optional_nutrient_assessment.py

"""
Created by Juan M.
on 26/03/2021
"""

"""
This script reads individual GSMs from a file location. GSMs are then inspected to check if a 
nutrient that has been previously removed from the media has been synthesized intra-cellularly.
"""

import cobra
from cobra.exceptions import OptimizationError
import pandas as pd
import seaborn as sns
import os
import warnings
from os import listdir
from os.path import isfile, join

warnings.filterwarnings("error")

path_in = ''
path_out = ''

output_folder = ''

if not os.path.exists(path_out + output_folder):
    os.makedirs(path_out + output_folder)
    os.makedirs(path_out + output_folder + 'graphs/')
    os.makedirs(path_out + output_folder + 'compilation/')
    os.makedirs(path_out + output_folder + 'cluster/')

simple_sugars = {'D-glucose': "EX_glc_D(e)", 'fructose': "EX_fru(e)",
                 'galactose': "EX_gal(e)", 'mannose': "EX_man(e)",
                 'ribose': "EX_rib_D(e)", 'lactose': "EX_lcts(e)",
                 'L-fucose': "EX_fuc_L(e)", 'inulin': "EX_inulin(e)",
                 'maltose': "EX_malt(e)", 'D-xylose': "EX_xyl_D(e)",
                 'sucrose': "EX_sucr(e)", 'arabinose': "EX_arab_D(e)",
                 'ac_glucosamine': "EX_acgam(e)", 'chitobiose': "EX_chtbs(e)",
                 'glucosamine': "EX_gam(e)"
                 }

amino_acids = {'D-alanine': "EX_ala_D(e)", 'alanine': "EX_ala_L(e)",
               'asparagine': "EX_asn_L(e)", 'aspartate': "EX_asp_L(e)",
               'arginine': "EX_arg_L(e)", 'cysteine': "EX_cys_L(e)",
               'glutamine': "EX_gln_L(e)", 'glycine': "EX_gly(e)",
               'glutamate': "EX_glu_L(e)", 'histidine': "EX_his_L(e)",
               'isoleucine': "EX_ile_L(e)", 'leucine': "EX_leu_L(e)",
               'lysine': "EX_lys_L(e)", 'D-methionine': "EX_met_D(e)",
               'L-methionine': "EX_met_L(e)", 'phenylalanine': "EX_phe_L(e)",
               'proline': "EX_pro_L(e)", 'D-serine': "EX_ser_D(e)",
               'L-serine': "EX_ser_L(e)", 'threonine': "EX_thr_L(e)",
               'tryptophan': "EX_trp_L(e)", 'tyrosine': "EX_tyr_L(e)",
               'valine': "EX_val_L(e)", 'aspactic acid': "EX_asp_L(e)",
               'L-methionine sulfoxide': "EX_metsox_S_L(e)"
               }

cations = {
    'calcium': "EX_ca2(e)", 'cadmium': "EX_cd2(e)",
    'mercury': "EX_hg2(e)", 'magnesium': "EX_mg2(e)",
    'sodium': "EX_na1(e)", 'ammonia': "EX_nh4(e)",
    'potassium': "EX_k(e)", 'hydrogen ion': "EX_h(e)",
    'nitrogen': "EX_n2(e)"
}

anions = {
    'chloride ion': "EX_cl(e)", 'phosphate': "EX_pi(e)", 'sulfate': "EX_so4(e)",
    'sulfite': "EX_so3(e)", 'hydrogen sulfide': "EX_h2s(e)", 'hydrogen': "EX_h2(e)",
    'thiosulfate': "EX_tsul(e)", 'nitrite': "EX_no2(e)", 'nitrate': "EX_no3(e)",
}

metals = {
    'copper': "EX_cu2(e)", 'fe2': "EX_fe2(e)", 'cobalt': "EX_cobalt2(e)",
    'fe3': "EX_fe3(e)", 'manganese': "EX_mn2(e)", 'nickel': "EX_ni2(e)",
    'zinc': "EX_zn2(e)"
}

main_cofactors = {
    'biotin': "EX_btn(e)",
    'menaquionine-7': "EX_mqn7(e)",
    'cobalamin I': "EX_cbl1(e)",
    'menaquionine-8': "EX_mqn8(e)",
    'cobalamin II': "EX_cbl2(e)", 'nicotinic acid': "EX_nac(e)",
    'adenosylcobalamin': "EX_adpcbl(e)",
    'folic acid': "EX_fol(e)", 'niacinamide': "EX_ncam(e)",
    'nicotinamide ribotide': "EX_nmn(e)", 'pantothenic acid': "EX_pnto_R(e)",
    'pyridoxine': "EX_pydxn(e)",
    'reduced riboflavin': "EX_rbflvrd(e)",
    'riboflavin': "EX_ribflv(e)",
    'tetrahydrofolic acid': "EX_thf(e)",
    'thiamine': "EX_thm(e)", 'thiamine monophosphate': "EX_thmmp(e)",
    'demethylmenaquinone': "EX_2dmmq8(e)",
    'pyridoxal': "EX_pydx(e)",
    'pyridoxamine': "EX_pydam(e)",
    'ubiquinone-8': "EX_q8(e)"
}

