Team:UT-Tokyo/Project/Inhibition/Discussion

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==Section-1==
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==LacI - pLac==
LacI represses the frequently used promoter, pLac. The binding of LacI to pLac is competitively inhibited and the repression of pLac is weakened by introducing 8 LacI-binding-sites on pSB1C3 (a high-copy-plasmid).
LacI represses the frequently used promoter, pLac. The binding of LacI to pLac is competitively inhibited and the repression of pLac is weakened by introducing 8 LacI-binding-sites on pSB1C3 (a high-copy-plasmid).
By introducing 8 tandem repeats of LacI binding sites on pSB1C3 in addition to pLac-RBS-GFP-d.term on pSB1A2, it is expected that the binding of LacI to pLac is competitively inhibited which can be visually tracked by GFP expression. Moreover, longer LacI binding sites  (more than 8 binding sites) is thought to capture more LacI and enhance GFP expression more effectively.
By introducing 8 tandem repeats of LacI binding sites on pSB1C3 in addition to pLac-RBS-GFP-d.term on pSB1A2, it is expected that the binding of LacI to pLac is competitively inhibited which can be visually tracked by GFP expression. Moreover, longer LacI binding sites  (more than 8 binding sites) is thought to capture more LacI and enhance GFP expression more effectively.
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==Section-2==
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 +
==ArgR - ArgR binding site==
rocF is the gene coding the enzyme that converts L-arginine to L-ornithine and urea. By introducing rocF, e.coli obtains the urea cycle. ArgR is the common repressor of the bacterial arginine biosynthetic genes. By introducing ArgR binding sites, the probability that ArgR binds to the operator of the arginine biosynthetic genes falls and arginine biosynthesis is derepressed. (Tokyo Tech 2011)
rocF is the gene coding the enzyme that converts L-arginine to L-ornithine and urea. By introducing rocF, e.coli obtains the urea cycle. ArgR is the common repressor of the bacterial arginine biosynthetic genes. By introducing ArgR binding sites, the probability that ArgR binds to the operator of the arginine biosynthetic genes falls and arginine biosynthesis is derepressed. (Tokyo Tech 2011)
By introducing ArgR binding sites (including 8 binding sites) on pSB1C3 (high-copy-plasmid) in addition to Ptrc-RBS-rocF on pSB6A1 (low-copy-plasmid), ArgR is sequestered by ArgR binding sites and arginine biosynthesis is derepressed, so that urea production rate is expected to rise compared to Ptrc-RBS-rocF on low-copy-plasmid / ArgR binding site on high-copy-plasmid (Tokyo Tech 2011). Furthermore, although a single ArgR binding site introduced downstream of Ptrc-RBS-rocF did not derepress arginine biosynthesis, it is thought that sufficiently long ArgR binding sites introduced downstream the Ptrc-RBS-rocF binds to many more ArgR proteins and derepresses arginine biosynthesis, consequently enhancing the urea production rate.
By introducing ArgR binding sites (including 8 binding sites) on pSB1C3 (high-copy-plasmid) in addition to Ptrc-RBS-rocF on pSB6A1 (low-copy-plasmid), ArgR is sequestered by ArgR binding sites and arginine biosynthesis is derepressed, so that urea production rate is expected to rise compared to Ptrc-RBS-rocF on low-copy-plasmid / ArgR binding site on high-copy-plasmid (Tokyo Tech 2011). Furthermore, although a single ArgR binding site introduced downstream of Ptrc-RBS-rocF did not derepress arginine biosynthesis, it is thought that sufficiently long ArgR binding sites introduced downstream the Ptrc-RBS-rocF binds to many more ArgR proteins and derepresses arginine biosynthesis, consequently enhancing the urea production rate.
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[[File:UT Tokyo Fig knockdown-hycAp 640 240.png|480]]
== Modeling ==
== Modeling ==
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To assess the effectiveness of our method, we made a model and to calculate estimated differences in transcription factor availability with and without adding tandem repeats of binding sites.
To assess the effectiveness of our method, we made a model and to calculate estimated differences in transcription factor availability with and without adding tandem repeats of binding sites.
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We start with up the equilibrium reaction:
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We start with up the equilibrium reaction:<br />
 +
*[[File:UT Tokyo-TF-DNA.png|Alt="Transcription Factor + DNA ←→ Transcription Factor-DNA"|x18px]]
