Alonso-Gutierrez, J. et al. (2013). Metabolic engineering of Escherichia coli for limonene and perillyl alcohol production. Metabolic engineering, 19, 33-41.
 Dudley, Q. M. et al. (2019). Cell-free biosynthesis of limonene using enzyme-enriched Escherichia coli lysates. Synthetic Biology, 4(1), ysz003.
 Srividya, N. et al. (2015). Functional analysis of (4S)-limonene synthase mutants reveals determinants of catalytic outcome in a model monoterpene synthase. Proceedings of the National Academy of Sciences, 112(11), 3332-3337.
 Korman, T. P. et al. (2017). A synthetic biochemistry platform for cell free production of monoterpenes from glucose. Nature communications, 8(1), 1-8.
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 Walsh, C. T. (1989). Enzymes in the D-alanine branch of bacterial cell wall peptidoglycan assembly.The Journal of Biological Chemistry,264(5), 2393-2396.
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We love easy-to-modulate cell-free system. However, through our human practice activities during the initial phase of our iGEM project, we realized that Synbio and cell-free system are unrecognized from general public.
Thus, we selected the theme which is not only interesting as a story but also biologically important. Here was beginning of the story for information processing where mathematical modeling and wet experiment interacted each other through Design-Build-Test-Learn (DBTL) cycle.
This battle story also expanded into war in the mirror which can be broken by racemase. Our success in monoterpene productions for Zombie and Samurai also gave us an entry point for creation of our business model which was pivoted by interviews to experts.
Our experience in Synbio modeling was implanted in a smartphone application which we utilized when we had a chance to educate high school students. By using our user-friendly application, they could understand a behavior of toggle switch circuit, which was one of the first successes in Synbio and important to understand cell-fate decision in developmental biology and regenerative medicine.
The story we developed was the war between zombies and Samurai.
Both Zombie and Samurai are essentially human beings, but their states switch by some factor. Zombies are able to make Samurai join their group by releasing communication molecules. On the other hand, Samurai also try to save the companion.
At the end of the battle, the winner side is defined by the concentration of communication molecules in the field.
A genetic circuit for the Zombie and Samurai war consists of two sub-systems; toggle switch and cell-cell communication module (shown above).
The two states, Zombie and Samurai, are achieved by two stable states of a toggle switch circuit composed of two repressors each of which inhibiting gene expression of the other.
Problem of cell-free
In contrast to cellular system, a cell-free system lacks cell growth and has much smaller degradation-dilution term, which lead to longer operating time (shown as Fig.1).
We thus estimated operation time for state-switch between Zombie and Samurai in our cell-free system.
Degradation rate in cell-free
Figure 2 shows the relationship between this degradation rate and operation time for state switching.
The blue point is about normal protein degradation, and the green point shows the case of the LVA degradation tag are introduced on the protein.
Considering a system based only on normal protein degradation of a cell-free system without growth of volume, it takes too much time to operate a state-switch between Samurai and Zombie.
War in cell-free
Modeling - Zombies vs Samurai Scenario
Our simulation showed fate of the battle between Zombies and Samurai in the test tube.
Depending on initial concentration of components, we can prepare a Zombie test tube and a Samurai test tube which are stable state.
Then, by mixing Zombie and Samurai cell-free solutions in various ratios, the battle started. When Zombie state cell-free solution and Samurai state cell-free solution were mixed at a ratio of 2:8, the mixed solution was stable in the Samurai state.
This means that the Samurai have beaten the Zombie. However, a slight change of the ratio completely turned their fate. When the Zombie and Samurai solutions were mixed at a ratio of 3:7, the mixed solution was stable in the Zombie state and the Zombie will destroyed the Samurai.
Integrated modeling including crosstalk
Problem of crosstalk
Because of the same activation by Samurai signaling molecule for the both repressors, Samurai state seems to be not stable.
By additional effect from the messy crosstalk, two nullclines have only one intersection, and the system looses bistability (shown center of figure 1 below).
However, when we reduce the maximum expression by Rhl promoter to 1/10, phase space analysis shows both stabilities of Zombie and Samurai state (shown right of figure 1 below).
