Team:Grenoble/Projet/Results/rmsA

From 2011.igem.org

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<div class="left">
<div class="left">
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<div  class="blocbackground" id="RSMA">
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<div  class="blocbackground" id="RSMA">
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<h1>Post-transcriptional regulation</h1>
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<h1>
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</div>
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Characterisation of the RsmA post-transcriptional regulation system components
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    <div  class="blocbackground" id="Results1">
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</h1>
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    <h2>Results</h2>
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</div>
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<p>The RsmA system has a homologous in Escherichia Coli named CsrA. We know these two system are extremely closed on
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<div  class="blocbackground" id="Results1">
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structural and functional sides. The most difference between this two regulation systems is on target regulon.  
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    <h2>
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For example, in Pseudomonas aeruginosa Rsma regulate many virulence genes as type III secretion system
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    Can rsmA be transferred into E. coli?
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(anja Brencic and Stephen Lory). In Escherichia coli, RsmA homologous regulate metabolic network.
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    </h2>
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Our goal is to integrate this translational regulation system in the toggle switch. We need to know whether it influence
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<p>
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the bacteria’s life.</p>
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The RsmA system from Pseudomonas has a homologue in Escherichia coli, named “CsrA”. We know that these two systems are extremely similar. Consequently we ask ourselves whether the synthesis of RsmA in E. coli interferes with its survival. Figure 1 shows growth curves of E.coli cells transformed by a plasmid containing an IPTG-inducible rsmA sequence from Pseudomonas and control cells carrying the same plasmid without rsmA. The superimposed curves demonstrate that the synthesis of RsmA does not interfere with the growth of E. coli.  
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<a href="https://static.igem.org/mediawiki/2011/9/91/Growth_cur_final2.png"><img src="https://static.igem.org/mediawiki/2011/9/91/Growth_cur_final2.png"
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</p>
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alt="logo iGEM"/></a>
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<a href="https://static.igem.org/mediawiki/2011/9/91/Growth_cur_final2.png"><img src="https://static.igem.org/mediawiki/2011/9/91/Growth_cur_final2.png"alt="logo iGEM"/>
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<div class="legend"><strong>Figure 1 RsmA influence on DH5α growth.</strong> Bacteria from overnight culture were reseeding in rich medium supplemented with tetracycline at 20mg/ml and also IPTG at the concentration given in the legend.</div>
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</a>
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<p>Figure 1 present growth curve of DH5α carries into a plasmid pVLT31 with or without rsmA and Natural RBS cloned downstream
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<div class="legend">
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the Plac promoter. Two triads can be seen. The triad containing the strains with empty plasmid shows an upper growth curve
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<strong>
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compared to the second triad carries pVLT31-rsmA. But it’s important to say that the two groups start their growth not at
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Figure 1 Influence of RsmA production on the growth of E coli DH5α.
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the same value. That explains a time lag between these two groups. After normalization of all curves, no differences
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</strong>
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between these two kind of bacteria could be seen. We conclude that the RsmA overexpression hasn’t effects on the growth of bacteria.</p>
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Bacteria transformed with pVLT31-rsmA or empty pVLT31 from overnight culture were re-suspended in rich medium supplemented with tetracycline at 20mg/ml. Induction of rsmA transcription is induced by IPTG at the concentrations given in the legend. Curves are normalized to their first OD value.  
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</div>
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</div>
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</div>
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    <div  class="blocbackground" id="Results2">
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<div  class="blocbackground" id="Results2">
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<h2>Characterisation of the leader sequences </h2>
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<h2>