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  Transcription Factor + DNA ←→ Transcription Factor-DNA
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By introducing binding sites into high-copy plasmids, the following reactions are added:<br />
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*[[File:UT Tokyo TF-Genome.png|Alt="Transcription Factor+ Genome DNA ←→ Transcription Factor-Genome DNA"|x18px]] <br />
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By introducing binding sites into high-copy plasmids, the following reactions are added:
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*[[File:UT Tokyo TF-bs.png|Alt="Transcription Factor + Binding Site on Plasmid ←→Transcription Factor-Binding Site"|x18px]]
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  Transcription Factor+ Genome DNA ←→ Transcription Factor-Genome DNA
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-
  Transcription Factor + Binding Site on Plasmid ←→Transcription Factor-Binding Site
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Let
Let
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*[T]+[TI]=const=:Z (Total concentration of the binding site on plasmid)
*[T]+[TI]=const=:Z (Total concentration of the binding site on plasmid)
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What we want to know is how [GI]/Y changes from a situation where [G]:[T] is 1:0 (wild type) to 1:1000 (introducing 10 tandem binding sites into a 100 copy  plasmid), because [GI]/Y represents the proportion of Genomic DNA bound by the transcription factor. Let u:= [GI]/Y.
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What we want to know is how [[File:UT Tokyo GI-Y.png|30px|Alt="[GI]/Y"]] changes from a situation where [G]:[T] is 1:0 (wild type) to 1:1000 (introducing 10 tandem binding sites into a 100 copy  plasmid), because [[File:UT Tokyo GI-Y.png|30px|Alt="[GI]/Y"]] represents the proportion of Genomic DNA bound by the transcription factor. Let u:= [[File:UT Tokyo GI-Y.png|30px|Alt="[GI]/Y"]].
By substitution,
By substitution,
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we set the variables y:=Y/X, z:=Z/X, t:=1/kX.
we set the variables y:=Y/X, z:=Z/X, t:=1/kX.
 +
 +
=== For LacI ===
Now, we solve this equation for the LacI transcription factor because its k is known.
Now, we solve this equation for the LacI transcription factor because its k is known.
the equilibrium constant [[File:UT Tokyo k LacI.png|300px]]
the equilibrium constant [[File:UT Tokyo k LacI.png|300px]]
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for the equilibrium
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for the equilibrium [1]<br />
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  LacI + DNA ←→ complex LacI-DNA (ref)
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*[[File:UT Tokyo-LacIDNA.png|Alt="LacI + DNA ←→ LacI-DNA"|300px]]
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The concentration of genomic DNA is [[File:UT Tokyo GenomeConc.png|300px|Alt="0.88x10^(-15)/6.02*10^23 = 1.887*10^(-9) [l/mol]"]](CCDB)
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The concentration of genomic DNA is [[File:UT Tokyo GenomeConc.png|300px|Alt="0.88x10^(-15)/6.02*10^23 = 1.887*10^(-9) [l/mol]"]][2]
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From the above, we caluculated u against X (Total concentration of the transcriptional factor) for several values of Z/Y(the number of binding sites introduced) = 0, 1, 10, 100, 1000 and obtained the graph following
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From the above, we caluculated u against X (Total concentration of the transcription factor) for several values of Z/Y(the number of binding sites introduced) = 0, 1, 10, 100, 1000 and obtained the graph following
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This graph shows the obvious effectiveness of introducing LacI binding sites into a high-copy plasmid (when the copy number ~ 10^2). Also, it shows that If X is high the effect of introducing tandem repeat is greater(by comparing Z/Y = 100 and 1000).
This graph shows the obvious effectiveness of introducing LacI binding sites into a high-copy plasmid (when the copy number ~ 10^2). Also, it shows that If X is high the effect of introducing tandem repeat is greater(by comparing Z/Y = 100 and 1000).
-
For reference, we write some graphs with larger/smaller k, to apply to other transcriptional factors.
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=== With Larger/Smaller k Than That of LacI ===
 +
 
