadph_c + 0.012379 nh4_c + 0.000307 ni2_c + 0.044164 pe160_p + 0.03435 pe161_p + 0.017704 pe181_p + 0.010599 pg160_p + 0.008244 pg161_p + 0.004249 pg181_p + 0.180021 phe__L_c + 0.000223 pheme_c + 0.214798 pro__L_c + 0.03327 ptrc_c + 0.000223 pydx5p_c + 0.000223 q8h2_c + 0.000223 ribflv_c + 0.209684 ser__L_c + 0.000223 sheme_c + 0.004126 so4_c + 0.006744 spmd_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.246506 thr__L_c + 0.055234 trp__L_c + 0.133993 tyr__L_c + 5.5e-05 udcpdp_c + 0.140101 utp_c + 0.411184 val__L_c + 0.000324 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.749831 ppi_c\n", - "Found dctp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 98 metabolites\n", - "The actual model None solves in and its biomass contains 99 metabolites\n", - "0.000223 10fthf_c + 0.000223 2dmmql8_c + 2.5e-05 2fe2s_c + 0.000248 4fe4s_c + 0.000223 5mthf_c + 0.000279 accoa_c + 0.000223 adocbl_c + 0.499149 ala__L_c + 0.000223 amet_c + 0.28742 arg__L_c + 0.234232 asn__L_c + 0.234232 asp__L_c + 226.48169 atp_c + 2e-06 btn_c + 0.004952 ca2_c + 0.000223 chor_c + 0.004952 cl_c + 0.002944 clpn160_p + 0.00229 clpn161_p + 0.00118 clpn181_p + 0.000168 coa_c + 2.4e-05 cobalt2_c + 0.008151 colipa_e + 0.129799 ctp_c + 0.000674 cu2_c + 0.088988 cys__L_c + 0.0156665987984 datp_c + 0.0170179105677 dctp_c + 0.015628955519 dgtp_c + 0.0159429335293 dttp_c + 0.000223 enter_c + 0.000223 fad_c + 0.006388 fe2_c + 0.007428 fe3_c + 0.255712 gln__L_c + 0.255712 glu__L_c + 0.595297 gly_c + 0.154187 glycogen_c + 0.000223 gthrd_c + 0.209121 gtp_c + 70.028756 h2o_c + 0.000223 hemeO_c + 0.092056 his__L_c + 0.282306 ile__L_c + 0.18569 k_c + 0.437778 leu__L_c + 3e-06 lipopb_c + 0.333448 lys__L_c + 3.1e-05 malcoa_c + 0.149336 met__L_c + 0.008253 mg2_c + 0.000223 mlthf_c + 0.000658 mn2_c + 7e-06 mobd_c + 7e-06 mococdp_c + 7e-06 mocogdp_c + 0.000223 mql8_c + 0.001345 murein3p3p_p + 0.000605 murein3px4p_p + 0.005381 murein4p4p_p + 0.005448 murein4px4p_p + 0.000673 murein4px4px4p_p + 0.001787 nad_c + 4.5e-05 nadh_c + 0.000112 nadp_c + 0.000335 nadph_c + 0.012379 nh4_c + 0.000307 ni2_c + 0.044164 pe160_p + 0.03435 pe161_p + 0.017704 pe181_p + 0.010599 pg160_p + 0.008244 pg161_p + 0.004249 pg181_p + 0.180021 phe__L_c + 0.000223 pheme_c + 0.214798 pro__L_c + 0.03327 ptrc_c + 0.000223 pydx5p_c + 0.000223 q8h2_c + 0.000223 ribflv_c + 0.209684 ser__L_c + 0.000223 sheme_c + 0.004126 so4_c + 0.006744 spmd_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.246506 thr__L_c + 0.055234 trp__L_c + 0.133993 tyr__L_c + 5.5e-05 udcpdp_c + 0.140101 utp_c + 0.411184 val__L_c + 0.000324 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.749831 ppi_c\n" - ] - } - ], - "source": [ - "update_ecoli = biomass.Update()\n", - "biomass.Update.update_biomass(update_ecoli,dna_coeff,model)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Generate new coefficients for RNA\n", - "rna = biomass.RNA()\n", - "transcriptomic = pd.read_csv('/home/jean-christophe/Documents/Maitrise_UCSD/biomass/test_ecoli/transcriptomic_wt.csv')\n", - "rna_coeff = biomass.RNA.get_coefficients(rna,genbank_path,\n", - " 'iML1515.json',transcriptomic,\n", - " CELL_WEIGHT=CELL_WEIGHT,TOTAL_RNA_RATIO=TOTAL_RNA_RATIO)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{: 0.097752775568245617,\n", - " : 0.10155095383786925,\n", - " : 0.10612200828008511,\n", - " : 0.10811360344042688}" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "rna_coeff" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Found atp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 0.101550953838 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.129417083268 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.0252687077394 datp_c + 0.0274482428511 dctp_c + 0.0252079927725 dgtp_c + 0.0257144089183 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.26316 glu__L_c + 0.612638 gly_c + 0.131845857854 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.119210701912 utp_c + 0.423162 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found gtp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 0.101550953838 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.129417083268 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.0252687077394 datp_c + 0.0274482428511 dctp_c + 0.0252079927725 dgtp_c + 0.0257144089183 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.26316 glu__L_c + 0.612638 gly_c + 0.10811360344 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.119210701912 utp_c + 0.423162 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found utp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 0.101550953838 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.129417083268 