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<p>We extracted and cloned several leader sequences that comport a ribosome-binding site (RBS). We first wanted to verify whether we could use them with a reporter gene,in order to:
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Characterisation of the leader sequences  
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<ul>
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</h2>
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<li><a href="#lab">Characterise their RBS strength</a></li>
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<p>
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<li><a href="#lab">Use them for further testtomeasure the effect of rsmAlaterrsmA +rsmY transcription. </a></li>
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We cloned several leader sequences that contain a ribosome-binding site (RBS) in front of a reporter gene, GFP, in order to:
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<ul>
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</ul>
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<li>
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</p>
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<a href="https://static.igem.org/mediawiki/2011/a/a7/Digrame_rbs_strengh.png" alt="figure4">
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<p>We first tested the following constructions with a FACSCalibur flow cytometer:</p>
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Characterise their RBS strength
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<a href="https://static.igem.org/mediawiki/2011/f/f2/Figure_2_construction.png"><img
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</a>
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height="450px" src="https://static.igem.org/mediawiki/2011/f/f2/Figure_2_construction.png"
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</li>
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alt="figure2"/></a>
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<li>
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<div class="legend"><strong>Figure 2:</strong>
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<a href="#lab">
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:Constructions used to characterise the sequences RBS strength of magA and fha leader sequences.  
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Use them for the translational control of downstream genes by the RsmA/rsmY system.  
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</div>
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</a>
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</li>
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<p>We used the brick BBa_K256003 as a reference to compare our leader sequences to. Fha1 and maga leader sequences are cloned to the same components as BBa_K256003, and carried by the same plasmid.  
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</ul>
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We used two negative controls:  
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The leader sequences used were mag and fha from Pseudomonas as well as the biobrick BBa_K256003, which was used as a reference. All constructs of Figure 2 have identical promoters, GFP reporter gene and terminators and are carried by the same plasmid.
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</p>
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</p>
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<ul>
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<a href="https://static.igem.org/mediawiki/2011/1/1a/Contructions_test.png">
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<li><a href="#lab">A brick similar to BBa_K5450010 that differs only by the absence of promoter</a></li>
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<img height="450px" src="https://static.igem.org/mediawiki/2011/1/1a/Contructions_test.png"alt="figure2"/>
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<li><a href="#lab">A cell culture containing no plasmid </a></li>
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<div class="legend">
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<strong>
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</ul>
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Figure 2:
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<p>Cell were incubate one night at 37°C, 250rpm, during 14h.  They were re-suspended tree hours before the test. Optic density at 600 nm was 3± 0,3 for all samples 15mn before the test. 50 μl of LB containing cellsand medium were diluted into 500 μl of filtered in 0,2 nm PBS, and tube were loader into the FACS.</p>
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</strong>
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</a>
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<a href="https://static.igem.org/mediawiki/2011/6/6f/Figure_3_facs.png"><img
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:Constructions used to characterise RBS included sequences strength of magA and fha leader sequences.  
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height="300px" src="https://static.igem.org/mediawiki/2011/6/6f/Figure_3_facs.png"
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</div>
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alt="figure3"/></a>
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<h3>
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<div class="legend"><strong>Figure 3:</strong>Dot plot of the water tube and one of the sample tubes. The measurements are done with 40000 events. FACS measurements were realised in duplicate (only one his shown).</div>
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Flow cytometry test
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</h3>
