Difference between revisions of "Team:EPF Lausanne/Interlab"

 
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          <h1>What are we talking about?</h1>
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          <h1>What are we talking about?</h1>
          <p>In science, and in the field of synthetic biology in particular, characterizing new devices turns out to be as important as conceiving them. This not only provides a “how to use” guide for future users of your part but also allows the discovery of biologically relevant information about how it functions. When it comes to iGEM, the importance of characterization reaches huge proportion since thousands of new parts are registered each year. As a matter of fact, last year the competition launched its first InterLab Study, inviting every participating team to collaborate to measure previously existing devices. In addition to providing robust and statistically useful data, the InterLab Study aims at assessing how those measurements vary between labs. How similar are data from two teams using the same protocol? How well are the ratios conserved using two different measurement equipment? This year, these questions will be answered for the three constructs each team was given. They each contained a promoter from the widely used Anderson promoter collection that controlled the expression of a GFP (see description below). We contributed this year by measuring the three constructs in biological triplicates with a flow cytometer, which allowed us to assess the cell-to-cell variability of our samples. As part of the extra-credit assignment, we also provided technical triplicates of our data, thus determining the precision of the measurements. Beside the study, we were also able to integrate obtained data in our project since our reporter plasmid had its GFP controlled by J23117. </p>
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          <p>In the field of synthetic biology, characterizing devices is as important as conceiving them. This is <!-- a voir--> a major concern when it comes to iGEM, where thousands of new parts are registered each year. As a matter of fact the competition launched last year the first edition of the InterLab study. This additional section <!-- aaah--> of the competition invites each participating team to measure fluorescence of various constructs. Not only does the study provide large data for characterization but it also aims at assessing the variation in the measurements from different labs. How similar are the measurements when using the same bacterial strain, the same protocol or the same instrument? and what if they are different? This year, these questions are addressed by teams based on three constructs. Each of these contains a GFP gene controlled by a different promoter from the
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<a href="http://parts.igem.org/Promoters/Catalog/Anderson" > Anderson promoters collection</a>. These promoters derive from the initial J23119 promoter, in which mutations have been introduced to create the other members of the collection. Their different tightnesses establish a fine gradient for protein expression.  iGEM had us analyze the fluorescence of J23101, J23106 and J23117. Their relative strength are 0.7, 0.47 and 0.06 respectively, measured by Anderson and the 2006 iGEM Berkeley team. We contributed this year by measuring three biological replicates per promoter and fulfilled the extra-credit assignment by also providing technical triplicates for each of them. We were able to integrate the results we obtained into our project since it also uses the J23117 promoter in one of our <a href="https://2015.igem.org/Team:EPF_Lausanne/Part_Collection" > reporter plasmids </a>. </p>
 
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<h2>Tested constructs</h2>
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<h2>Tested constructs</h2>
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<img src="https://static.igem.org/mediawiki/2015/e/ee/EPF_Lausanne_J23101.png" alt="J23101" width=70% height=70%>
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<img src="https://static.igem.org/mediawiki/2015/e/ee/EPF_Lausanne_J23101.png" alt="J23101" width=70% height=70%>
 
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<a href="http://parts.igem.org/Part:BBa_J23101" > BBa_J23101
 
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<a href="http://parts.igem.org/Part:pSB1C3" > pSB1C3
 
