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| {{Paris/Menu}} | | {{Paris/Menu}} |
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- | {{Paris/Header|Method & Algorithm : ƒ1}} | + | {{Paris/Header|Method & Algorithm : ƒ3}} |
| + | <center> = act_''pFlhDC'' </center> |
| + | <br> |
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| [[Image:f3omp.jpg|thumb|Specific Plasmid Characterisation for ƒ3]] | | [[Image:f3omp.jpg|thumb|Specific Plasmid Characterisation for ƒ3]] |
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- | We have <span style="color:#0000FF;">[OmpR<sup>*</sup>]<sub>''real''</sub> = {coef<sub>omp</sub>}''expr(pTet)'' = {coef<sub>omp</sub>} ƒ1([aTc]<sub>i</sub>)</span>
| + | According to the characterization plasmid (see right) and to our modeling, in the '''exponential phase of growth''', at the steady state, |
- | and <span style="color:#0000FF;">[FliA]<sub>''real''</sub> = {coef<sub>FliA</sub>}''expr(pBad)'' = {coef<sub>FliA</sub>} ƒ2([arab]<sub>i</sub>)</span> | + | |
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- | but we use <span style="color:#0000FF;">[aTc]<sub>i</sub> = Inv_ƒ1( [OmpR<sup>*</sup>] ) </span>
| + | we have ''' [''OmpR<sup>*</sup>'']<sub>''real''</sub> = {coef<sub>''ompR''</sub>} ƒ1([aTc]<sub>i</sub>) ''' |
- | and <span style="color:#0000FF;">[ara]<sub>i</sub> = Inv_ƒ2( [FliA] ) </span> | + | and ''' [FliA]<sub>''real''</sub> = {coef<sub>FliA</sub>} ƒ2([arab]<sub>i</sub>) ''' |
| + | |
| + | but we use ''' [aTc]<sub>i</sub> = Inv_ƒ1( [OmpR<sup>*</sup>] ) ''' |
| + | and ''' [arab]<sub>i</sub> = Inv_ƒ2( [FliA] ) ''' |
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| So, at steady-states, | | So, at steady-states, |
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| [[Image:F3ompfinal.jpg|center]] | | [[Image:F3ompfinal.jpg|center]] |
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- | <br><br>
| + | we use this analytical expression to determine the parameters : |
- | | + | |
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| <div style="text-align: center"> | | <div style="text-align: center"> |
- | {{Paris/Toggle|Table|Team:Paris/Modeling/More_f1_Table}} | + | {{Paris/Toggle|Table of Values|Team:Paris/Modeling/More_f3_Table}} |
| </div> | | </div> |
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| <div style="text-align: center"> | | <div style="text-align: center"> |
- | {{Paris/Toggle|Algorithm|Team:Paris/Modeling/More_f1_Algo}} | + | {{Paris/Toggle|Algorithm|Team:Paris/Modeling/More_f3_Algo}} |
| </div> | | </div> |
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- | Also, this experiment will enable us to know the expression of ƒ1 :
| + | Then, if we have time, we want to verify the expected relation |
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- | [[Image:ExprF1.jpg|center]] | + | [[Image:SumFlhDC1.jpg|center]] |
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| <br> | | <br> |
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| [[Team:Paris/Modeling/Protocol_Of_Characterization| <Back - to "Protocol Of Characterization" ]]| | | [[Team:Paris/Modeling/Protocol_Of_Characterization| <Back - to "Protocol Of Characterization" ]]| |
| </center> | | </center> |
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- | {|border="1" style="text-align: center"
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- | |param
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- | |signification
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- | |unit
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- | |value
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- | |comments
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- | |-
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- | |[expr(pFlhDC)]
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- | |expression rate of <br> pFlhDC '''with RBS E0032'''
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- | |nM.min<sup>-1</sup>
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- | |need for 20 mesures with well choosen values of [aTc]<sub>i</sub> <br> and for 20 mesures with well choosen values of [arab]<sub>i</sub> <br> and 5x5 measures for the relation below?
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- | |-
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- | |γ<sub>GFP</sub>
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- | |dilution-degradation rate <br> of GFP(mut3b)
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- | |min<sup>-1</sup>
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- | |0.0198
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- | |-
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- | |[GFP]
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- | |GFP concentration at steady-state
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- | |nM
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- | |need for 20 + 20 measures <br> and 5x5 measures for the relation below?
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- | |-
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- | |(''fluorescence'')
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- | |value of the observed fluorescence
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- | |au
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- | |need for 20 + 20 measures <br> and 5x5 measures for the relation below?
