Matching and Testing
The dynamics pattern of each pair of pInv-gen and pInv-rep
![Fig-T-5: The elements of our concern in invertase module. Through changing such components we wish to understand their property and illustrate an optimized combination of them.](https://static.igem.org/mediawiki/2015/thumb/f/f1/LDW-5.jpeg/719px-LDW-5.jpeg)
We co-transform pairs of pInv-gen and pInv-rep into E. coli BL21(DE3) or Top10, and have measured till now 13 different combinations them (see Table-T-1). A detailed pattern of relationships between time and RFU/OD can be hence revealed. Most of our data indicate the RFU/OD – time graphs shares a similar pattern (See Fig-T-6). The signal of Cre fused with EGFP stably increase after induction, perhaps a linear relationship; the mcherry signal, however, resembles an S-type curve that show a tiny or no growth and suddenly erupt a period after induction. Later, the increasing rate damped and the curve moves to a plateau phase. But technically, each pattern is slightly different because the molecular element of in this pathway varies from each other.
There are 3 major variants in this study, invertase (itself), promoter, and the ssra-mediated degradation, and additionally the fusion site of EGFP onto invertase does significantly count (See Fig-T-5). Using a series of combination of these variants we can understand their effect on invertase module.
![Table-T-1: A detailed list of information of each pInv-rep and pInv-gen in this study.](https://static.igem.org/mediawiki/2015/thumb/f/fa/LDW-T.png/800px-LDW-T.png)
![Fig-T-6: The measured dynamics pattern of all 13 combinations of pInv-gen and pInv-rep. For relationship of group name and there corresponding device, please check Table-T-1.](https://static.igem.org/mediawiki/2015/f/fa/LDW-6-1.jpeg)
This mission require us to utilize a method to quantitatively understand the in vivo enzymatic dynamics of each invertase, and the system we conduct such experiment must be reconstruction-friendly, since we have to test a variety of elements (e.g. promoter and ssra) in similar pattern to most accurately obtain data. Hence, we developed a real-time invertase dynamics testing system to observe the performance of each combination of different elements.
System construction
The real-time invertase dynamics testing system contains two different plasmids in E. coli (see Fig-T2). The first one is an invertase generation vector, namely pInv-gen, that produces invertase-EGFP fusion protein through induction. The second one is called pInv-rep, a reporter vector that produce mcherry signal to indicate the inversion successfully happens. The invertase-EGFP on pInv-gen is controlled by an inducible promoter (T7-LacO promoter or Pbad). The target sequence (RTS) of corresponding invertase locates in the pInv-rep, surrounding a mcherry gene which is yet upside-down and transcribed by a constructive promoter (e.g. BBa_J23101). This mcherry-coding sequence can be inverted and restored to 5’ – 3’ direction at the existence of Cre-GFP, rendering red signal. Additionally, an ssra tag that intensifies the protein degradation may be fused to the C-terminus of invertase-EGFP and mcherry to be in tune with our final device that aims to clean up the redundant invertase not participating in a second round inversion.
Once if the inducer is added into the culture, the green fluorescence will increase at first due to the expression of invertase-EGFP. Then, the red fluorescence is generated because the Cre-EGFP restores the reversed mcherry sequence (see Fig-T-3). The length of interval between green and red indicates the corresponding single timing length of the invertase module. In our study, the variants to render different time length are invertase itself, promoter, and the degrading rate by ssra. Specifically, the activity level of invertase directly determines the time need to invert most of pInv-reps, and the promoter decides the rate of generation of invertase, which also contribute sigfificant to the speed of module. The ssra-tag, on the contrary, reduces the speed of inversion while effectively inhibiting the leakage expression when inducer is not in the culture.
Achievement
We uses this system to measure totally 21 pairs of different combination of pInv-gens and pInv-reps. There are 6 different invertases we have tested using the Real-time system. While Cre and Flp are most commonly used recombinases in Biobrick plates, we newly contributed 4 brand-new invertases: Dre, Vcre, Scre, and Vika, all of which are Cre-family recombinases with different and non-intervolving RTS. We successfully proved that all these invertase work pretty good in our system, which you can see in RESULTS. All of the data we gather are analyzed by modeling group to render its corresponding time length. This work could guide other groups for their final design.
Timer design plug-in
Additionally, we prepared a website plug-in to for potential users to design their own timer with specific length of counting time, a project in cooperation with SYSU-software. According to the data gathered in this research and other promoter intensity given by iGEM official page, we can anticipate the overall timing length of any given combination of various invertase module. Vice versus, if a user could provide his/her target time, we can automatically generate one or more optimized design of Micro-time to precisely match the demand.
Bacteria Timer
Introduction
A report from Science[1](在本版面最后添加参考文献), by which we were inspired, tries to explain that synthetic gene networks can be constructed to emulate a cellular counter that would enable complex synthetic programming and a variety of biotechnology applications.
One of the figures (fig. 1) from this article indicates how genes can work in a counting system by reversal of recombinases. Two recombinases in the circuit, Flpe and Cre, in conjunction with their specific recognition site, FRT and LoxP, accomplishes the whole flipping process. Convenient to distinguish, we'll call it circuit 1.
Based on Circuit 1, we designed what we call circuit 2 (fig. 2) , which is, to our perspective, more functional and less induced, by principally altering the location of genes.
The comparison between them indicates 2 advantages of circuit 2 over circuit 1 (fig. 3) .
First, it continues transcripting and flipping in a circulation once induced. It happens theoratically because it may be bothered by objective resistence, but it provides us with a possibility to time gene reaction and control certain protein expression in a time scale.
