updated mechanisms and parameters for PURE

Author: murrayrm

biocrnpyler/components/basic.py

@@ -7,7 +7,7 @@
 from ..core.reaction import Reaction
 from ..core.species import Complex, Species
 from ..mechanisms.binding import One_Step_Binding
-from ..mechanisms.enzyme import BasicCatalysis
+from ..mechanisms.enzyme import MichaelisMenten
 from ..mechanisms.metabolite import OneStepPathway
 
 
@@ -794,7 +794,7 @@ def __init__(
         Component.__init__(
             self=self,
             name=self.enzyme.name,
-            default_mechanism=BasicCatalysis(),
+            default_mechanism=MichaelisMenten(),
             **kwargs,
         )
 

biocrnpyler/mechanisms/binding_parameters.tsv

@@ -27,12 +27,12 @@ mechanism_id	part_id	param_name	param_val	units	comments
 # multiplying by 1e-6.
 
 # Chemical complex binding (aTc to TetR)
-binding	chemical_complex	kb	2.00	/uM/sec	SK07, Table 1, Reaction 6
-binding	chemical_complex	ku	0.001	/sec	SK07, Table 1, Reaction 8
+binding	chemical_complex	kb	2.00	/uM/sec	SK07, Table 1, R6
+binding	chemical_complex	ku	0.001	/sec	SK07, Table 1, R8
 
 # Protein-DNA binding (TetR2 to DNA)
-binding	dna_protein	kb	2.86	/uM/sec	SK07, Table 1, Reaction 23
-binding	dna_protein	ku	5.11e-4	/sec	SK07, Table 1, Reaction 24
+binding	dna_protein	kb	2.86	/uM/sec	SK07, Table 1, R23
+binding	dna_protein	ku	5.11e-4	/sec	SK07, Table 1, R24
 
 # Default cooperativity
 binding		cooperativity	2		number of binding modules to bind simultaneously

biocrnpyler/mechanisms/enzyme_parameters.tsv

@@ -6,13 +6,13 @@
 mechanism_id	part_id	param_name	param_val	units	comments
 
 # Basic (Michaelis-Menten) catalysis parameters
-catalysis		kb	100	/sec	assuming 10 ms to diffuse across 1 um (characteristic cell size)
-catalysis		ku	10	uM/sec	90% binding
-# catalysis		kcat	1
+catalysis		kb	100	/uM/sec	assuming 10 ms to diffuse across 1 um (characteristic cell size)
+catalysis		ku	10	/sec	90% binding
+# catalysis		kcat	1	/sec
 
 # Reversible Michaelis-Menten catalysis parameters
-catalysis		kb1	100	/sec	assuming 10 ms to diffuse across 1 um (characteristic cell size)
-catalysis		ku1	10	uM/sec	90% binding
+catalysis		kb1	100	/uM/sec	assuming 10 ms to diffuse across 1 um (characteristic cell size)
+catalysis		ku1	10	sec	90% binding
 catalysis		kb2	100	/sec	assuming 10 ms to diffuse across 1 um (characteristic cell size)
 catalysis		ku2	10	uM/sec	90% binding
 catalysis		kcat_rev	0.01

biocrnpyler/mechanisms/txtl.py

@@ -1983,7 +1983,7 @@ def __init__(
         else:
             raise ValueError("Fuels must be a list of Species!")
 
-        if all([isinstance(s, Species) for s in fuels]):
+        if all([isinstance(s, Species) for s in wastes]):
             self.wastes = wastes
         else:
             raise ValueError("wastes must be a list of Species!")

biocrnpyler/mechanisms/txtl_parameters.tsv

@@ -31,22 +31,22 @@ translation		ktl	0.05	/sec	15 aa/s and protein length of 300 aa
 # multiplying by 1e-6.  Dissociation constaints are computed by dividing
 # unbinding rate by the binding rate.
 