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- | |-
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- | |''conversion''
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- | |conversion ratio between <br> fluorescence and concentration
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- | |nM.au<sup>-1</sup>
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- | |(1/79.429)
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- | |}
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- | <br><br>
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- | {|border="1" style="text-align: center"
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- | |param
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- | |signification <br> corresponding parameters in the [[Team:Paris/Modeling/Oscillations#Resulting_Equations|equations]]
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- | |unit
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- | |value
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- | |comments
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- | |-
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- | |β<sub>13</sub>
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- | |production rate of FliA-pFlhDC '''with RBS E0032''' <br> β<sub>13</sub>
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- | |nM.min<sup>-1</sup>
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- | |-
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- | |(K<sub>12</sub>/{coef<sub>fliA</sub>})
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- | |activation constant of FliA-pFlhDC <br> K<sub>12</sub>
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- | |nM
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- | |-
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- | |n<sub>12</sub>
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- | |complexation order of FliA-pFlhDC <br> n<sub>12</sub>
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- | |no dimension
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- | |-
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- | |β<sub>2</sub>
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- | |production rate of OmpR-pFlhDC '''with RBS E0032''' <br> β<sub>2</sub>
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- | |nM.min<sup>-1</sup>
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- | |-
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- | |(K<sub>22</sub>/{coef<sub>omp</sub>})
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- | |activation constant of OmpR-pFlhDC <br> K<sub>22</sub>
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- | |nM
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- | |-
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- | |n<sub>22</sub>
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- | |complexation order of OmpR-pFlhDC <br> n<sub>22</sub>
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- | |no dimension
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- | |}
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- | <br><br>
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- | Then, if we have time, we want to verify the expected relation
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- | [[Image:SumFlhDC1.jpg|center]]
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Method & Algorithm : 3
= act_pFlhDC
Specific Plasmid Characterisation for 3
According to the characterization plasmid (see right) and to our modeling, in the exponential phase of growth, at the steady state,
we have [OmpR*]real = {coefompR} 1([aTc]i)
and [FliA]real = {coefFliA} 2([arab]i)
but we use [aTc]i = Inv_1( [OmpR*] )
and [arab]i = Inv_2( [FliA] )
So, at steady-states,
we use this analytical expression to determine the parameters :
↓ Table of Values ↑
param
| signification
| unit
| value
| comments
|
(fluorescence)
| value of the observed fluorescence
| au
|
| need for 20 mesures with well choosen values of [aTc]i and for 20 mesures with well choosen values of [arab]i and 5x5 measures for the relation below?
|
conversion
| conversion ratio between fluorescence and concentration ↓ gives ↓
| nM.au-1
| (1/79.429)
|
|
[GFP]
| GFP concentration at steady-state
| nM
|
|
|
γGFP
| dilution-degradation rate of GFP(mut3b) ↓ gives ↓
| min-1
| 0.0198
| Time Cell Division : 35 min.
|
3
| activity of pFlhDC with RBS E0032
| nM.min-1
|
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|
param
| signification corresponding parameters in the equations
| unit
| value
| comments
|
β22
| total transcription rate of FliA><pFlhDC with RBS B0034 β22
| nM.min-1
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(K6/{coeffliA})
| activation constant of FliA><pFlhDC K6
| nM
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n6
| complexation order of FliA><pFlhDC n6
| no dimension
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β17
| basal activity of pFlhDC with RBS B0034 β17
| nM.min-1
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(K15/{coefompR})
| activation constant of OmpR><pFlhDC K15
| nM
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n15
| complexation order of OmpR><pFlhDC n15
| no dimension
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↓ Algorithm ↑
find_3 ( FliA )
function optimal_parameters = find_f3_FliA(X_data, Y_data, initial_parameters)
global beta17;
function output = act_pFlhDC(parameters, X_data)
for k = 1:length(X_data)
output(k) = beta17*(1 - hill( X_data(k), parameters(2), parameters(3))) ...
+ parameters(1)*hill(X_data(k), parameters(2), parameters(3));
end
end
options=optimset('LevenbergMarquardt','on','TolX',1e-10,'MaxFunEvals',1e10,'TolFun',1e-10,'MaxIter',1e4);
optimal_parameters = lsqcurvefit( @(parameters, X_data) act_pFlhDC(parameters, X_data), ...
initial_parameters, X_data, Y_data, options );
end
find_3 ( OmpR* )
function optimal_parameters = find_f3_OmpR(X_data, Y_data, initial_parameters)
function output = act_pFlhDC(parameters, X_data)
for k = 1:length(X_data)
output(k) =(1 - hill( X_data(k), parameters(2), parameters(3) )) * parameters(1);
end
end
options=optimset('LevenbergMarquardt','on','TolX',1e-10,'MaxFunEvals',1e10,'TolFun',1e-10,'MaxIter',1e4);
optimal_parameters = lsqcurvefit( @(parameters, X_data) act_pFlhDC(parameters, X_data), ...
initial_parameters, X_data, Y_data, options );
end
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Then, if we have time, we want to verify the expected relation
<Back - to "Implementation" |
<Back - to "Protocol Of Characterization" |
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