7. Loading and inspecting ME-models

In this tutorial we will load and inspect the reconstructed Bacillus subtilis ME-model.

7.1. Import libraries

[1]:

from coralme.builder.main import MEBuilder
import coralme

7.2. Load as a JSON

Load the ME-model coming out of the Troubleshooter

[2]:

me = coralme.io.json.load_json_me_model("./bsubtilis/MEModel-step3-bsubtilis-TS.json")

Adding Metabolites into the ME-model...                                    : 100.0%|██████████|  4630/ 4630 [00:00<00:00]
Adding ProcessData into the ME-model...                                    : 100.0%|██████████|  4752/ 4752 [00:00<00:00]
Adding Reactions into the ME-model...                                      : 100.0%|██████████|  7758/ 7758 [00:14<00:00]
Updating ME-model Reactions...                                             : 100.0%|██████████|  6369/ 6369 [00:21<00:00]

7.3. Load as a pickle

[ ]:

# me = coralme.io.pickle.load_pickle_me_model("./bsubtilis/MEModel-step3-bsubtilis-TS.pkl")

7.4. Inspecting ME-model properties

7.4.1. Summary of the ME-model

[3]:

me

[3]:
Name coralME
Memory address 7f1c5c495b10
Number of metabolites 4630
Number of reactions 7758
Number of genes 1154
Number of mRNA genes 1038
Number of rRNA genes 30
Number of tRNA genes 86
Objective expression dummy_reaction_FWD_SPONT
Compartments mc, c, e 
[4]:

print("ME-model has {} reactions".format(len(me.reactions)))

ME-model has 7758 reactions

[5]:

print("ME-model has {} metabolites".format(len(me.metabolites)))

ME-model has 4630 metabolites

[6]:

print("ME-model has {} genes".format(len(me.all_genes)))

ME-model has 1154 genes

7.4.2. Reactions

7.4.2.1. Metabolic reaction

[7]:

r = next(i for i in me.reactions if isinstance(i,coralme.core.reaction.MetabolicReaction))
r

[7]:
Reaction identifier23CN2P1_REV_BSU07840-MONOMER
Name
Memory address0x7f1b98d6c9d0
Stoichiometry

1.0 3amp_c + [4.47434028634533e-6*mu1] BSU07840-MONOMER + 1.0 h_c --> 1.0 23camp_c + 1.0 h2o_c

1.0 3 AMP C10H12N5O7P + [4.47434028634533e-6*mu1] BSU07840-MONOMER + 1.0 H+ --> 1.0 2',3'-Cyclic AMP + 1.0 H2O H2O

GPR
Lower bound0
Upper bound999999.0
Reaction typecoralme.core.reaction.MetabolicReaction
FluxME-model not optimized/feasible
Reduced costME-model not optimized/feasible
Bound violationME-model not optimized/feasible

7.4.2.2. Translation reaction

[8]:

r = next(i for i in me.reactions if isinstance(i,coralme.core.reaction.TranslationReaction))
r

[8]:
Reaction identifiertranslation_BSU00090
Name
Memory address0x7f1b9abcb310
Stoichiometry

1.0 10fthf_c + [0.00208119658119658*mu1] BSU01120-MONOMER + [4.27350427350427e-6*mu1] BSU01390-MONOMER + [4.27350427350427e-6*mu1] BSU15720-MONOMER + [4.27350427350427e-6*mu1] BSU15730-MONOMER + [0.00208119658119658*mu1] BSU16500-MONOMER + [4.27350427350427e-6*mu1] BSU16520-MONOMER + [8.54700854700855e-6*mu1] BSU16630-MONOMER + [4.27350427350427e-6*mu1] BSU25460-MONOMER + [4.27350427350427e-6*mu1] BSU25470-MONOMER + [4.27350427350427e-6*mu1] BSU25480-MONOMER + [4.27350427350427e-6*mu1] BSU28870-MONOMER + [0.000498399634202103*mu1 + 0.000195123456790123 + 0.0269135802469136*(0.222222222222222*mu1 + 0.087)/mu1] RNA_BSU00090 + [2.55589556001079e-8*mu1 + 1.00063311174422e-8] RNA_degradosome + 36.0 ala__L_c + 23.0 arg__L_c + 14.0 asn__L_c + 27.0 asp__L_c + [488.0 + 9.86382716049383*(0.222222222222222*mu1 + 0.087)/mu1] atp_c + 3.0 cys__L_c + [8.54700854700855e-6*mu1] generic_RF + [0.00208119658119658*mu1] generic_Tuf + 29.0 generic_tRNA_AAA_lys__L_c + 8.0 generic_tRNA_AAC_asn__L_c + 8.0...