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<br> Sequencing can be found here
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<a href="https://static.igem.org/mediawiki/2015/0/0c/EPFL_SequencingJ23101.pdf" > Sequencing can be found here
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<br> Sequencing can be found here
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<a href="https://static.igem.org/mediawiki/2015/1/1d/EPFL_SequencingJ23106.pdf" > Sequencing can be found here
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<a href="https://static.igem.org/mediawiki/2015/e/e1/EPFL_SequencingJ23117.pdf" > Sequencing can be found here
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<h1>How did we achieve this?</h1>
<h1>How did we achieve this?</h1>
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The construction of the three devices was achieved using the BioBrick cloning system. Plasmids pSB1C3 containing promoters J23101, J23106 or J23117 were <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#restriction" >opened</a> using <a href="http://ch.promega.com/products/cloning-and-dna-markers/restriction-enzymes/spei/" >SpeI</a> and <a href="https://www.neb.com/products/r3140-psti-hf" >PstI</a>enzymes while plasmid pSB1A2 containing I13504 was digested with <a href="https://www.neb.com/products/r0145-xbai">XbaI</a>and <a href="https://www.neb.com/products/r3140-psti-hf" >PstI</a>. pSB1C3-J23101, pSB1C3-J23106 and pSB1C3-J23117 were <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#dephosphorylation" >dephosphorylated </a> with antarctic phosphatase in order to prevent self-ligation. I13504 was finally <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#t4ligation" >ligated</a> with each of the open promoter-containing pSB1C3 plasmids using T4 ligase. Constructs were run on a <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#agarosegel" >1.2% agarose gel</a>, <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#gelextraction" >purified</a> and <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#transformation" >transformed</a> in DH5alpha high-efficient bacteria to be finally plated on chloramphenicol <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#lbagar" >LB agar plates</a>. Three colonies per plate were cultured overnight as biological replicates in 5mL <a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols#lbmedium" >LB medium</a> with chloramphenicol in test tubes. Cultures were spun down and pellets resuspended in 1mL PBS. Samples were measured by <a href="http://www.bdbiosciences.com/us/instruments/research/cell-analyzers/bd-accuri-c6/m/1294932?cc=US" >Accuri c6 Flow-Cytometer (BD)</a> and data was acquired three times with 20 minutes intervals.
The construction of the three devices was achieved using the BioBrick cloning system. Plasmids pSB1C3 containing promoters J23101, J23106 or J23117 were opened using SpeI and PstI enzymes while plasmid pSB1A2 containing I13504 was digested with XbaI and PstI. pSB1C3-J23101, pSB1C3-J23106 and pSB1C3-J23117 were dephosphorylated with antarctic phosphatase in order to prevent their self-ligation. I13504 was finally ligated with each of the open promoter-containing pSB1C3 plasmids using T4 ligase. Constructs were run on a 1.2% agarose gel, purified and transformed in DH5alpha high-efficient bacteria to be finally plated on chloramphenicol LB agar plates. Three colonies per plate were cultured overnight as biological replicates in 5mL LB medium with chloramphenicol in test tubes. Cultures were spun down and pellets resuspended in 1mL PBS. Samples were measured by Accuri c6 Flow-Cytometer (BD) and data were acquired three times in arbitrary units.
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More information are available in our InterLab Protocol, InterLab Worksheet and in our
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<a href="https://2015.igem.org/Team:EPF_Lausanne/Notebook/Protocols" > Protocol
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<h1>What did we obtain?</h1>
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Fluorescence of constructs is given in arbitrary units as the mean of the three measurements of the biological triplicates. Figure 1 shows these results, in which the error bars stand for the standard deviation calculated across triplicates. We estimated the promoters to be different from each other and formally assessed this statement by calculating the p-values. They were all less than 10<SUP>-5</SUp>, thus proving our assumption to be true. However, it was more relevant to express fluorescence in ratios to get rid of the arbitrary units. We plotted them with those calculated by Christopher Anderson (Figure 2) and we were surprised by the huge discrepancy between the two data sets. J23101/J23106 ratios are similar to each other (1.67 fold difference) but the J23101/J23117 and J23106/J23117 ratios we obtained are much higher than Anderson’s (27 and 16 fold respectively). This first glimpse into inter-laboratory variation is very instructive and shows how challenging reproducing exact measurements can be. The gap between ratios for J23117, the tightest of the 3 promoters, may be due to the fact that it is more difficult more measure low fluorescence levels precisely. Furthermore, it is possible that Anderson a different instrument, chassis or protocols. Unfortunately, we were not able to find all the details of his experiments. We are curious to see what results the other teams obtained and whether they made similar hypotheses.
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                  <a href="https://static.igem.org/mediawiki/2015/5/52/EPFL_Interlab2_Fig1.png"><img src="https://static.igem.org/mediawiki/2015/5/52/EPFL_Interlab2_Fig1.png" alt="" width="50%"></a>
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                  <figcaption><b>Fig.1</b> - Mean of fluorescence expression of K12 DH5alpha E.Coli with three constructs: pSB1C3 with J23101+I13504, pSB1C3 with J23106+I13504, pSB1C3 with J23117+I13504. Error bars represent the standard deviation across replicates. Results are given in arbitrary units. </figcaption>
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                  <figcaption><b>Fig.2</b> - Fluorescence ratios between the three constructs containing the three different promoters from the Anderson collection: J23101, J23106 and J23117. In yellow are the ratios obtained by our team (EPFL 2015), measured with a flow cytometer, and in red are those obtained by Christopher Anderson and the 2006 Berkeley team. While J23101/J23106 ratio is rather conserved between the two measurements, J23101/J23117 and J23106/J23117 ratios are dramatically different. This is probably due to the presence of J23117 that is a weak promoter and making precise measurement harder to perform. </figcaption>
