Difference between revisions of "Team:Pasteur Paris/InterLab"

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<tr>
 
<tr>
 
<td>Replicate 1</td>
 
<td>Replicate 1</td>
−
<td>0.085</td>
+
<td style="background-color: #00aeff;">0.085</td>
−
<td>0.069</td>
+
<td style="background-color: #00aeff;">0.069</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
 
<td>Replicate 2</td>
 
<td>Replicate 2</td>
−
<td>0.085</td>
+
<td style="background-color: #00aeff;">0.085</td>
−
<td>0.066</td>
+
<td style="background-color: #00aeff;">0.066</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
 
<td>Replicate 3</td>
 
<td>Replicate 3</td>
−
<td>0.086</td>
+
<td style="background-color: #00aeff;">0.086</td>
−
<td>0.064</td>
+
<td style="background-color: #00aeff;">0.064</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
 
<td>Replicate 4</td>
 
<td>Replicate 4</td>
−
<td>0.090</td>
+
<td style="background-color: #00aeff;">0.090</td>
−
<td>0.064</td>
+
<td style="background-color: #00aeff;">0.064</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
 
<td>Arith. Mean</td>
 
<td>Arith. Mean</td>
−
<td>0.087</td>
+
<td style="background-color: #ffe100">0.087</td>
−
<td></td>
+
<td style="background-color: #ffe100">0.066</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
 
<td>Corrected Abs600</td>
 
<td>Corrected Abs600</td>
−
<td>0.022</td>
+
<td style="background-color: #ffe100">0.022</td>
 
<td>/</td>
 
<td>/</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
 
<td>Reference OD600</td>
 
<td>Reference OD600</td>
−
<td>0.063</td>
+
<td style="background-color: #ffe100">0.063</td>
 
<td>/</td>
 
<td>/</td>
 
</tr>
 
</tr>
 
<tr>
 
<tr>
−
<td>OD600/Abs600</td>
+
<td style="background-color: #d51c1c">OD600/Abs600</td>
−
<td>2.930</td>
+
<td style="background-color: #d51c1c">2.930</td>
 
<td>/</td>
 
<td>/</td>
 
</tr>
 
</tr>

Revision as of 21:19, 29 September 2018

""

INTRODUCTION

This year, the iGEM Measurement Committee offered to all teams the possibility to do the Fifth International InterLaboratory Measurement Study in synthetic biology. This work concerns the reliability and repeatability of scientific measurements.

This project involves providing the same protocols and gathering all data from different teams to build a database with reference values.

During this edition, the main objective is to enhance measurements precision in synthetic biology by detecting and correcting sources of errors. Last year, the goal was to reduce variability in fluorescence measurements (GFP) with a normalization of OD. This year, we try to reduce this variability between labs by normalizing to absolute CFUs (colony-forming units).

DEVICES

For this study, we had to transform six plasmids and two controls:

  • Negative control BBa_R0040: sequence for pTet inverting regulator, corresponding to TetR repressible promoter.
  • Positive control BBa_I20270: promoter and GFP sequence.
  • And six GFP expressing constitutive devices:
    Device 1 BBa_J364000
    Device 2 BBa_J364001
    Device 3 BBa_J364002
    Device 4 BBa_J364007
    Device 5 BBa_J364008
    Device 6 BBa_J364009.

FIRST APPROACH

The first approach consists in converting between absorbance of cells to absorbance of a known concentration of beads.

Absorbance of a known concentration of beads

First, we did a calibration, using LUDOX CL-X, to obtain a conversion factor (Figure 1). This factor enables us to transform absorbance data from our plate reader into a basic OD measurement which can be found in a spectrophotometer.

LUDOX CL-X H2O
Replicate 1 0.085 0.069
Replicate 2 0.085 0.066
Replicate 3 0.086 0.064
Replicate 4 0.090 0.064
Arith. Mean 0.087 0.066
Corrected Abs600 0.022 /
Reference OD600 0.063 /
OD600/Abs600 2.930 /
Figure 1: Results of the first calibration. The experiment was performed 4 times. The row colored in red shows our conversion factor

Then, we carried out a second calibration, using silica beads in a microsphere suspension, to convert absorbance measurements into a number of cells. This conversion is based on the plotting of a standard curve of particle concentration (Figure 2) that we have determined during this calibration.

Figure 2: Our particle standard curve based on silica beads measurements.



We did the same work creating a standard curve of fluorescence for fluorescein concentration. Then, we had to use this to transform our cell based readings into a fluorescein concentration.

Figure 3: Our fluorescein standard curve based on fluorescence measurements.

Absorbance of cells

After calibrations, we began cell culture expression measurement. For that, we did overnight cultures of two colonies for each device. 24 hours later, we measured absorbance and fluorescence of growing cultures with our plate reader. Then, we used our fluorescence standard curve to transform our cell measurements into fluorescein concentrations (Figure 4).

Hour 0

Neg. Control Pos. Control Device 1 Device 2 Device 3 Device 4 Device 5 Device 6
104.00 165.00 496.00 237.00 -13.00 444.00 237.00 216.00
35.00 129.00 457.00 252.00 -50.00 381.00 137.00 150.00
39.00 111.00 504.00 197.00 -51.00 433.00 209.00 156.00
-24.00 118.00 426.00 156.00 -17.00 -92.00 156.00 170.00
47.00 149.00 612.00 279.00 -40 581 240.00 177.00
61.00 122.00 588.00 258.00 -34.00 564.00 166.00 132.00
61.00 138.00 604.00 281.00 -44.00 576.00 224.00 156.00
59.00 119.00 559.00 239.00 -27.00 524.00 154.00 112.00


Hour 6

Figure 4: Results for fluorescence per particle at hour 0 and hour 6.


According to those results, we can deduce the strength of each promoter.
Device 1 (BBa_J364000): high strength
Device 2 (BBa_J364001): high strength
Device 3 (BBa_J364002): low strength
Device 4 (BBa_J364007): high strength
Device 5 (BBa_J364008): medium strength
Device 6 (BBa_J364009): medium strength

SECOND APPROACH

This second approach involves counting how many colonies grow on a plate. With this number, we have determined a cell concentration for each sample. Then, with CFU values for positive and negative control samples, we calculated a conversion factor from absorbance to CFU.

Example for a final dilution factor of 8.105

First, we counted the colonies on each plate.

Sample Number of colonies
1.1 34
1.2 73
1.3 93
2.1 137
2.2 71
2.3 64
3.1 44
3.2 40
3.3 65

Secondly, we multiplied the colony count by the final dilution factor. Then, we obtained the CFU/mL.

Sample CFU/mL
1.1 2.72 107
1.2 5.84 107
1.3 7.44 107
2.1 1.10 108
2.2 5.68 107
2.3 5.12 107
3.1 3.52 107
3.2 3.20 107
3.3 5.20 107