-transcription		K	5e-4	uM	SK07, Table 1, R8 / R6
-transcription		k	0.05	/sec	ktx from transcription_mm
+transcription		K	1.33e-3	uM	SK01 -> BFS formulas w/ RNAP = 1.3 (PURE)
+transcription		k	2.5e-2	/sec	hand-tuned to match MM in gfp_expression.py (TODO)
 transcription		n	2		cooperativity
 transcription		kleak	0.013	/sec	SK07, Table 1, R37
 
 # Transcription_MM and Translation_MM
 transcription_mm		ktx	0.05	/sec	50 nt/s and transcript length of 1000 nt
-transcription_mm		kb	8.6e-6	/uM/sec	SK07, Table 1, R31
+transcription_mm		kb	8.6	/uM/sec	SK07, Table 1, R31
 transcription_mm		ku	0.01	/sec	SK07, Table 1, R32
 translation_mm		ktl	0.05	/sec	15 aa/s and protein length of 300 aa
 translation_mm		kb	0.1	/uM/sec	SK07, Table 1, R45
 translation_mm		ku	100	/sec	SK07, Table 1, R46
 
 # Energy_Transcription_MM and Energy_Translation_MM
 energy_transcription_mm		ktx	50	/sec	50 nt/s (rate will be divided by length)
-energy_transcription_mm		kb	8.6e-6	/uM/sec	SK07, Table 1, R31
+energy_transcription_mm		kb	8.6	/uM/sec	SK07, Table 1, R31
 energy_transcription_mm		ku	0.01	/sec	SK07, Table 1, R32
 energy_transcription_mm		kb_ntps	10	/uM/sec	fast binding of NTPs to RNAP:DNA complex (TODO)
 energy_transcription_mm		ku_ntps	1e-6	/sec	slow unbinding of NTPs to RNAP:DNA complex (TODO)

biocrnpyler/mixtures/pure.py

@@ -172,7 +172,9 @@ def __init__(
         ntps='NTPs',
         ndps='NDPs',
         amino_acids='AAs',
-        fuel='ATP',
+        atp='ATP',
+        adp='ADP',
+        fuel='Fuel_CP',
         parameter_file='mixtures/pure_parameters.tsv',
         **kwargs,
     ):
@@ -190,8 +192,14 @@ def __init__(
             if not include_resources:
                 raise ValueError("include_fuel requires include_resources")
             self.fuel = Metabolite(fuel)
-            self.add_components([self.fuel])
+            self.adp = Metabolite(adp)
+            self.atp = Metabolite(
+                atp, precursors=[self.fuel, self.adp], products=[self.adp]
+            )  # fuel becomes ATP, and ATP is degraded
+            self.add_components([self.atp])  # includes ADP, fuel
         else:
+            self.atp = None
+            self.adp = None
             self.fuel = None
 
         if include_machinery:
@@ -224,9 +232,9 @@ def __init__(
             if include_fuel:
                 default_mechanisms['translation'] = Energy_Translation_MM(
                     ribosome=self.ribosome.get_species(),
-                    fuels=4 * [self.fuel.get_species()]
+                    fuels=4 * [self.atp.get_species()]
                     + [self.amino_acids.get_species()],
-                    wastes=[],
+                    wastes=4 * [self.adp.get_species()],
                 )
             else:
                 default_mechanisms['translation'] = Energy_Translation_MM(

biocrnpyler/mixtures/pure_parameters.tsv

@@ -58,3 +58,8 @@ energy_translation_mm		ku	0.003	/sec	Singhal et al. Table S2
 energy_translation_mm		kb_fuel	10	/uM/sec	fast binding of NTPs to RNAP:DNA complex (TODO)
 energy_translation_mm		ku_fuel	1e-6	/sec	slow unbinding of NTPs to RNAP:DNA complex (TODO)
 energy_translation_mm		length	300	aa	default length of a protein (for resource uasge)
+
+# Parameters for energy regeneration
+initial concentration		Fuel_CP	16666	uM	50 mM small molecule * 3/10 in final mix
+one_step_pathway	ATP_production	k	0.02	/uM/sec	alpha_atp, Singhal et al. Table S2 (TODO)
+one_step_pathway	ATP_degradation	k	0.0000177	/sec	Delta_ATP, Singhal et al. Table S2 (TODO)

examples/gfp_expression.py

@@ -17,7 +17,7 @@
     name='gfp', promoter='pconst', rbs='rbs_strong', protein='GFP'
 )
 
-# Simulation parmaters
+# Simulation parameters
 initial_conditions = {'dna_gfp': 1 * nM}
 timepts = np.linspace(0, 6 * hrs, 1000)
 