secondary_cofactors = {
    'heme': "EX_pheme(e)", 'siroheme': "EX_sheme(e)",
    'thymidine': "EX_thymd(e)", 'cytosine': "EX_csn(e)",
    'uracil': "EX_ura(e)", 'adenosine': "EX_adn(e)",
    'adenine': "EX_ade(e)", 'guanine': "EX_gua(e)",
    'deoxyadenosine': "EX_dad_2(e)", 'deoxyguanosine': "EX_dgsn(e)",
    'guanosine': "EX_gsn(e)", 'guanosine triphosphate': "EX_gtp(e)",
    'Methylthioadenosine': "EX_5mta(e)", 'adenosine monophosphate': "EX_amp(e)",
    'S-adenosylmethionine': "EX_amet(e)", 'deoxyadenosine triphosphate': "EX_datp(e)",
    '5-Thymidylic acid': "EX_dtmp(e)", 'hypoxanthine': "EX_hxan(e)",
    'cytidine': "EX_cytd(e)", 'inosine': "EX_ins(e)",
    'xanthine': "EX_xan(e)", 'deoxycytidine': "EX_dcyt(e)",
    'uridine': "EX_uri(e)", 'deoxyinosine': "EX_din(e)",
    'cytidine monophosphate': "EX_cmp(e)", 'xanthosine': "EX_xtsn(e)"
}

dipeptide = {
    'Alanyl-glutamine': 'EX_alagln(e)', 'Carnosine': 'EX_alahis(e)',
    'Cysteinylglycine': 'EX_cgly(e)', 'Glycyl-L-asparagine': 'EX_glyasn(e)',
    'Glycyl-L-glutamine': 'EX_glygln(e)', 'Glycylleucine': 'EX_glyleu(e)',
    'Glycyl-L-methionine': 'EX_glymet(e)',
    'Gly-Cys': 'EX_glycys(e)', 'Glycyl-L-tyrosine': 'EX_glytyr(e)', 'L-cystine': "EX_Lcystin(e)",
    'Glycyl-Phenylalanine': 'EX_glyphe(e)', 'L-alanyl-L-threonine': 'EX_alathr(e)',
    'L-methionyl-L-alanine': 'EX_metala(e)', 'L-alanyl-L-leucine': 'EX_alaleu(e)',
    'Glycylproline': 'EX_glypro(e)', 'L-alanyl-L-aspartate': 'EX_alaasp(e)',
    'L-alanylglycine': 'EX_alagly(e)', 'Alanyl-glutamate': 'EX_alaglu(e)',
    'Glycyl-L-aspartate': 'EX_glyasp(e)', 'Glycyl-L-glutamate': 'EX_glyglu(e)'
}

fatty_acids = {
    'Stearic acid': 'EX_ocdca(e)', 'Myristic acid': 'EX_ttdca(e)',
    'Dodecanoic acid': 'EX_ddca(e)', 'Oleic acid': 'EX_ocdcea(e)'
}

bile_acids = {
    'Chenodeoxycholic acid-glycine': 'EX_dgchol(e)',
    'Glycocholic acid': 'EX_gchola(e)',
    'Taurocholic acid': 'EX_tchola(e)'
}

other = {
    'Glycerol 3-phosphate': 'EX_glyc3p(e)',
    '4-Aminobenzoate': 'EX_4abz(e)',
    'Glutathione': 'EX_gthrd(e)', 'Diaminoheptanedioate': 'EX_26dap_M(e)',
    'Dephospho-CoA': 'EX_dpcoa(e)', '1,2-Diacyl-sn-glycerol': 'EX_12dgr180(e)',
    'Methyl-Oxovaleric Acid': 'EX_3mop(e)',
    'Chorismate': 'EX_chor(e)',
    '4-Hydroxybenzoic acid': 'EX_4hbz(e)', 'Oxidized glutathione': 'EX_gthox(e)',
    'Putrescine': 'EX_ptrc(e)', 'Indole': 'EX_indole(e)',
    'Lanosterin': 'EX_lanost(e)',
    'Choline sulfate': 'EX_chols(e)',
    'Ketobutyric acid': 'EX_2obut(e)',
    'Glycolaldehyde': 'EX_gcald(e)',
    'Trimethylamine': 'EX_tma(e)', 'NADP': 'EX_nadp(e)',
    'Acetic acid': 'EX_ac(e)',
    'Formic acid': 'EX_for(e)',
    'Gamma-butyrobetaine': 'EX_gbbtn(e)',
    'Acetoacetic acid': 'EX_acac(e)',
    'Coenzyme A': 'EX_coa(e)',
    'Ethanolamine': 'EX_etha(e)',
    'Tetrathionate': 'EX_tet(e)',
    'Dehydro-deoxy-gluconate': 'EX_2ddglcn(e)',
    'Carbon dioxide': 'EX_co2(e)', 'Allantoin': 'EX_alltn(e)',
    'Cholesterol': 'EX_chsterol(e)', 'Formaldehyde': 'EX_fald(e)',
    'Water': 'EX_h2o(e)',
    'Phenylpyruvic acid': 'EX_phpyr(e)',
    'Urea': 'EX_urea(e)',
    'L-Lactic acid': 'EX_lac_L(e)',
    'D-Galacturonate': 'EX_galur(e)',
    'Citric acid': 'EX_cit(e)',
    'Malic acid': 'EX_mal_L(e)',
    'Acetylmannosamine': 'EX_acmana(e)', 'Glycerol': 'EX_glyc(e)',
    'Carnitine': "EX_crn(e)", 'Ornithine': "EX_orn(e)", 'Spermidine': 'EX_spmd(e)'
}