We plotted the constructs’ mean of fluorescence across the three measurements of the three biological replicates (Fig.1). As units were arbitrary, we also expressed the ratio between the three promoters (Fig.2) which gives a more relevant information about difference in GFP expression. As showed in the figure, we compared our results with the measured strength of those promoters from the Anderson collection (lien vers la page). While the J23101/J23106 ratio is quite similar to the one measured by Anderson himself (only 1.67 fold difference), J23101/J23117 and J23106/J23117 ratios vary from 27 and 16 fold respectively between our results and Anderson’s. A plausible explanation for such discrepancy could be the variation between measurement instruments. While we used a Flow-Cytometer that allows finer measurements of week constructs such as J23117, it is likely that Anderson used a plate reader or another instrument. Also, the different chassis or protocol used to prepare samples could also impact on GFP expression. Those differences are precisely what the InterLab Study intends to shed light on and we are curious to see the results that other iGEM teams will obtain.
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                        <a href="https://static.igem.org/mediawiki/2015/a/ad/EPFL_Interlab_Fig1.png"><img src="https://static.igem.org/mediawiki/2015/a/ad/EPFL_Interlab_Fig1.png" alt="" width="75%"></a>
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                        <figcaption>Fig.1 - Mean of fluorescence expression of K12 DH5alpha E.Coli with three constructs: pSB1C3 with J23101+I13504, pSB1C3 with J23106+I13504, pSB1C3 with J23117+I13504. Results are given in arbitrary units. </figcaption>
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                        <a href="https://static.igem.org/mediawiki/2015/5/5b/EPFL_Interlab_Fig2.png"><img src="https://static.igem.org/mediawiki/2015/5/5b/EPFL_Interlab_Fig2.png" alt="" width="75%"></a>
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                        <figcaption>Fig.2 - Fluorescence ratios between the three constructs containing the three different promoters from the Anderson collection: J23101, J23106 and J23117. In blue are the ratios obtained by the our team (EPFL 2015), measured with a Flow-Cyotemeter and in yellow are those obtained by Christopher Anderson and the 2006 Berkeley team. While J23101/J23106 ratio is rather conserved between the two measurements, J23101/J23117 and J23106/J23117 ratios are dramatically different. This is probably due to the presence of J23117 that is a weak promoter and making precise measurement harder to perform. </figcaption>
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Nevertheless, while waiting for the InterLab results to come out, we found interesting to investigate variations among our own samples or, in other words, to lead an IntraLab study. For that purpose, we reproduced as much as possible the same experimental conditions while making our cultures grow, this way avoiding some unwanted variation due to sample preparation. We first compared technical replicates from a same colony. Each of the three technical replicates had 100’000 individuals measured. After eliminating the noise from our data, we approximated the fluorescence to be normally distributed across single cell measurements due to their large number. In order to determine if technical replicates were significantly different, we calculated confidence intervals for each one of them. Based on the Bonferroni correction (as we are comparing three measurements), we set the confidence level at 99.2% instead of the commonly used 95% level. Despite large samples number per measurement, we were surprised to see that about two third of the technical replicates were significantly different. Figure 3 displays a typical example where we can clearly see how the first two measurements are contained in each other’s CI while the third is clearly out. Unless samples were not sufficiently homogeneous, meaning bacteria were agglomerated in population clusters expressing different fluorescence levels and which seems quite unlikely, we can state that despite their great accuracy, measurements had a significant difference with each other. Increasing the statistical robustness could then be achieved by doing more than three technical replicates and consider each median as a part of a normal distribution itself. This will also allow measuring the proper variation due to the flow cytometer and obtaining a more precise mean of fluorescence for each construct.
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                        <a href="https://static.igem.org/mediawiki/2015/c/c5/EPFL_Interlab_Fig3.2.png"><img src="https://static.igem.org/mediawiki/2015/c/c5/EPFL_Interlab_Fig3.2.png" alt="" width="75%"></a>
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                        <figcaption>Fig.3 - Median of fluorescence from three measurements of one biological replicate of pSB1C3 with J23106+I13504. Bars represent a 99.2% confidence interval to assess if the measurements are significantly different from each other. Measurements 1 and 2 are not significantly different on a level of 99.2% because they are framed by the CI of the other. Measurement 3 on the other hand is significantly different on the same level since it is not included  in other measurements CI. </figcaption>
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Along with the technical variation, we also compared the different biological replicates. And we were blown away by how two colonies with the same exact plasmids could have so different fluorescence expression. Figure 4 shows how wide the gap is between colonies. Unlike Figure 3, it is not possible to clearly see CI bars on this figure since they are extremely small compared to median differences. This result is nevertheless reassuring in a way since it proves technical difference is less than biological one, which should appear as obvious due to the stochastic basis of a living organism. This huge biological variation can also be used to explain technical variation. 100’000 organisms are maybe not sufficient to have a comprehensive sample of the population. This explanation could be assessed by increasing the number of bacteria sampled per measure, for example by a 10x factor. So if the biological variance is so important, what can we expect from the comparison of fluorescence from two different chassis? That’s what we are eager to learn during the Giant Jamboree!
