Team:Bologna/Project

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Transcription of the target gene yields a mRNA strand - containing the CIS-repressing sequence at its 5' end - available for translation into protein by ribosomes (<i>see Fig. 1, left panel</i>). When the promoter controlling the TRANS coding sequence is active, it drives the transcription of an oligoribonucleotide complementary to the CIS mRNA sequence. The TRANS/CIS <b>RNA duplex</b> prevents ribosomes from binding to RBS on target mRNA, thus <b>silencing protein synthesis</b>. The amount of the TRANS-repressor regulates the rate of translation of the target mRNA (<i>see Fig. 1, right panel</i>)
Transcription of the target gene yields a mRNA strand - containing the CIS-repressing sequence at its 5' end - available for translation into protein by ribosomes (<i>see Fig. 1, left panel</i>). When the promoter controlling the TRANS coding sequence is active, it drives the transcription of an oligoribonucleotide complementary to the CIS mRNA sequence. The TRANS/CIS <b>RNA duplex</b> prevents ribosomes from binding to RBS on target mRNA, thus <b>silencing protein synthesis</b>. The amount of the TRANS-repressor regulates the rate of translation of the target mRNA (<i>see Fig. 1, right panel</i>)
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[[Image:project3b.png|center|950px|thumb|<center>Figure 1 - T-REX device</center>]]
[[Image:project3b.png|center|950px|thumb|<center>Figure 1 - T-REX device</center>]]
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<font face="Calibri" font size="5" color="#000000"><b>CIS and TRAN Parts Design</b>
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<font face="Calibri" font size="5" color="#000000"><b>CIS and TRANS Parts Design</b>
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To identify CIS-repressing and TRANS-repressor complementary parts, we developed <a href="https://2009.igem.org/Team:Bologna/Software">BASER</a> software. We used it to seek for two complementary 50bp non-coding sequences, whose transcribed RNAs:<br>
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To identify CIS-repressing and TRANS-repressor DNA sequences, we developed <a href="https://2009.igem.org/Team:Bologna/Software">BASER</a> software. We used it to seek for two complementary 50bp non-coding sequences, whose transcribed RNAs:<br>
a) feature maximal free energy in the secondary structure (i.e. reducing the probability of its intra-molecular annealing); <br>
a) feature maximal free energy in the secondary structure (i.e. reducing the probability of its intra-molecular annealing); <br>
b) have minimal unwanted interactions with genomic mRNA; <br>
b) have minimal unwanted interactions with genomic mRNA; <br>
c) present a minimal probability of partial/shifted hybridization with complementary strands. <br><br>
c) present a minimal probability of partial/shifted hybridization with complementary strands. <br><br>
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Here below are the CIS-repressing and TRANS-repressor sequences:
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Here below are the CIS-repressing and TRANS-repressor sequences. More details about BASER and its functioning can be found in the <html><a href="https://2009.igem.org/Team:Bologna/Software">software section</a>.</html>
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More details about BASER and its functioning can be found in the <html><a href="https://2009.igem.org/Team:Bologna/Software">software section</a>.</html>
 
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<font face="Calibri" font size="5" color="#000000"><b>Testing Circuit</b>
<font face="Calibri" font size="5" color="#000000"><b>Testing Circuit</b>
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To characterize the T-REX device, we developed a [https://2009.igem.org/Team:Bologna/Modeling mathematical model] of the whole testing circuit considering the interaction between all its parts. Model equations were implemented in Simulink (Fig. 4) to simulate the circuit and it intermediate parts. After the identification of model parameters on the data obtained from experiments with the intermediate parts, the GFP level as a function of the TRANS/CIS affinity  was predicted by simulating the whole testing circuit .  
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In order to characterize the T-REX device, we developed a mathematical model of the parts and we simulated the response of the testing circuit. (LINK)
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[[Image:ModelSandro.png|center|900px|thumb|<center>Figure 4 - Simulink Model</center>]]
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***é PARTE MODELLO***
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<font face="Calibri" font size="5" color="#000000"><b>Testing Circuit's Positive Control</b></font>
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<font face="Calibri" font size="5" color="#000000"><b>Characterization of Parts</b></font>
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The Testing Circuit is constituted by intermediate parts that were experimentally characterized to obtain date for the model paramiter identification. Details of this characterization are available in the [https://2009.igem.org/Team:Bologna/Wetlab wet-lab] section.
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To have a positive control, we designed a circuit (Fig. 3) that simulates the behavior of the testing circuit (Fig. 2) when the T-REX device is idle or for the absence of TRANS-repressor or in case that TRANS-repressor mRNA is unable to silence LacI translation.
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[[Image:OffCircuit1.png|center|900px|thumb|<center>Figure 3 - Testing Circuit's Positive Control</center>]]
 
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<font face="Calibri" font size="5" color="#000000"><b>Characterization???</b></font>
 
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Before realizing the whole Testing Circuit, we decided to characterize the constitutive parts with intermediate circuits. Data from this analysis were used to test the model of parts and to assign the model parameters.
 