1.0 10-Formyltetrahydrofolate + [0.00208119658119658*mu1] BSU01120-MONOMER + [4.27350427350427e-6*mu1] BSU01390-MONOMER + [4.27350427350427e-6*mu1] BSU15720-MONOMER + [4.27350427350427e-6*mu1] BSU15730-MONOMER + [0.00208119658119658*mu1] BSU16500-MONOMER + [4.27350427350427e-6*mu1] BSU16520-MONOMER + [8.54700854700855e-6*mu1] BSU16630-MONOMER + [4.27350427350427e-6*mu1] BSU25460-MONOMER + [4.27350427350427e-6*mu1] BSU25470-MONOMER + [4.27350427350427e-6*mu1] BSU25480-MONOMER + [4.27350427350427e-6*mu1] BSU28870-MONOMER + [0.000498399634202103*mu1 + 0.000195123456790123 + 0.0269135802469136*(0.222222222222222*mu1 + 0.087)/mu1] RNA_BSU00090 + [2.55589556001079e-8*mu1 + 1.00063311174422e-8] RNA_degradosome + 36.0 L-Alanine + 23.0 L-Arginine + 14.0 L-Asparagine + 27.0 L-Aspartate + [488.0 + 9.86382716049383*(0.222222222222222*mu1 + 0.087)/mu1] ATP C10H12N5O13P3 + 3.0 L-Cysteine + [8.54700854700855e-6*mu1] generic_RF + [0.00208119658119658*mu1] generic_Tuf + 29.0...

GPR
Lower bound0.0
Upper bound1000.0
Reaction typecoralme.core.reaction.TranslationReaction
FluxME-model not optimized/feasible
Reduced costME-model not optimized/feasible
Bound violationME-model not optimized/feasible

7.4.2.3. Transcription reaction

[9]:

r = next(i for i in me.reactions if isinstance(i,coralme.core.reaction.TranscriptionReaction))
r

[9]:
Reaction identifiertranscription_TU8J2-1243_from_BSU25200-MONOMER
Name
Memory address0x7f1b9aea4700
Stoichiometry

[4.27350427350427e-6*mu1] BSU00550-MONOMER_mod_mg2(1) + [4.27350427350427e-6*mu1] BSU01010-MONOMER + [4.27350427350427e-6*mu1] BSU16600-MONOMER + [4.27350427350427e-6*mu1] BSU27320-MONOMER + [4.27350427350427e-6*mu1] BSU37080-MONOMER_mod_mg2(3) + [0.00273829471591343*mu1 + 0.00107204238128011] RNAP_BSU25200MONOMER + 189.0 atp_c + 122 ctp_c + 111 gtp_c + 3.0 h2o_c + 154 utp_c --> 1.0 RNA_BSU23050 + 3.0 adp_c + 3.0 h_c + 183.35422381299998 mRNA_biomass + 3.0 pi_c + 573 ppi_c

