Updated figures for revised manuscript

Figures/Figure1_toy_ec_pam.py

@@ -2,6 +2,7 @@
 from cobra import Model, Reaction, Metabolite
 import matplotlib.pyplot as plt
 import matplotlib.gridspec as gridspec
+from mpl_toolkits.axes_grid1.inset_locator import inset_axes
 from PIL import Image
 Image.MAX_IMAGE_PIXELS = None #to make sure the image is loaded properly in high quality
 
@@ -79,7 +80,7 @@ def build_toy_gem():
     r1.add_metabolites({Metabolite('Substrate'): 1})
     # R2:
     r2 = model.reactions.get_by_id('R2')
-    r2.add_metabolites({Metabolite('Substrate'): -1, Metabolite('Intermediate'): 1, Metabolite('CO2'): 1})
+    r2.add_metabolites({Metabolite('Substrate'): -1, Metabolite('Intermediate'): 1, Metabolite('ATP'): 0.5})
     # R3:
     r3 = model.reactions.get_by_id('R3')
     r3.add_metabolites({Metabolite('Intermediate'): -1, Metabolite('Byproduct'):1, Metabolite('ATP'):1})
@@ -106,7 +107,7 @@ def build_toy_gem():
     return model
 
 def build_active_enzyme_sector(Config):
-    kcat_fwd = [1, 0.5, 1, 1, 0.5 ,0.45, 1.5]  # High turnover for exchange reactions
+    kcat_fwd = [1, 0.5, 1, 1, 0.5 ,0.45, 1.5]  # High turnover for exchange reactions [1, 0.5, 1, 1, 0.5 ,0.45, 1.5]
     kcat_rev = [kcat for kcat in kcat_fwd]
     rxn2kcat = {}
     for i in range(n-3): # all reactions have an enzyme, except excretion reactions
@@ -161,9 +162,9 @@ def run_simulations(pamodel, substrate_axis):
             'Ccsc':Ccsc, 'Cesc':Cesc,
             'x_axis_csc': x_axis_csc,'x_axis_esc': x_axis_esc}
 
-def plot_sensitivities(fig, grdspec, glc_rates, mu_list, tot_prot_csc, substrate_csc, e1_esc):
+def plot_sensitivities(fig, grdspec, glc_rates, mu_list, tot_prot_csc, substrate_csc, e1_esc, pie_data, pie_labels):
     gs = gridspec.GridSpecFromSubplotSpec(2, 1,
-                                          height_ratios=[1,1], hspace=0, subplot_spec=grdspec)
+                                          height_ratios=[1,2], hspace=0, subplot_spec=grdspec)
     sens_ax = fig.add_subplot(gs[1, 0])  # sensitivity coefficient linegraph
     mu_ax = fig.add_subplot(gs[0, 0], sharex=sens_ax) # mu vs v_s linegraph
 
@@ -173,28 +174,35 @@ def plot_sensitivities(fig, grdspec, glc_rates, mu_list, tot_prot_csc, substrate
     mu = mu_ax.plot(glc_rates, mu_list, color = 'black', linewidth= 3)#(35/255,158/255,137/255)
     mu_ax.xaxis.set_visible(False)
     # mu_ax.legend([mu], labels=['growth rate'], loc='center left')
-    mu_ax.set_ylabel('$v_{biomass} $ $(h^{-1})$', fontsize = FONTSIZE)
+    mu_ax.set_ylabel('$v_{biomass} $ $(h^{-1})$', fontsize = FONTSIZE*3/4)
     # add B panel annotation
-    mu_ax.annotate('B', xy=(0.01, 0.01), xycoords='data',
-                   xytext=(-0.1, 1.05), textcoords='axes fraction',
+    mu_ax.annotate('B', xy=(-0.1, 0.1), xycoords='figure fraction',
+                   xytext=(-0.1, 1.5), textcoords='axes fraction',
                    va='top', ha='left', fontsize=FONTSIZE*1.5, weight='bold')
+    mu_ax.set_ylim([0.03,0.07])
 