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<font face="Calibri" font size="5" color="#000000"><b><i>pSB1A2</i> vs <i>pSB3K3</i></b>
 
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* In order to identify the ratio between the high copy number the low to medium copy number plasmids, we analyzed the BBa_K201003 GFP production both on pSB1A2 and pSB3K3:
 
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|[[Image:1429GFP_openloop_hc.png|center|450 px|thumb|<center><font face="Calibri" font size="4">Figure 4a - BBa_K201003 on pSB1A2</font></center>]]
 
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|[[Image:1429GFP_openloop_lc.png|center|450 px|thumb|<center><font face="Calibri" font size="4">Figure 4b - BBa_K201003 on pSB3K3</font></center>]]
 
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<b>Results can be found in the [https://2009.igem.org/Team:Bologna/Characterization#Plasmid_copy_number_characterization wet-lab section]</b> </center>
 
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<font face="Calibri" font size="5" color="#000000"><b><i>BBa_J23100</i> vs <i>BBa_J23118</i></b>
 
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* In order to identify the ratio between BBa_J23100 and BBa_J23118 promoters, we analyzed the BBa_K079031 and BBa_K079032 GFP production on pSB1A2:
 
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|[[Image:2547GFP_open_tag.png|center|450 px|thumb|<center><font face="Calibri" font size="4">Figure 5a - BBa_K079032 on pSB1A2</font></center>]]
 
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|[[Image:1429GFP_openloop_hc_tag.png|center|450 px|thumb|<center><font face="Calibri" font size="4">Figure 5b - BBa_K079031 on pSB1A2</font></center>]]
 
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<b>Results can be found in the [https://2009.igem.org/Team:Bologna/Characterization#Promoter_characterization wet-lab section]</b></center>
 
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<font face="Calibri" font size="5" color="#000000"><b><i>Presence</i> vs <i>Absence</i> of LacI natural operator O2</b>
 
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* We needed to confirm that LacI natural operator O2 don't influence GFP production when LacI repressor is not present. We compare then the expression level from BBa_K079032 and BBa_K201001
 
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|[[Image:2547GFP_open_tag.png|center|450 px|thumb|<center><font face="Calibri" font size="4">Figure 6a - BBa_K079032 on pSB1A2</font></center>]]
 
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|[[Image:2547GFPO2_open_tag.png|center|450 px|thumb|<center><font face="Calibri" font size="4">Figure 6b - BBa_K201001 on pSB1A2</font></center>]]
 
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<b>Results can be found in the [https://2009.igem.org/Team:Bologna/Characterization#GFP_production_in_absence_/_presence_of_operator_Ox wet-lab section]</b></center>
 
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<font face="Calibri" font size="5" color="#000000"><b>Interaction of <i>LacI repressor</i> with its <i>natural operator O2</i></b>
 
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* We studied interactions between LacI repressor and its natural operator O2, using different IPTG concentration in order to evaluate LacI repression strengthanalyzing this two genetic circuits:
 
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|[[Image:LACi_GFP2_tag.png|center|750 px|thumb|<center><font face="Calibri" font size="4">Figure 7 - interactions between LacI repressor and its natural operator O2</font></center>]]
 
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<center><b>Results can be found in the [https://2009.igem.org/Team:Bologna/Characterization wet-lab section]</b></center>
 
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Latest revision as of 02:56, 22 October 2009

ProvaBol2.png
HOME TEAM PROJECT SOFTWARE MODELING WET LAB PARTS HUMAN PRACTICE JUDGING CRITERIA


T-REX Project

(Trans-Repressor of Expression)


The aim of our project is the design of a standard device to control the synthesis of any protein of interest. This "general-purpose" device, implemented in E. coli, acts at the translational level to allow silencing of protein expression faster than using regulated promoters. We named this device T-REX (Trans Repressor of Expression).
T-REX consists of two new BioBricks:

  • CIS-repressing, to be assembled upstream of the target protein coding sequence. It contains a ribosomal binding site (RBS);
  • TRANS-repressor, complementary to the CIS-repressing and placed under the control of a different promoter. For a better repressive effectiveness, the TRANS sequence contains also a RBS cover, released in two versions of different length (either 4 or 7 nucleotides).
    The longer version covers also 3 nucleotides of the Shine-Dalgarno sequence.