[4.27350427350427e-6*mu1] BSU00550-MONOMER_mod_mg2(1) + [4.27350427350427e-6*mu1] BSU01010-MONOMER + [4.27350427350427e-6*mu1] BSU16600-MONOMER + [4.27350427350427e-6*mu1] BSU27320-MONOMER + [4.27350427350427e-6*mu1] BSU37080-MONOMER_mod_mg2(3) + [0.00273829471591343*mu1 + 0.00107204238128011] RNAP_BSU25200MONOMER + 189.0 ATP C10H12N5O13P3 + 122 CTP C9H12N3O14P3 + 111 GTP C10H12N5O14P3 + 3.0 H2O H2O + 154 UTP C9H11N2O15P3 --> 1.0 RNA_BSU23050 + 3.0 ADP C10H12N5O10P2 + 3.0 H+ + 183.35422381299998 mRNA_biomass + 3.0 Phosphate + 573 Diphosphate

GPR
Lower bound0.0
Upper bound1000.0
Reaction typecoralme.core.reaction.TranscriptionReaction
FluxME-model not optimized/feasible
Reduced costME-model not optimized/feasible
Bound violationME-model not optimized/feasible

7.4.2.4. Formation reaction

[10]:

r = next(i for i in me.reactions if isinstance(i,coralme.core.reaction.ComplexFormation))
r

[10]:
Reaction identifierformation_BSU00090-MONOMER
Name
Memory address0x7f1b98def070
Stoichiometry

4.0 protein_BSU00090 --> 1.0 BSU00090-MONOMER

4.0 protein_BSU00090 --> 1.0 BSU00090-MONOMER

GPR
Lower bound0.0
Upper bound1000.0
Reaction typecoralme.core.reaction.ComplexFormation
FluxME-model not optimized/feasible
Reduced costME-model not optimized/feasible
Bound violationME-model not optimized/feasible

7.4.2.5. tRNA Charging reaction

[11]:

r = next(i for i in me.reactions if isinstance(i,coralme.core.reaction.tRNAChargingReaction))
r

[11]:
Reaction identifiercharging_tRNA_BSU_tRNA_5_AUU
Name
Memory address0x7f1b9918bbe0
Stoichiometry

[4.27350427350427e-6*mu1*(0.000116266666666667*mu1 + 1.0000455184)] BSU15430-MONOMER_mod_zn2(2) + [0.000116266666666667*mu1 + 4.55184e-5] RNA_BSU_tRNA_5 + [0.000116266666666667*mu1 + 4.55184e-5] ile__L_c --> 1.0 generic_tRNA_AUU_ile__L_c

[4.27350427350427e-6*mu1*(0.000116266666666667*mu1 + 1.0000455184)] BSU15430-MONOMER_mod_zn2(2) + [0.000116266666666667*mu1 + 4.55184e-5] RNA_BSU_tRNA_5 + [0.000116266666666667*mu1 + 4.55184e-5] L-Isoleucine --> 1.0 generic_tRNA_AUU_ile__L_c

GPR
Lower bound0.0
Upper bound1000.0
Reaction typecoralme.core.reaction.tRNAChargingReaction
FluxME-model not optimized/feasible
Reduced costME-model not optimized/feasible
Bound violationME-model not optimized/feasible

7.4.2.6. Post-translational modification reaction

[12]:

r = next(i for i in me.reactions if isinstance(i,coralme.core.reaction.PostTranslationReaction))
r

[12]:
Reaction identifiertranslocation_BSU07840_Cell_Wall
Name
Memory address0x7f1b98956650
Stoichiometry

[0.101527777777778*mu1] BSU27650-MONOMER + [0.101527777777778*mu1] BSU35300-MONOMER + 58.480000000000004 atp_c + 58.480000000000004 h2o_c + 1.0 protein_BSU07840 + [0.101527777777778*mu1] secYEG --> 58.480000000000004 adp_c + 58.480000000000004 h_c + 58.480000000000004 pi_c + 1.0 protein_BSU07840_Cell_Wall