     # plot the sensitivity coefficients
     vs = sens_ax.plot(glc_rates, substrate_csc, color ='orange', linewidth= 3) #(62/255,174/255, 137/255)
-    e1 = sens_ax.plot(glc_rates, e1_esc, color =(68 / 255, 1 / 255, 84 / 255), linewidth= 3, linestyle ='dashed')
+    e1 = sens_ax.plot(glc_rates, e1_esc, color =(0.00,0.45,0.81), linewidth= 3, linestyle ='dashed')
     e_tot = sens_ax.plot(glc_rates, tot_prot_csc, color ='darkred', linewidth= 3, linestyle ='dotted')#(62/255, 64/255, 137/255)
 
     sens_ax.legend([vs, e1, e_tot], labels=['$FCSC_{v_{1}}$','$ESC_{E_{1}}$','$PCSC$'], loc='center left')
     sens_ax.set_ylim([-0.1,1.3])
-    sens_ax.set_ylabel('Sensitivity Coefficients', fontsize = FONTSIZE)
-    sens_ax.set_xlabel('$v_{substrate,max}$ $(mmol_{substrate}/g_{CDW}/h)$', fontsize = FONTSIZE)
+    sens_ax.set_xlim([0.04,0.1])
+    sens_ax.set_ylabel('Sensitivity Coefficients', fontsize = FONTSIZE*3/4)
+    sens_ax.set_xlabel('$v_{substrate,max}$ $(mmol_{substrate}/g_{CDW}/h)$', fontsize = FONTSIZE*3/4)
+
+    # Add a pie chart showing the enzyme sensitivities as an inset in the sensitivity linegraph
+    inset_ax = inset_axes(sens_ax, width="50%", height="50%", loc='center right')
+    inset_ax.pie(pie_data, labels=pie_labels,  textprops={'fontweight': 'bold'}, startangle=90, labeldistance = 0.6)
 
     return fig
 
 if __name__ == "__main__":
-
+    #NOTE:RUN THIS SCRIPT FROM THE MAIN DIRECTORY IN THE COMMAND LINE.
+    # otherwise the relative paths set in this script will result in errors
     FONTSIZE = 16
-    width = 7
+    width = 10
     height = 12
     model = build_toy_gem()
     active_enzyme = build_active_enzyme_sector(Config)
@@ -215,14 +223,14 @@ def plot_sensitivities(fig, grdspec, glc_rates, mu_list, tot_prot_csc, substrate
     # gridspec inside gridspec
     fig = plt.figure()
 
-    gs0 = gridspec.GridSpec(2, 1, figure=fig, height_ratios=[1,1])
+    gs0 = gridspec.GridSpec(2, 1, figure=fig, height_ratios=[3,2])
     gs_toymodel = gs0[0]
     gs_sensitivities = gs0[1]
 
-    image_path = 'Figure1_toy-model.png'
+    image_path = 'Figures/Figure1_toy-model.png'
     toy_model = np.asarray(Image.open(image_path))
     ax_fig = fig.add_subplot(gs_toymodel)
-    ax_fig.imshow(toy_model)
+    ax_fig.imshow(toy_model, aspect='equal')
     ax_fig.annotate('A', xy=(2, 1), xycoords='data',
                     xytext=(-0.1, 1), textcoords='axes fraction',
                     va='top', ha='left', fontsize=FONTSIZE*1.5, weight='bold')
@@ -236,16 +244,21 @@ def plot_sensitivities(fig, grdspec, glc_rates, mu_list, tot_prot_csc, substrate
         if 'R1_flux_ub' in id:
             substrate_csc = [row[index] for row in simulation_results['Ccsc']]
 
+    pielabels = []
     for index, id in enumerate(simulation_results['x_axis_esc']):
         if 'E1' in id:
             e1_esc = [row[index] for row in simulation_results['Cesc']]
+        if 'E3' in id:
+            pielabels.append('')
+        else:
+            pielabels.append(id)
 
 
     fig = plot_sensitivities(fig, gs_sensitivities, simulation_results['substrate_axis'], simulation_results['mu_list'],
-                             tot_prot_csc, substrate_csc, e1_esc)
+                             tot_prot_csc, substrate_csc, e1_esc, simulation_results['Cesc'][-1], pielabels)
     fig.set_figwidth(width)
     fig.set_figheight(height)
     plt.tight_layout()
 
-    fig.savefig('Figure1_toy_model-sensitivities.png',bbox_inches='tight')
+    fig.savefig('Figures/Figure1_toy_model-sensitivities.png',bbox_inches='tight')
     plt.show()