@@ -253,66 +253,68 @@
 # PURE mixtures
 #
 
+pure_timepts = np.linspace(0, 180 * min)
+
 simple_mixture = bcp.PURE(
     name='simple', components=[gfp_dna, cfp_dna],
     include_machinery=False, include_resources=False, include_fuel=False)
 simple_crn = simple_mixture.compile_crn()
 simple_res = simple_crn.simulate_with_bioscrape_via_sbml(
-    timepts, initial_condition_dict=cfp_initial_conditions
+    pure_timepts, initial_condition_dict=cfp_initial_conditions
 )
 
 machinery_mixture = bcp.PURE(
     name='machinery', components=[gfp_dna, cfp_dna],
     include_machinery=True, include_resources=False, include_fuel=False)
 machinery_crn = machinery_mixture.compile_crn()
 machinery_res = machinery_crn.simulate_with_bioscrape_via_sbml(
-    timepts, initial_condition_dict=cfp_initial_conditions
+    pure_timepts, initial_condition_dict=cfp_initial_conditions
 )
 
 resource_mixture = bcp.PURE(
     name='resources', components=[gfp_dna, cfp_dna],
     include_machinery=True, include_resources=True, include_fuel=False)
 resource_crn = resource_mixture.compile_crn()
 resource_res = resource_crn.simulate_with_bioscrape_via_sbml(
-    timepts, initial_condition_dict=cfp_initial_conditions
+    pure_timepts, initial_condition_dict=cfp_initial_conditions
 )
 
 energy_mixture = bcp.PURE(
     name='energy', components=[gfp_dna, cfp_dna],
     include_machinery=True, include_resources=True, include_fuel=True)
 energy_crn = energy_mixture.compile_crn()
 energy_res = energy_crn.simulate_with_bioscrape_via_sbml(
-    timepts, initial_condition_dict=cfp_initial_conditions
+    pure_timepts, initial_condition_dict=cfp_initial_conditions
 )
 
 energy_mixture_gfp = bcp.PURE(
     name='energy', components=[gfp_dna],
     include_machinery=True, include_resources=True, include_fuel=True)
 energy_crn_gfp = energy_mixture_gfp.compile_crn()
 energy_res_gfp = energy_crn_gfp.simulate_with_bioscrape_via_sbml(
-    timepts, initial_condition_dict=initial_conditions
+    pure_timepts, initial_condition_dict=initial_conditions
 )
 
 plt.figure(6)
 plt.clf()
 
 plt.plot(
-    timepts / min, simple_res['protein_GFP'] / uM,
+    pure_timepts / min, simple_res['protein_GFP'] / uM,
     label='GFP+CFP, simple')
 plt.plot(
-    timepts / min, machinery_res['protein_GFP'] / uM,
+    pure_timepts / min, machinery_res['protein_GFP'] / uM,
     label='GFP+CFP, machinery')
 plt.plot(
-     timepts / min, resource_res['protein_GFP'] / uM,
+     pure_timepts / min, resource_res['protein_GFP'] / uM,
      label='GFP+CFP, resources')
 plt.plot(
-    timepts / min, energy_res['protein_GFP'] / uM,
+    pure_timepts / min, energy_res['protein_GFP'] / uM,
     label='GFP+CFP, energy')
 plt.plot(
-    timepts / min, energy_res_gfp['protein_GFP'] / uM,
+    pure_timepts / min, energy_res_gfp['protein_GFP'] / uM,
     label='GFP only, energy')
 plt.plot(
-    timepts / min, pure_res['protein_GFP'] + 0.1 / uM, '--',
+    timepts[0:50] / min, pure_res['protein_GFP'][0:50] + 0.1 / uM, '--',
     label='GFP only + 0.1, basic')
 