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<p>The cytometer count each particle that pass through the light beam; It is necessary to select an analysis gate that corresponds to the bacteria size.  We can then see what is the natural fluorescence of our control bacteria. This allows defining the windows of basal signal (M1) and positive signal (M2). We look at the average fluorescence within windows that comport the most cells.</p>
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<p>
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We used a FACSCalibur flow cytometer to measure the GFP fluorescence emitted by cells containing the constructs shown in Fig.2. Two negative controls were set up: a brick having the GFP reporter gene but no promoter (BBa_E0840) and a cell culture containing no plasmid.
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</p>
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<p>
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50 μl of LB containing cells were diluted into 500 μl of filtered PBS (OD600 of inoculum was 3± 0,3 for all samples) and then introduced into the FACS ten minutes after dilution.
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</p>
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<p>
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The cytometer counts each particle that passes through the light beam. Therefore it is necessary to select an analysis window that corresponds to the size of the bacteria (see Fig. 3).
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</p>
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<p>
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<a href "https://static.igem.org/mediawiki/2011/4/49/Population_cell.png">
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<img height="300px" src="https://static.igem.org/mediawiki/2011/4/49/Population_cell.png"/>
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<div class="legend">
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<strong>
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Figure 3:
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</strong>
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</a>
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Dot plots of particle size distributions obtained with a water sample containing no bacteria (left) and a sample containing bacteria (right). 40000 events were counted. FACS measurements were realised in duplicate.
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</div>
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<p>
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We then analysed the basal fluorescence recorded from control bacteria expressing no GFP. This allows to define two windows: the M1 window referring to basal fluorescence levels and containing fluorescence values obtained for all negative controls; the M2 window comprising fluorescence signals that are greater than the basal level. We show for each construction the average fluorescence (in red) within the window that contains most of the cells (percentages indicated in black, see Fig. 4).
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</p>
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<a href="https://static.igem.org/mediawiki/2011/2/27/Figure_4_flow_cytometre2.png"><img
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<a href "https://static.igem.org/mediawiki/2011/d/d8/Facs_result_for_each_fha_system_constructs.png">
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height="700px" src="https://static.igem.org/mediawiki/2011/2/27/Figure_4_flow_cytometre2.png"
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<img height="700px" src="https://static.igem.org/mediawiki/2011/d/d8/Facs_result_for_each_fha_system_constructs.png" alt="figure4"/>
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alt="figure4"/></a>
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<div class="legend"><strong>Figure 4:</strong> Individuals flow cytometer results for each construction. In red are theGFP’s fluorescence averages, in black the rate of bacteriawithin the M1 or M2 window.</div>
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<a href="https://static.igem.org/mediawiki/2011/d/df/Figure_5_flow_courbe.png"><img
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height="350px" src="https://static.igem.org/mediawiki/2011/d/df/Figure_5_flow_courbe.png"
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alt="figure4"/></a>
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<div class="legend"><strong>Figure 5:</strong> Compilation of the flow cytometer measurements.  1and 2 are the negative controls, 3 :magaleader sequence, 4: fha leader sequence, 5 : strongest biobrick RBS.</div>
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<p>The two negatives controls (WT and without promoter) show a very little fluorescent signal as expected. The reference brick BBa_K25003 shows an impressive amount of GFP with about 77 % of the cell population that fluoresce more than the control.Its average fluorescent signal is 1030 vs 2,5(wild type). The signal from the brick containing maga leader sequence (BBA_K545006) doesn’t differ very much from the negative controls: four per cent of the cell population fluoresce more than the controls, at a very low level even. The fluorescence mean is 4,4 vs 2,5 from the WT control (window M1). </p>
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<div class="legend">
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<p>Part BBa_K545010 containing the fha leader sequence induce a fluorescence signal higher than the control for 90 % of the cell population. The average signal (M2 window) is 154 vs 2,5(WT) and 1029 (BBa_K25003).</p>
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<strong>
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Figure 4:
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</strong>
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</a>