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                        <figcaption>Fig.4 - Mean of fluorescence expression of K12 DH5alpha E.Coli with three constructs: pSB1C3 with J23101+I13504, pSB1C3 with J23106+I13504, pSB1C3 with J23117+I13504. Results are given in arbitrary units. </figcaption>
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          <h1>What did it bring to us?</h1>
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<h1>IntraLab Study</h1>
          <p>Finally, those results bring up a lot of new insights on or project that aims at making cells possess the circuits of a machine. How could this information be integrated in the design of a system like ours? We can imagine for example applying a selection mechanism to organisms, somehow like it has been done in agriculture and for the cattle in man history. To comply with the rigid structure imposed by logic gates, bacteria must work in the most similar way and of course are expected to be the most efficient ones. This final comment underlines what we wanted to prove at the beginning: measuring is equally important as creating. A powerful system is the product of the strong and bilateral interaction between those two concepts.  </p>
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While waiting for InterLab results to come out at the Giant Jamboree, we investigated fluorescence variation among our own measurements, carrying out what we called an IntraLab Study. This also implies slightly changing the focus: instead of different strains, we compared different colonies (biological replicates) and analyzed the variability in measurements with only one instrument, rather than between instruments.
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Each flow cytometer measurement computed the fluorescence of 100’000 cells. Based on this high number and on the shape of its distribution, we assumed the fluorescence to be normally distributed. Doing so, we also approximated the mean by the median. We first performed z tests on technical replicates and biological replicates in order to see any significant difference among them. We used a confidence level of 0.8% instead of 2.5% on the basis of the Bonferonni correction principle. We noticed that p-values for biological replicates were all less than 10<sup>-5</sup> confirming the strong difference between them. Fluorescence varied in fact from 20% to 30% in intensity among the colonies, constituting an important disparity (Figure 3). This tells us that colonies from a same transformation can behave very differently. This is probably due to how well the plasmid integration occurred in each. As pSB1C3 is high-copy, there are also many distribution possibilities for the number of plasmids in each cell.
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<figcaption><b>Fig.3 </b>- Mean fluorescence of three biological replicates of the construct containing J23101 promoter. The mean was calculated across the three measurement and error bars display the associated standard deviation. We notice first colony is 30% smaller than the third. </figcaption>
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We then looked at the variation among technical replicates. This time, we obtained 75% of triplicated had a p-values under 0.08, meaning they were significanty different. We were puzzled by this result because we calculated only 1% variation between fluorescence measurements. Therefore, we decided to run a more robust Fisher test on our data. At a 0.05 level, p-values for J23101, J23106 and J23117 measurements were 0.065, 0.125 and 0.024 respectively. While the two first indicate no significant difference between measurement repeats in J23101 and J23106, the last suggests it is not the case for J23117. This promoter has a weak fluorescence, which might imply less accurate measurements. Nevertheless, we found those results to be odd, so we decided to plot each set of technical replicates next to each other (e.g. Figure 4). We discovered that fluorescence had a tendency to decrease over time in 80% of measured colonies of each promoter. It is unlikely that the instrument systematically caused a reduction in fluorescence. It was most likely due to a third factor, probably biological or physical. We immediately thought the PBS medium could have affected E.Coli metabolism triggering a loss of GFP expression. But as the variation is only 1%, despite this disruptive factor, we can firmly affirm the flow cytometer provided accurate measurements.
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                  <figcaption><b>Fig.4</b> - Median of fluorescence of technical replicates of the second colony of the J23106 containing construct. Bars represent a confidence interval at the level of 0.8% and state clearly the significant difference between the three measurements. Moreover, we observe a clear decrease of fluorescence over time since the three measurements were performed one after the other.  </figcaption>
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        <h1>What did it bring us?</h1>
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        <p>The InterLab and IntraLab studies taught us interesting lessons and brought new insights to our project. First, we saw how setting up an experiment requires thorough thinking about multiple parameters. If we had the time, we would have carried out more measurements, to compare how time spent in PBS really impacted on the fluorescence of our cells. Secondly, we did not expect colonies with similar DNA contents to behave so differently. In a project like Bio LOGIC, precision and stability are major features since we want cells to reproduce computer-like transistors. One way of getting around this variation problem would be the selection of clones through many batches of test. In conclusion, those two examples proved the importance of measuring devices, as said in the beginning. A good system is based on the interaction between design and measurements, who must constantly improve one another.
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Latest revision as of 01:11, 19 September 2015