rich_media_no_explored_n = {}
rich_media_no_explored_n.update(simple_sugars)
rich_media_no_explored_n.update(amino_acids)
rich_media_no_explored_n.update(main_cofactors)
rich_media_no_explored_n.update(other)
rich_media_no_explored_n.update(bile_acids)
rich_media_no_explored_n.update(fatty_acids)
rich_media_no_explored_n.update(dipeptide)
rich_media_no_explored_n.update(main_cofactors)
rich_media_no_explored_n.update(secondary_cofactors)
rich_media_no_explored_n.update(metals)
rich_media_no_explored_n.update(anions)
rich_media_no_explored_n.update(cations)

explored_groups = {
    'B1': {'thiamine': "thm", 'thiamine monophosphate': "thmmp", 'thiamine pyrophosphate': "thmpp"},
    'B2': {'riboflavin': "ribflv", 'reduced riboflavin': "rbflvrd", 'flavin adenine dinucleotide': "fad",
           'flavin mononucleotide': "fmn"},
    'B3': {'nicotinic acid': "nac", 'niacinamide': "ncam", 'nicotinamide ribotide': "nmn",
           'nicotinamide adenine dinucleotide': "nad"},
    'B5': {'pantothenic acid': "pnto_R"},
    'B6': {'pyridoxine': "pydxn", 'pyridoxal': "pydx", 'pyridoxamine': "pydam", 'pyridoxal 5-phosphate': "pydx5p"},
    'B9': {'folic acid': "fol", 'tetrahydrofolic acid': "thf", '5-methyltetrahydrofolate': "5mthf"},
    'B12': {'cobalamin I': "cbl1", 'cobalamin II': "cbl2", 'adenosylcobalamin': "adocbl"},
    'K': {'menaquionine-7': "mqn7", 'menaquionine-8': "mqn8", 'demethylmenaquinone': "2dmmq8",
          'ubiquinone-8': "q8"}
}

# Creates a list of bacteria names (models) located in the path_in directory when running several microbes at once
models_in = [f for f in listdir(path_in) if isfile(join(path_in, f))]
models_in = [os.path.splitext(f)[0] for f in models_in]

rich_media_df = pd.DataFrame()

for ingredient in rich_media_no_explored_n:
    code = rich_media_no_explored_n[ingredient]
    new_ingredient = pd.DataFrame([100], index=[code])
    rich_media_df = pd.concat([rich_media_df, new_ingredient])

production_boolean_table = pd.DataFrame()

for name in models_in:

    print(name)
    microbe_boolean_table = pd.DataFrame()

    for explored_group in explored_groups:
        model = cobra.io.read_sbml_model(path_in + name + '.xml')

        media_dict = rich_media_df.to_dict()
        uptakes = media_dict[0]

        group_of_reactions = explored_groups[explored_group]

        for metabolite in group_of_reactions:
            reaction = group_of_reactions[metabolite]
            ex_reaction = 'EX_' + reaction + '(e)'
            if ex_reaction in uptakes:
                del uptakes[ex_reaction]
                
        value = 0

        for metabolite in group_of_reactions:
            reaction = group_of_reactions[metabolite]
            explored_metabolite = reaction + '[c]'
            ex_reaction = 'EX_' + reaction + '(e)'
            with model:
                medium = model.medium

                for ingredient in medium:
                    if ingredient not in uptakes:
                        medium[ingredient] = 0.0

                model.medium = medium
                if explored_metabolite in model.metabolites:
                    try:
                        solution = model.optimize()
                        if solution.objective_value is not None and solution.objective_value > 0.09 and solution.status != 'Infeasible':
                            metabolite_reactions = model.metabolites.get_by_id(explored_metabolite).summary().to_string()
                            if 'Empty DataFrame' not in metabolite_reactions:
                                print(explored_metabolite, 'HAS BEEN used in one or more reactions')
                                value = 1
                    except (UserWarning, OptimizationError):
                        value = 0

        group_test = pd.DataFrame([value], index=[explored_group])
        group_test.columns = [name]
        microbe_boolean_table = pd.concat([microbe_boolean_table, group_test])

    microbe_boolean_table = microbe_boolean_table.transpose()
    production_boolean_table = pd.concat([production_boolean_table, microbe_boolean_table])

production_boolean_table.to_csv(path_out + output_folder + 'compilation/synthesis_compilation.csv')

with open(path_out + output_folder + 'experimental_design.txt', 'w') as file:
    file.write('This results were generated using the optional_nutrient_assessment.py script\n\n')
    file.write('Using the following media:\n', str(rich_media_no_exp_source))