Transcription of the target gene yields a mRNA strand - containing the CIS-repressing sequence at its 5' end - available for translation into protein by ribosomes (see Fig. 1, left panel). When the promoter controlling the TRANS coding sequence is active, it drives the transcription of an oligoribonucleotide complementary to the CIS mRNA sequence. The TRANS/CIS RNA duplex prevents ribosomes from binding to RBS on target mRNA, thus silencing protein synthesis. The amount of the TRANS-repressor regulates the rate of translation of the target mRNA (see Fig. 1, right panel)

Figure 1 - T-REX device



CIS and TRANS Parts Design

To identify CIS-repressing and TRANS-repressor DNA sequences, we developed BASER software. We used it to seek for two complementary 50bp non-coding sequences, whose transcribed RNAs:
a) feature maximal free energy in the secondary structure (i.e. reducing the probability of its intra-molecular annealing);
b) have minimal unwanted interactions with genomic mRNA;
c) present a minimal probability of partial/shifted hybridization with complementary strands.

Here below are the CIS-repressing and TRANS-repressor sequences. More details about BASER and its functioning can be found in the software section.

CIS-repressing
Prefix non-coding TRANS target RBS Suffix
GAATTCGCGGCCGCTTCTAGAG AACACAAACTATCACTTTAACAACACATTACATATACATTAAAATATTAC AAAGAGGAGAAA TACTAGTAGCGGCCGCTGCAG


TRANS-repressor (4)
Prefix RBS cover non-coding TRANS Suffix
GAATTCGCGGCCGCTTCTAGAG CTTT GTAATATTTTAATGTATATGTAATGTGTTGTTAAAGTGATAGTTTGTGTT TACTAGTAGCGGCCGCTGCAG


TRANS-repressor (7)
Prefix RBS cover non-coding TRANS Suffix
GAATTCGCGGCCGCTTCTAGAG CCTCTTT GTAATATTTTAATGTATATGTAATGTGTTGTTAAAGTGATAGTTTGTGTT TACTAGTAGCGGCCGCTGCAG



Testing Circuit

In order to test our T-REX device, we developed the following genetic circuit (Fig. 2):

Figure 2 - Genetic Circuit to test CIS and TRANS' mRNA functionality


The CIS-repressing sequence is assembled upstream of lac I (BBa_C0012), therefore the synthesis of LacI should be silenced/damped by the constitutively transcribed TRANS-repressor mRNA. To detect silencing of LacI, due to the action of T-REX, we realized a new inverter (BBa_K201001) consisting of a promoter regulated by LacI (BBa_K201008) and a GFP reporter (BBa_J04031).
We expect that a TRANS-repressor oligoribonucleotide with high affinity to CIS-repressing mRNA, inhibits the translation of LacI and then determines a maximally expressed GFP. Otherwise, in case of low TRANS/CIS affinity one should expect partially (or completely) repressed GFP expression.
To maximize the probability to silence the CIS transcript and switch on the GFP, we decided to use a high copy number (HCN) plasmid (pSB1A2) for the TRANS-repressor and a low copy number (LCN) plasmid (pSB3K3) for the LacI generator.
If the GFP inverter is unable to reveal the LacI reduction due to T-REX action, because of a high level of the free LacI concentration, IPTG can be supplied to reduce free LacI. In fact, the sensitivity of the GFP inverter to LacI variations depends on free LacI concentration. Using IPTG is thus possible to set actual LacI value in the region where the inverter has the highest sensitivity.

Mathematical Model

To characterize the T-REX device, we developed a mathematical model of the whole testing circuit considering the interaction between all its parts. Model equations were implemented in Simulink (Fig. 4) to simulate the circuit and it intermediate parts. After the identification of model parameters on the data obtained from experiments with the intermediate parts, the GFP level as a function of the TRANS/CIS affinity was predicted by simulating the whole testing circuit .

Figure 4 - Simulink Model



Characterization of Parts

The Testing Circuit is constituted by intermediate parts that were experimentally characterized to obtain date for the model paramiter identification. Details of this characterization are available in the wet-lab section.