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.0252687077394 datp_c + 0.0274482428511 dctp_c + 0.0252079927725 dgtp_c + 0.0257144089183 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.26316 glu__L_c + 0.612638 gly_c + 0.10811360344 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.0977527755682 utp_c + 0.423162 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found ctp_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 0.101550953838 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.10612200828 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.0252687077394 datp_c + 0.0274482428511 dctp_c + 0.0252079927725 dgtp_c + 0.0257144089183 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.26316 glu__L_c + 0.612638 gly_c + 0.10811360344 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.0977527755682 utp_c + 0.423162 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n" - ] - } - ], - "source": [ - "update_rna = biomass.Update()\n", - "biomass.Update.update_biomass(update_rna,rna_coeff,model)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(75.37723, -226.48169000000001)\n" - ] - } - ], - "source": [ - "#Will have to fit GAM and NGAM\n", - "adp_coeff = model.reactions.Ec_biomass_iML1515_WT_75p37M.get_coefficient(model.metabolites.adp_c)\n", - "atp_coeff = model.reactions.Ec_biomass_iML1515_WT_75p37M.get_coefficient(model.metabolites.atp_c)\n", - "print(adp_coeff,atp_coeff)\n", - "#model.reactions.Ec_biomass_iML1515_WT_75p37M.add_metabolites({model.metabolites.atp_c:})\n", - "#model.reactions.Ec_biomass_iML1515_WT_75p37M.reaction" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Update the proteins\n", - "proteomic = pd.read_csv('/home/jean-christophe/Documents/Maitrise_UCSD/biomass/test_ecoli/proteomic.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "del proteomic['Unnamed: 0']" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "#Update the proteins\n", - "protein_update = biomass.Protein()\n", - "protein_coeff = biomass.Protein.get_coefficients(protein_update,\n", - " genbank_path,\n", - " 'iML1515.json',\n", - " proteomic,\n", - " CELL_WEIGHT=CELL_WEIGHT,\n", - " PROTEIN_RATIO=PROTEIN_RATIO\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Found glu__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.612638 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.423162 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found val__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.612638 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found trp__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.612638 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found met__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.612638 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found gly_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found asn__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found phe__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found pro__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found ser__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found gln__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found ile__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found leu__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found arg__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found cys__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found asp__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.247011681276 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.343161 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found lys__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.247011681276 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.240778115037 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found tyr__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.247011681276 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.240778115037 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.0797282631267 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found ala__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.627612911971 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.247011681276 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.240778115037 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.0227636368936 trp__L_c + 0.0797282631267 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found thr__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.627612911971 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.247011681276 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.240778115037 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.259631533661 