Second, circuit 2 can transfer certain DNA sequences unit after unit. Imagine if there is a target gene between the first frt and loxP in the initial phase, it would pass on and on in the continuous units after flipping.
Construction
Due to time limits, we focused on constructing circuit 2, our original design.
We added florescent protein eCFP(标上砖号) and mCherry(标上砖号) right in the downstream of the ssrA-tag of recombinase flpe and cre, respectively. And we add a final GFP(标上砖号) as a reporter. pSB1C3 was used as vector for cloning and we tried to transfer the entire circuit to pSB3K3 in order to test its viability (fig. 4) .
In terms of ligation efficiency, we resembles small fragments (promoters, FRTs and LoxPs) and deliver them to IDT for complete synthesis. Then we ligate long fragments in between according to our design (fig. 5) . Worth of attention, we created a new "2A" assembly by using DNA clean up and arranging gene segments with different resistances (fig. 6).
Testing
Experimental proof must be accomplished after construction.
2 objectives for circuit 2 must be achieved during testing. One is that we must prove it actually has capability to reverse. The other one is that we must test its efficiency and explore how close it is to an ideal biological device that can really calculate time.
For the first goal, we thought that it could be solved by digestion (fig. 7) . When sequences flip, certain restricted enzyme cutting sites won’t change. What have changed are their locations. Gene length can be altered when sequences reverse, which can be visualized in an elecrophoretic way, as shown in fig. 7.
For the second goal, we used qPCR to verify feasibility of the circuit. We design primers shown in the picture (fig. 8) . We can tell from amplication curves (fig. 9) whether it reverses and calculates time when phases have altered.
Yeast Timer
(Our project, micro-timer, is to construct a counter on DNA that can imprint time on microbes.)
Micro timer 2.0 (Eu-timer) is constructed by DNA-based counting motifs that are inserted into different sites of chromosomes, creating a relatively large-scale system with more motifs than that in Micro timer 1.0.
The Eu-timer uses recombinases from Ser family such as Bxb1, which typically catalyzes site-specific recombination between an attachment site on the infecting phage chromosome (attP) and an attachment site in the host chromosome (attB) in natural system. The resulting integration reaction inserts the phage genome into the host chromosome bracketed by newly formed attL and attR (LR) sites. When attB and attP are engineered to be opposite BP sites, the integrase alone catalyzes the inversion of sequences flanked by BP sites, changing BP sites into LR sites, and will not revert the DNA flanked by LR sites.
In the design of Eu-timer (Fig 1) , each inverted promoter flanked by BP sites is downstream of an inverted reporter gene and followed by a ser integrase gene. The reporter i(inverted reporter gene)-attP-promoter i-attB-integrase unit is defined as a counting motif, named eu-timer integrase motif (EIM).
The circuit can be programmed to record time by counting a specific type of events like the expression of cyclins. Once the motifs are activated, the downstream expression can work automatically and will not be terminated or reset by the hosts themselves, which is the reason why we believe that such a system can imprint “the same time” on microbes derived from a single clone.
We then designed an telomere-like device by making little changes upon Micro timer 1.0, named Micro timer 1.1 (Fig 2) , in which the flanking site are of same direction. With every cell division, this device will sequentially truncate a part of the sequence, and finally lead to cell death, working like telomere.
Modelling
First of all, we get two tables of one certain combination, including different kinds of plasmid with certain type of promoter, invert-ase together with its recognition site on the reporter and a ssra tag of a specific intensity which we will calculate later. From the second table in each group, we show the RFU changing with respect to time and obviously it reflects the quantity of the protein. The second derivative of the fitting curve is the enzymatic activity, which is the product of the enzymatic activity of one single enzyme at a given moment and the total quantity of the enzyme. Now let consider it separately. As for the enzymatic activity, we use the Michaelis-Menten equation to describe it.
S in this equation is the quantity of the plasmid to be inverted in the bacterial population per volume . S= S initial value-the first order integral of V0. So the expression of V0 is an ODE model. Another important fact that we need to take into consideration is that since the quantity of the plasmid to be inverted in the bacterial population per volume is limited, the total feedback is on the enzymatic activity. So the ODE model can be only used from the start moment till the first derivative of the curve reaching its maximum. As for the quantity of the enzyme, we can use the cftool in matlab to fit a function to show the quantity with respect to the time using the data in the first table of each group. However, in order to get the total quantity of the enzyme produced in the process we must add the expression leakage of RFU (expression: OD0/OD * G0 . OD0 is the first line of the first table in moment 0. OD is shown in table 3. G0 is also constant. ) to the actual value of the RFU in the first table of each group which supposed to be linear. Up to now, we can get the coefficient Vmax and Km in this function, that is, we get the exact function of the fitting curve of the second table in each group. In order to get the rest part of the function, let’s move forward to the meaning of the first order derivative of the fitting curve = quantity of inverted promoters equal (=S) * promoter intensity – the degeneration rate of the protein with the ssra tag – the nutrition correction equation which called Logistic equation. The degeneration rate of the protein with the ssra tag can be obtain in the following method. We use the principal component analysis on each four difference between row OCG and OCGS, OGC and OGCS, MCG and MCGS, MGC and MGCS of the same line which means at the same moment, to integrate one data for each line. Then we use the data at moment 0,1,2 and so on to construct the function of the degeneration rate of the protein caused by the ssra tag using the cftool in matlab.
Now we get the complete function of the second table and the constant Vmax and Km, which is the property of the certain kind of enzyme we use in each group.
The abbreviation of the term in each row.
Now we use the data of MCG group as an example, the fitting curve of the second table is the red one, the blue one is the scatter diagram linked together with line showing quantity of the enzyme with respect to the time and since we know the form of the function is linear, we can easily derivate the exact function by fitting.