EPFL 2015 iGEM bioLogic Logic Orthogonal gRNA Implemented Circuits EPFL 2015 iGEM bioLogic Logic Orthogonal gRNA Implemented Circuits

Interlab study

What are we talking about?

In the field of synthetic biology, characterizing devices is as important as conceiving them. This is a major concern when it comes to iGEM, where thousands of new parts are registered each year. As a matter of fact the competition launched last year the first edition of the InterLab study. This additional section of the competition invites each participating team to measure fluorescence of various constructs. Not only does the study provide large data for characterization but it also aims at assessing the variation in the measurements from different labs. How similar are the measurements when using the same bacterial strain, the same protocol or the same instrument? and what if they are different? This year, these questions are addressed by teams based on three constructs. Each of these contains a GFP gene controlled by a different promoter from the Anderson promoters collection. These promoters derive from the initial J23119 promoter, in which mutations have been introduced to create the other members of the collection. Their different tightnesses establish a fine gradient for protein expression. iGEM had us analyze the fluorescence of J23101, J23106 and J23117. Their relative strength are 0.7, 0.47 and 0.06 respectively, measured by Anderson and the 2006 iGEM Berkeley team. We contributed this year by measuring three biological replicates per promoter and fulfilled the extra-credit assignment by also providing technical triplicates for each of them. We were able to integrate the results we obtained into our project since it also uses the J23117 promoter in one of our reporter plasmids .


How did we achieve this?

The construction of the three devices was achieved using the BioBrick cloning system. Plasmids pSB1C3 containing promoters J23101, J23106 or J23117 were opened using SpeI and PstIenzymes while plasmid pSB1A2 containing I13504 was digested with XbaIand PstI. pSB1C3-J23101, pSB1C3-J23106 and pSB1C3-J23117 were dephosphorylated with antarctic phosphatase in order to prevent self-ligation. I13504 was finally ligated with each of the open promoter-containing pSB1C3 plasmids using T4 ligase. Constructs were run on a 1.2% agarose gel, purified and transformed in DH5alpha high-efficient bacteria to be finally plated on chloramphenicol LB agar plates. Three colonies per plate were cultured overnight as biological replicates in 5mL LB medium with chloramphenicol in test tubes. Cultures were spun down and pellets resuspended in 1mL PBS. Samples were measured by Accuri c6 Flow-Cytometer (BD) and data was acquired three times with 20 minutes intervals.

What did we obtain?

Fluorescence of constructs is given in arbitrary units as the mean of the three measurements of the biological triplicates. Figure 1 shows these results, in which the error bars stand for the standard deviation calculated across triplicates. We estimated the promoters to be different from each other and formally assessed this statement by calculating the p-values. They were all less than 10-5, thus proving our assumption to be true. However, it was more relevant to express fluorescence in ratios to get rid of the arbitrary units. We plotted them with those calculated by Christopher Anderson (Figure 2) and we were surprised by the huge discrepancy between the two data sets. J23101/J23106 ratios are similar to each other (1.67 fold difference) but the J23101/J23117 and J23106/J23117 ratios we obtained are much higher than Anderson’s (27 and 16 fold respectively). This first glimpse into inter-laboratory variation is very instructive and shows how challenging reproducing exact measurements can be. The gap between ratios for J23117, the tightest of the 3 promoters, may be due to the fact that it is more difficult more measure low fluorescence levels precisely. Furthermore, it is possible that Anderson a different instrument, chassis or protocols. Unfortunately, we were not able to find all the details of his experiments. We are curious to see what results the other teams obtained and whether they made similar hypotheses.