[0.101527777777778*mu1] BSU27650-MONOMER + [0.101527777777778*mu1] BSU35300-MONOMER + 58.480000000000004 ATP C10H12N5O13P3 + 58.480000000000004 H2O H2O + 1.0 protein_BSU07840 + [0.101527777777778*mu1] secYEG --> 58.480000000000004 ADP C10H12N5O10P2 + 58.480000000000004 H+ + 58.480000000000004 Phosphate + 1.0 protein_BSU07840_Cell_Wall

GPR
Lower bound0.0
Upper bound1000.0
Reaction typecoralme.core.reaction.PostTranslationReaction
FluxME-model not optimized/feasible
Reduced costME-model not optimized/feasible
Bound violationME-model not optimized/feasible

7.4.3. Mapped gene functions

[13]:

from collections import defaultdict
import pandas
d = defaultdict(int)
for g in me.all_genes:
    for f in g.functions:
        d[f] += 1
pandas.DataFrame.from_dict({"count":d})

[13]:
count
Translation 209
tRNA-Charging 135
Metabolic:S_Nucleotides_and_nucleic_acids 67
Metabolic:S_Coenzymes_and_prosthetic_groups 76
Metabolic:S_Amino_acids_and_related_molecules 155
Metabolic:S_Other_function 16
Transcription 46
Metabolic:S_Carbohydrates_and_related_molecules 148
Metabolic:S_Cell_wall 40
Metabolic:S_Lipids 55
Post-translation 13
Metabolic:S_Transport 235
Metabolic:Not Determined 14
Metabolic:S_Membrane_bioenergetics 47
Metabolic: No subsystem 8
Metabolic:S_Phosphate_and_sulfur 7

7.4.3.1. Inspecting functions of a gene

[14]:

g = me.all_genes.get_by_id("RNA_BSU37160")
g.functions

[14]:

{'Transcription'}

7.4.4. Complexes formed by a gene

[15]:

g = me.all_genes.get_by_id("RNA_BSU37160")
g.complexes

[15]:

{<Complex CPLX8J2-30_mod_zn2(1)_mod_mg2(2) at 0x7f1b9b1d9db0>,
 <RNAP RNAP_BSU00980MONOMER at 0x7f1b9b1da530>,
 <RNAP RNAP_BSU01730MONOMER at 0x7f1b9b1da5c0>,
 <RNAP RNAP_BSU04730MONOMER at 0x7f1b9b1da5f0>,
 <RNAP RNAP_BSU09520MONOMER at 0x7f1b9b1da4a0>,
 <RNAP RNAP_BSU13450MONOMER at 0x7f1b9b1da410>,
 <RNAP RNAP_BSU14730MONOMER at 0x7f1b9b1da4d0>,
 <RNAP RNAP_BSU15320MONOMER at 0x7f1b9b1da680>,
 <RNAP RNAP_BSU15330MONOMER at 0x7f1b9b1da560>,
 <RNAP RNAP_BSU16470MONOMER at 0x7f1b9b1da650>,
 <RNAP RNAP_BSU23100MONOMER at 0x7f1b9b1da500>,
 <RNAP RNAP_BSU23450MONOMER at 0x7f1b9b1da440>,
 <RNAP RNAP_BSU25200MONOMER at 0x7f1b9b1da620>,
 <RNAP RNAP_BSU27120MONOMER at 0x7f1b9b1da470>,
 <RNAP RNAP_BSU34200MONOMER at 0x7f1b9b1da3e0>,
 <RNAP RNAP_CPLX8J236 at 0x7f1b9b1da6b0>,
 <RNAP RNAP_MONOMER8J26 at 0x7f1b9b1da590>}

7.4.5. Sinks to be curated through manual curation

The Troubleshooter finds gaps that need to be curated to allow for growth. Most of these are cofactors that will require some synthesis pathways (e.g. 4fe4s), but others will only need some transporters (e.g. metal ions). This was run with curated files, so the following is empty.

[16]:

me.reactions.query("^TS_")

[16]:

[]