thr__L_c + 0.0227636368936 trp__L_c + 0.0797282631267 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n", - "Found his__L_c in biomass reaction\n", - "The actual model None solves in and its biomass contains 69 metabolites\n", - "The actual model None solves in and its biomass contains 70 metabolites\n", - "0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.627612911971 ala__L_c + 0.000223 amet_c + 0.161929110332 arg__L_c + 0.161998059007 asn__L_c + 0.247011681276 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.0339389328166 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.141825601201 gln__L_c + 0.270793150946 glu__L_c + 0.613200453524 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.0699114757573 his__L_c + 0.250858500817 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.355860354476 leu__L_c + 0.240778115037 lys__L_c + 0.0942919276299 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.112190529727 phe__L_c + 0.000223 pheme_c + 0.190933683041 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.251744848146 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.259631533661 thr__L_c + 0.0227636368936 trp__L_c + 0.0797282631267 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.378209616073 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c\n" - ] - }, - { - "data": { - "text/plain": [ - "0.9702748855568007" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "update_protein = biomass.Update()\n", - "biomass.Update.update_biomass(update_protein,protein_coeff,model)\n", - "model.optimize().f" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'0.000223 10fthf_c + 2.6e-05 2fe2s_c + 0.000223 2ohph_c + 0.00026 4fe4s_c + 0.513689 ala__L_c + 0.000223 amet_c + 0.295792 arg__L_c + 0.241055 asn__L_c + 0.241055 asp__L_c + 75.55223 atp_c + 2e-06 btn_c + 0.005205 ca2_c + 0.005205 cl_c + 0.000576 coa_c + 2.5e-05 cobalt2_c + 0.133508 ctp_c + 0.000709 cu2_c + 0.09158 cys__L_c + 0.026166 datp_c + 0.027017 dctp_c + 0.027017 dgtp_c + 0.026166 dttp_c + 0.000223 fad_c + 0.006715 fe2_c + 0.007808 fe3_c + 0.26316 gln__L_c + 0.26316 glu__L_c + 0.612638 gly_c + 0.215096 gtp_c + 70.028756 h2o_c + 0.094738 his__L_c + 0.290529 ile__L_c + 0.195193 k_c + 0.019456 kdo2lipid4_e + 0.450531 leu__L_c + 0.343161 lys__L_c + 0.153686 met__L_c + 0.008675 mg2_c + 0.000223 mlthf_c + 0.000691 mn2_c + 7e-06 mobd_c + 0.013894 murein5px4p_p + 0.001831 nad_c + 0.000447 nadp_c + 0.013013 nh4_c + 0.000323 ni2_c + 0.063814 pe160_p + 0.075214 pe161_p + 0.185265 phe__L_c + 0.000223 pheme_c + 0.221055 pro__L_c + 0.000223 pydx5p_c + 0.000223 ribflv_c + 0.215792 ser__L_c + 0.000223 sheme_c + 0.004338 so4_c + 9.8e-05 succoa_c + 0.000223 thf_c + 0.000223 thmpp_c + 0.253687 thr__L_c + 0.056843 trp__L_c + 0.137896 tyr__L_c + 5.5e-05 udcpdp_c + 0.144104 utp_c + 0.423162 val__L_c + 0.000341 zn2_c --> 75.37723 adp_c + 75.37723 h_c + 75.37323 pi_c + 0.773903 ppi_c'" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "linear_reaction_coefficients(model).keys()[0].reaction" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.8769972144269684" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.optimize().f" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Example_usage/.ipynb_checkpoints/Figures-checkpoint.ipynb b/Example_usage/.ipynb_checkpoints/Figures-checkpoint.ipynb deleted file mode 100644 index 2fd6442..0000000 --- a/Example_usage/.ipynb_checkpoints/Figures-checkpoint.ipynb +++ /dev/null @@ -1,6 +0,0 @@ -{ - "cells": [], - "metadata": {}, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Example_usage/.~lock.lipidomic_conversion.csv# b/Example_usage/.~lock.lipidomic_conversion.csv# deleted file mode 100644 index 0ed132d..0000000 --- a/Example_usage/.~lock.lipidomic_conversion.csv# +++ /dev/null @@ -1 +0,0 @@ -,jean-christophe,jeanchristophe-OptiPlex-7040,20.11.2017 14:45,file:///home/jean-christophe/.config/libreoffice/4; \ No newline at end of file diff --git a/Example_usage/.~lock.new_lipidomic_abundances.csv# b/Example_usage/.~lock.new_lipidomic_abundances.csv# deleted file mode 100644 index 285061c..0000000 --- a/Example_usage/.~lock.new_lipidomic_abundances.csv# +++ /dev/null @@ -1 +0,0 @@ -,jean-christophe,jeanchristophe-OptiPlex-7040,20.11.2017 18:23,file:///home/jean-christophe/.config/libreoffice/4; \ No newline at end of file diff --git a/Example_usage/.~lock.new_lipidomic_conversion.csv# b/Example_usage/.~lock.new_lipidomic_conversion.csv# deleted file mode 100644 index 80c2f4f..0000000 --- a/Example_usage/.~lock.new_lipidomic_conversion.csv# +++ /dev/null @@ -1 +0,0 @@ -,jean-christophe,jeanchristophe-OptiPlex-7040,20.11.2017 18:25,file:///home/jean-christophe/.config/libreoffice/4; \ No newline at end of file