 +
For reference, we write some graphs with larger/smaller k, to apply to other transcription factors.
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If k==2.4 * 10^8
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If k==2.4 * 10^8 (LacI)
[[File:UT_Tokyo_IG-graph8.jpg]]
[[File:UT_Tokyo_IG-graph8.jpg]]
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These graphs show that as k is increased, the effect of introducing binding sites becomes bigger.
These graphs show that as k is increased, the effect of introducing binding sites becomes bigger.
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 +
=== Reference ===
 +
*[1] LactoseRepressor-OperatorDNA Interactions: KineticAnalysis by aSurfacePlasmonResonanceBiosensor K. Bondeson, A. Frostellkarlsson, L. Fagerstam, G. Magnusson Univ Uppsala, Ctr Biomed, Dept Med Virol, S 75123 Uppsala, Sweden and Pharmacia Biosensor AB, S 75182 Uppsala, Sweden
 +
*[2] CCDB ''E.coli'' stastics http://ccdb.wishartlab.com/CCDB/cgi-bin/STAT_NEW.cgi
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;[[#見出し1|見出し1or子下階層ページ名1]]
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;[[#LacI - pLac|LacI - pLac]]
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:題名1の説明<br />改行して説明の続き
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;[[#ArgR - ArgR binding site|ArgR - ArgR binding site]]
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:説明
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;[[#Modeling|Modeling]]
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*[[#For LacI|For LacI]]
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*[[#With Larger/Smaller k Than That of LacI|With Larger/Smaller k Than That of LacI]]
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*[[#Reference|Reference]]
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Latest revision as of 03:09, 27 September 2012

Inhibition without Knockout:
Results & Discussion

box-background image

LacI - pLac

LacI represses the frequently used promoter, pLac. The binding of LacI to pLac is competitively inhibited and the repression of pLac is weakened by introducing 8 LacI-binding-sites on pSB1C3 (a high-copy-plasmid). By introducing 8 tandem repeats of LacI binding sites on pSB1C3 in addition to pLac-RBS-GFP-d.term on pSB1A2, it is expected that the binding of LacI to pLac is competitively inhibited which can be visually tracked by GFP expression. Moreover, longer LacI binding sites (more than 8 binding sites) is thought to capture more LacI and enhance GFP expression more effectively.

ArgR - ArgR binding site

rocF is the gene coding the enzyme that converts L-arginine to L-ornithine and urea. By introducing rocF, e.coli obtains the urea cycle. ArgR is the common repressor of the bacterial arginine biosynthetic genes. By introducing ArgR binding sites, the probability that ArgR binds to the operator of the arginine biosynthetic genes falls and arginine biosynthesis is derepressed. (Tokyo Tech 2011) By introducing ArgR binding sites (including 8 binding sites) on pSB1C3 (high-copy-plasmid) in addition to Ptrc-RBS-rocF on pSB6A1 (low-copy-plasmid), ArgR is sequestered by ArgR binding sites and arginine biosynthesis is derepressed, so that urea production rate is expected to rise compared to Ptrc-RBS-rocF on low-copy-plasmid / ArgR binding site on high-copy-plasmid (Tokyo Tech 2011). Furthermore, although a single ArgR binding site introduced downstream of Ptrc-RBS-rocF did not derepress arginine biosynthesis, it is thought that sufficiently long ArgR binding sites introduced downstream the Ptrc-RBS-rocF binds to many more ArgR proteins and derepresses arginine biosynthesis, consequently enhancing the urea production rate.