 plt.ylim([0, 12])
@@ -321,3 +323,117 @@
 plt.xlabel("Time [min]")
 plt.ylabel("Concentration [uM]")
 plt.legend()
+
+#
+# Activators and repressors
+#
+
+TetR = bcp.Protein('TetR')
+aTc = bcp.Species('aTc')
+TetR_inactive = bcp.ChemicalComplex(
+    [TetR.species, aTc], mechanisms={'binding': bcp.One_Step_Binding()}
+)
+ptet_repressed = bcp.RepressiblePromoter('ptet', TetR)
+dna_GFP_repressed = bcp.DNAassembly(
+    'GFP', promoter=ptet_repressed, rbs='RBS', protein='GFP', length=714
+)
+
+initial_conditions = {'dna_GFP': 1 * nM, 'protein_TetR': 30 * uM}
+repressed_mixture = bcp.PURE(
+    name='repressed',
+    components=[dna_GFP_repressed, TetR_inactive],
+    include_machinery=True,
+    include_resources=True,
+    include_fuel=True,
+)
+repressed_crn = repressed_mixture.compile_crn()
+
+TetR = bcp.Protein('TetR')
+aTc = bcp.Species('aTc')
+TetR_inactive = bcp.ChemicalComplex(
+    [TetR.species, aTc], mechanisms={'binding': bcp.One_Step_Binding()}
+)
+ptet_regulated = bcp.RegulatedPromoter('ptet', TetR)
+dna_GFP_regulated = bcp.DNAassembly(
+    'GFP', promoter=ptet_regulated, rbs='RBS', protein='GFP'
+)
+regulated_parameters = {
+    ('transcription', 'ptet_leak', 'ktx'): 50,          # unbound
+    ('transcription', 'ptet_TetR', 'ktx'): 0.001,       # bound
+}
+
+regulated_mixture = bcp.PURE(
+    name='regulated',
+    components=[dna_GFP_regulated, TetR_inactive],
+    include_machinery=True,
+    include_resources=True,
+    include_fuel=True,
+    parameters=regulated_parameters,
+)
+regulated_crn = regulated_mixture.compile_crn()
+
+plt.figure(7)
+plt.clf()
+
+offset = -0.01
+TetR_0 = initial_conditions['protein_TetR']
+for aTc_0 in np.linspace(0, 50*uM, 5):
+# aTc_0 = 0
+# for TetR_0 in np.linspace(0, 20*uM, 5):
+    repressed_res = repressed_crn.simulate_with_bioscrape_via_sbml(
+        pure_timepts, initial_condition_dict=initial_conditions
+        | {'aTc': aTc_0} | {'protein_TetR': TetR_0}
+    )
+    lines = plt.plot(
+        pure_timepts / min,
+        repressed_res['protein_GFP'] / uM + offset,
+        label=f"aTc={aTc_0 / uM} uM, TetR={TetR_0 / uM} uM",
+    )
+
+    regulated_res = regulated_crn.simulate_with_bioscrape_via_sbml(
+        pure_timepts, initial_condition_dict=initial_conditions
+        | {'aTc': aTc_0} | {'protein_TetR': TetR_0}
+    )
+    plt.plot(
+        pure_timepts / min,
+        regulated_res['protein_GFP'] / uM + offset,
+        color=lines[0].get_color(),
+        linestyle='--',
+    )
+
+    offset += 0.05
+
+plt.title("Represssed (-) versus Regulated (--)")
+plt.xlabel("Time [min]")
+plt.ylabel("Concentration [uM]")
+plt.legend()
+
+#
+# PURE debugging
+#
+
+repressed_res = repressed_crn.simulate_with_bioscrape_via_sbml(
+    pure_timepts, initial_condition_dict=initial_conditions
+    | {'aTc': 37.5 * uM} | {'protein_TetR': 30 * uM}
+)
+
+plt.figure(8)
+plt.clf()
+bcp.plot_gene_expression_data(
+    repressed_res, repressed_crn, dna_GFP_repressed,
+    trace_offset=[0.01, 0.002, 0.1, 0.1])
+plt.suptitle("Gene expression, repressed", fontsize='large')
+plt.tight_layout()
+
+regulated_res = regulated_crn.simulate_with_bioscrape_via_sbml(
+    pure_timepts, initial_condition_dict=initial_conditions
+    | {'aTc': 37.5 * uM} | {'protein_TetR': 30 * uM}
+)
+
+plt.figure(9)
+plt.clf()
+bcp.plot_gene_expression_data(
+    regulated_res, regulated_crn, dna_GFP_regulated,
+    trace_offset=[0.01, 0.002, 0.1, 0.1])
+plt.suptitle("Gene expression, regulated", fontsize='large')
+plt.tight_layout()