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.
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.
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.
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.