480

Modeling

To assess the effectiveness of our method, we made a model and to calculate estimated differences in transcription factor availability with and without adding tandem repeats of binding sites.

We start with up the equilibrium reaction:

  • Alt="Transcription Factor + DNA ←→ Transcription Factor-DNA"

By introducing binding sites into high-copy plasmids, the following reactions are added:

  • Alt="Transcription Factor+ Genome DNA ←→ Transcription Factor-Genome DNA"
  • Alt="Transcription Factor + Binding Site on Plasmid ←→Transcription Factor-Binding Site"

Let

  • [I]:=concentration of the transcription factor alone
  • [G]:=concentration of the genomic DNA alone
  • [GI]:=concentration of the transcription factor - genome DNA complex
  • [T]:=concentration of the binding site on plasmid alone
  • [TI]:concentration of the transcriptional factor - binding site complex

Also, we assumed that the equilibrium constants, k, are equal. Alt="k:=[GI]/[I][G]=[TI]/[I][T]"

This leads to

  • [GI] = k [I][G]
  • [TI] = k [I][T]
  • [I]+[GI]+[TI]=const=:X (Total concentration of the transcription factor)
  • [G]+[GI]=const=:Y (Total concentration of the genomic DNA)
  • [T]+[TI]=const=:Z (Total concentration of the binding site on plasmid)

What we want to know is how Alt="[GI]/Y" changes from a situation where [G]:[T] is 1:0 (wild type) to 1:1000 (introducing 10 tandem binding sites into a 100 copy plasmid), because Alt="[GI]/Y" represents the proportion of Genomic DNA bound by the transcription factor. Let u:= Alt="[GI]/Y".

By substitution, UT Tokyo -GI- Y.png


we set the variables y:=Y/X, z:=Z/X, t:=1/kX.

For LacI

Now, we solve this equation for the LacI transcription factor because its k is known.

the equilibrium constant UT Tokyo k LacI.png for the equilibrium [1]

  • Alt="LacI + DNA ←→ LacI-DNA"


The concentration of genomic DNA is Alt="0.88x10^(-15)/6.02*10^23 = 1.887*10^(-9) [l/mol]"[2]


From the above, we caluculated u against X (Total concentration of the transcription factor) for several values of Z/Y(the number of binding sites introduced) = 0, 1, 10, 100, 1000 and obtained the graph following


UT Tokyo IG-graph8.jpg


This graph shows the obvious effectiveness of introducing LacI binding sites into a high-copy plasmid (when the copy number ~ 10^2). Also, it shows that If X is high the effect of introducing tandem repeat is greater(by comparing Z/Y = 100 and 1000).

With Larger/Smaller k Than That of LacI

For reference, we write some graphs with larger/smaller k, to apply to other transcription factors.


If k==10^6:

UT Tokyo IG-graph6.jpg


If k==10^7:

UT Tokyo IG-graph7.jpg


If k==2.4 * 10^8 (LacI)

UT Tokyo IG-graph8.jpg


If k==10^10:

UT Tokyo IG-graph10.jpg


These graphs show that as k is increased, the effect of introducing binding sites becomes bigger.


Reference

  • [1] LactoseRepressor-OperatorDNA Interactions: KineticAnalysis by aSurfacePlasmonResonanceBiosensor K. Bondeson, A. Frostellkarlsson, L. Fagerstam, G. Magnusson Univ Uppsala, Ctr Biomed, Dept Med Virol, S 75123 Uppsala, Sweden and Pharmacia Biosensor AB, S 75182 Uppsala, Sweden
  • [2] CCDB E.coli stastics http://ccdb.wishartlab.com/CCDB/cgi-bin/STAT_NEW.cgi