Fig.1 - Mean of fluorescence expression of K12 DH5alpha E.Coli with three constructs: pSB1C3 with J23101+I13504, pSB1C3 with J23106+I13504, pSB1C3 with J23117+I13504. Error bars represent the standard deviation across replicates. Results are given in arbitrary units.





Fig.2 - Fluorescence ratios between the three constructs containing the three different promoters from the Anderson collection: J23101, J23106 and J23117. In yellow are the ratios obtained by our team (EPFL 2015), measured with a flow cytometer, and in red are those obtained by Christopher Anderson and the 2006 Berkeley team. While J23101/J23106 ratio is rather conserved between the two measurements, J23101/J23117 and J23106/J23117 ratios are dramatically different. This is probably due to the presence of J23117 that is a weak promoter and making precise measurement harder to perform.

IntraLab Study

While waiting for InterLab results to come out at the Giant Jamboree, we investigated fluorescence variation among our own measurements, carrying out what we called an IntraLab Study. This also implies slightly changing the focus: instead of different strains, we compared different colonies (biological replicates) and analyzed the variability in measurements with only one instrument, rather than between instruments.


Each flow cytometer measurement computed the fluorescence of 100’000 cells. Based on this high number and on the shape of its distribution, we assumed the fluorescence to be normally distributed. Doing so, we also approximated the mean by the median. We first performed z tests on technical replicates and biological replicates in order to see any significant difference among them. We used a confidence level of 0.8% instead of 2.5% on the basis of the Bonferonni correction principle. We noticed that p-values for biological replicates were all less than 10-5 confirming the strong difference between them. Fluorescence varied in fact from 20% to 30% in intensity among the colonies, constituting an important disparity (Figure 3). This tells us that colonies from a same transformation can behave very differently. This is probably due to how well the plasmid integration occurred in each. As pSB1C3 is high-copy, there are also many distribution possibilities for the number of plasmids in each cell.




Fig.3 - Mean fluorescence of three biological replicates of the construct containing J23101 promoter. The mean was calculated across the three measurement and error bars display the associated standard deviation. We notice first colony is 30% smaller than the third.


We then looked at the variation among technical replicates. This time, we obtained 75% of triplicated had a p-values under 0.08, meaning they were significanty different. We were puzzled by this result because we calculated only 1% variation between fluorescence measurements. Therefore, we decided to run a more robust Fisher test on our data. At a 0.05 level, p-values for J23101, J23106 and J23117 measurements were 0.065, 0.125 and 0.024 respectively. While the two first indicate no significant difference between measurement repeats in J23101 and J23106, the last suggests it is not the case for J23117. This promoter has a weak fluorescence, which might imply less accurate measurements. Nevertheless, we found those results to be odd, so we decided to plot each set of technical replicates next to each other (e.g. Figure 4). We discovered that fluorescence had a tendency to decrease over time in 80% of measured colonies of each promoter. It is unlikely that the instrument systematically caused a reduction in fluorescence. It was most likely due to a third factor, probably biological or physical. We immediately thought the PBS medium could have affected E.Coli metabolism triggering a loss of GFP expression. But as the variation is only 1%, despite this disruptive factor, we can firmly affirm the flow cytometer provided accurate measurements.



Fig.4 - Median of fluorescence of technical replicates of the second colony of the J23106 containing construct. Bars represent a confidence interval at the level of 0.8% and state clearly the significant difference between the three measurements. Moreover, we observe a clear decrease of fluorescence over time since the three measurements were performed one after the other.

What did it bring us?

The InterLab and IntraLab studies taught us interesting lessons and brought new insights to our project. First, we saw how setting up an experiment requires thorough thinking about multiple parameters. If we had the time, we would have carried out more measurements, to compare how time spent in PBS really impacted on the fluorescence of our cells. Secondly, we did not expect colonies with similar DNA contents to behave so differently. In a project like Bio LOGIC, precision and stability are major features since we want cells to reproduce computer-like transistors. One way of getting around this variation problem would be the selection of clones through many batches of test. In conclusion, those two examples proved the importance of measuring devices, as said in the beginning. A good system is based on the interaction between design and measurements, who must constantly improve one another.

EPFL 2015 iGEM bioLogic Logic Orthogonal gRNA Implemented Circuits