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Figure 4: Individual flow cytometry results (at the right) for different constructs (at the left). The red number indicates an average of GFP fluorescence.  The percentage in black indicates the fraction of the bacterial population within the respective analysis window M1 or M2.
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</div>
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<p>
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The two negative controls (cells containing no plasmid (1) or plasmid without promoter (2)) show a basal fluorescence signal as expected. Cells containing the reference brick BBa_K25003 (5) show a maximum amount of GFP fluorescence with 77 % of the cell population that fluoresce more than the negative controls. The average fluorescent signal calculated for construct 5 is 1030 (vs 2,5 (neg control)). The fluorescence signal obtained with cells containing the brick with the maga leader sequence (3) does not differ very much from the negative controls (4,4 vs 2,5). Four per cent of this cell population fluoresces more than the negative control populations.
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</p>
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<p>
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90 % of cells containing the fha leader sequence (4) present a fluorescence signal that is higher than control cells. Their average fluorescence is 98.
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</p>
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<a href="https://static.igem.org/mediawiki/2011/c/c0/Superposition_FACS_Curves.png">
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<img height="350px" src="https://static.igem.org/mediawiki/2011/c/c0/Superposition_FACS_Curves.png" alt="figure4"/>
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<a href="https://static.igem.org/mediawiki/2011/2/2c/Figure_6_rbs.png"><img
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<div class="legend">
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height="400px" src="https://static.igem.org/mediawiki/2011/2/2c/Figure_6_rbs.png"
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<strong>
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alt="figure4"/></a>
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Figure 5:
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<div class="legend"><strong>Figure 6:</strong> relative strength of maga(BBa_K545006) and fha(BBa_K545005) leader sequences RBS compared to BBa_K25003 RBS. The later is the strongest RBS used to compare others RBS of the registry. Maga has got very week RBS binding site strength,whereas fhaLS is still in the same order level.</div>
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</strong>
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</a>
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Compilation of the flow cytometer measurements.  1and 2 are the negative controls, 3 : maga leader sequence, 4: fha leader sequence, 5 : reference biobrick BBa_K256003.
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</div>
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<p>
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Figure 5 summarises the cytometry results. We can see that both leader sequences mag and fha allow the translation of the gfp mRNA. They can therefore be used for further characterisation of the system.  The GFP fluorescence signal is much higher using the fha leader sequence when compared to mag. Figure 6 focuses on the RBS strength of those two gene leader sequences, and compares them to the strongest RBS of the part registry: BBa_0034. Mag has got very week RBS binding site strength, whereas fha is stronger (10% of the maximum value obtained for BBa_0034).
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</p>
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<a href="https://static.igem.org/mediawiki/2011/a/a7/Digrame_rbs_strengh.png">
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<img height="400px" src="https://static.igem.org/mediawiki/2011/a/a7/Digrame_rbs_strengh.png" alt="figure4"/>
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<div class="legend">
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<strong>
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Figure 6:
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</strong>
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</a>
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Relative strength of maga (BBa_K545006) and fha (BBa_K545005) leader sequences compared to BBa_K25003 RBS. The latter is the strongest RBS used to compare RBS sequences of the registry.  
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</div>
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<h2>
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Perspectives
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</h2>
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</p>
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So far only the characterisation of the leader sequences has been completed. Fha allows a better expression of GFP than mag.The next experiment will be to look at how these leader sequences react to the presence of the RsmA protein.
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</p>  
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<p>
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We did a few tests with ptet rsma and pcons-fha-gfp or pcons-mag-gfp.  The first result showed an extremely low gfp signal, which suggests a repressive effect of Rsma on fha and mag. We cannot conclude yet because some controls are lacking. This however gives very promising prospects.
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</p>
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</div>
</div>
</div>
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</div>
 
</html>
</html>

Revision as of 15:26, 24 October 2011

Grenoble 2011, Mercuro-Coli iGEM


Characterisation of the RsmA post-transcriptional regulation system components

Can rsmA be transferred into E. coli?

The RsmA system from Pseudomonas has a homologue in Escherichia coli, named “CsrA”. We know that these two systems are extremely similar. Consequently we ask ourselves whether the synthesis of RsmA in E. coli interferes with its survival. Figure 1 shows growth curves of E.coli cells transformed by a plasmid containing an IPTG-inducible rsmA sequence from Pseudomonas and control cells carrying the same plasmid without rsmA. The superimposed curves demonstrate that the synthesis of RsmA does not interfere with the growth of E. coli.

logo iGEM
Figure 1 Influence of RsmA production on the growth of E coli DH5α. Bacteria transformed with pVLT31-rsmA or empty pVLT31 from overnight culture were re-suspended in rich medium supplemented with tetracycline at 20mg/ml. Induction of rsmA transcription is induced by IPTG at the concentrations given in the legend. Curves are normalized to their first OD value.

Characterisation of the leader sequences

We cloned several leader sequences that contain a ribosome-binding site (RBS) in front of a reporter gene, GFP, in order to:

The leader sequences used were mag and fha from Pseudomonas as well as the biobrick BBa_K256003, which was used as a reference. All constructs of Figure 2 have identical promoters, GFP reporter gene and terminators and are carried by the same plasmid.

figure2
Figure 2: :Constructions used to characterise RBS included sequences strength of magA and fha leader sequences.

Flow cytometry test

We used a FACSCalibur flow cytometer to measure the GFP fluorescence emitted by cells containing the constructs shown in Fig.2. Two negative controls were set up: a brick having the GFP reporter gene but no promoter (BBa_E0840) and a cell culture containing no plasmid.

50 μl of LB containing cells were diluted into 500 μl of filtered PBS (OD600 of inoculum was 3± 0,3 for all samples) and then introduced into the FACS ten minutes after dilution.

The cytometer counts each particle that passes through the light beam. Therefore it is necessary to select an analysis window that corresponds to the size of the bacteria (see Fig. 3).

Figure 3: Dot plots of particle size distributions obtained with a water sample containing no bacteria (left) and a sample containing bacteria (right). 40000 events were counted. FACS measurements were realised in duplicate.

We then analysed the basal fluorescence recorded from control bacteria expressing no GFP. This allows to define two windows: the M1 window referring to basal fluorescence levels and containing fluorescence values obtained for all negative controls; the M2 window comprising fluorescence signals that are greater than the basal level. We show for each construction the average fluorescence (in red) within the window that contains most of the cells (percentages indicated in black, see Fig. 4).

figure4
Figure 4: Figure 4: Individual flow cytometry results (at the right) for different constructs (at the left). The red number indicates an average of GFP fluorescence. The percentage in black indicates the fraction of the bacterial population within the respective analysis window M1 or M2.

The two negative controls (cells containing no plasmid (1) or plasmid without promoter (2)) show a basal fluorescence signal as expected. Cells containing the reference brick BBa_K25003 (5) show a maximum amount of GFP fluorescence with 77 % of the cell population that fluoresce more than the negative controls. The average fluorescent signal calculated for construct 5 is 1030 (vs 2,5 (neg control)). The fluorescence signal obtained with cells containing the brick with the maga leader sequence (3) does not differ very much from the negative controls (4,4 vs 2,5). Four per cent of this cell population fluoresces more than the negative control populations.

90 % of cells containing the fha leader sequence (4) present a fluorescence signal that is higher than control cells. Their average fluorescence is 98.

figure4
Figure 5: Compilation of the flow cytometer measurements. 1and 2 are the negative controls, 3 : maga leader sequence, 4: fha leader sequence, 5 : reference biobrick BBa_K256003.

Figure 5 summarises the cytometry results. We can see that both leader sequences mag and fha allow the translation of the gfp mRNA. They can therefore be used for further characterisation of the system. The GFP fluorescence signal is much higher using the fha leader sequence when compared to mag. Figure 6 focuses on the RBS strength of those two gene leader sequences, and compares them to the strongest RBS of the part registry: BBa_0034. Mag has got very week RBS binding site strength, whereas fha is stronger (10% of the maximum value obtained for BBa_0034).

figure4
Figure 6: Relative strength of maga (BBa_K545006) and fha (BBa_K545005) leader sequences compared to BBa_K25003 RBS. The latter is the strongest RBS used to compare RBS sequences of the registry.

Perspectives

So far only the characterisation of the leader sequences has been completed. Fha allows a better expression of GFP than mag.The next experiment will be to look at how these leader sequences react to the presence of the RsmA protein.

We did a few tests with ptet rsma and pcons-fha-gfp or pcons-mag-gfp. The first result showed an extremely low gfp signal, which suggests a repressive effect of Rsma on fha and mag. We cannot conclude yet because some controls are lacking. This however gives very promising prospects.