Integrated modeling including crosstalk
Moreover, for this modeling, we drew a timecourse of mixed Zombie and Samurai.
We found that even if we consider the crosstalk, the two powers can compete and be biased to either side depending on their ratios.
Therefore, Wet-Dry experiment cycle showed that our cell-free system works as designed in the scenario.
Modeling - differential-equations
In order to model our systems, we established differential-equations. In this modeling, we assumed the behavior of E. coli in vivo, and used parameters adjusted somewhat to behave as designed.
From the appearance of the nullcline (shown below), the equilibrium points are arranged in the same way as a normal toggle switch.
Modeling - Results
The graphs shown below illustrates the behavior of our gene circuit. When the zombie state cell is induced with a samurai signal, the cell fate will change depending on the size of the signal.
Thus, we were able to create two final states simply by changing the initial concentration of communication molecules
To see the improvement in degradation effect by LVA degradation tagging, we constructed an improved part (BBa_K3580003) by a modification of an existing part: Plux/tet-GFP(BBa_K934025).
Experiment - Results match in vivo and in cell-free!
In order to compare in vivo activity of these parts (BBa_K3580003 and BBa_K934025), we first measured the fluorescence of GFP 240 minutes after the start of induction.
The fluorescence of tagged GFP (BBa_K3580003) was lower than that of normal GFP (BBa_K934025) at 240 min point. This result shows that tagged GFP was successfully degraded as we planned.
Then, we compared the fluorescence of GFP in a cell-free system which consisted of cruedextract of E.coli containing luxR protein.
Because of the programmed degradation, the fluorescence of tagged GFP(BBa_K3580003) showed slight signal nearly equal to a negative control where neither the template GFP DNA nor the inducer AHL existed.
The results show that LVA degradation tagged protein can be degraded exceptionally both in vivo and in vitro.
Material and Method
Preparation of the cell extract for Cell-free system containing reporter protein.
We prepared cell extracts containing the luxR reporter protein according to the protocol stated in the LVA degradation tag experiment.
Crosstalk Assay using extract-based CFPS
Under each condition, the reaction composition solution was prepared as shown in Table1. Cell-free reactions were performed on a 20µl scale. The fluorescence of cell-free expressed reporter GFP was measured on a real-time PCR(Step One Plus Real-Time PCR System, Applied Biosystems, Mx3005P, Stratagene California) for 12 hours at 37°C and the measured fluorescence values were quantitatively calibrated by FITC.
MixA is a mixture of small molecules mainly required for translation and its composition is shown in Table2. below.
Crosstalk (Wet Experiment)
A potential problem for our scenario was crosstalk, a situation in which a promoter in a quorum sensing (QS) systems is activated unexpectedly by another type of QS components.
To confirm such crosstalk, we prepared two kinds of cell-free translation systems containing LuxR or RhlR transcriptional activator. We then put signaling molecule (3OHSL-C4 or 3OHSL-C6) and target genes (Plux/tet-GFP or Prhl-RR-GFP), respectively.
To quantitatively compare GFP fluorescence values among different runs, we adopted standardized measurement using FITC.
Firstly, we conducted the experiment in a cell-free system with RhlR protein. In contrast to strong activation in the combination among 3OC4HSL, RhlR, and Prhl(RR) promoter, the other combinations showed little fluorescence.
As shown in two red bars of Fig. 2, LuxR protein with 3OC6HSL activates not only Lux promoter but also Rhl promoter which receives crosstalk. Although we tested another LuxR-responsible promoter, PRhlLR, it showed another crosstalk from RhlR protein.
Scenario - War in the mirror
In the Zombie vs. Samurai storyline, we envisioned a battle between two enantiomers, that is to say, one side has D amino acid and the other has L amino acid derived food as their food source, and both sides converts their opponent’s amino acid and deprives the of their food(Fig.1).
Although there is not yet a translation and transcription system that efficiently incorporates D amino acids, it is known that the originally natural enzyme chemically synthesized with D amino acids would be active.
Overview - Alanine racemase
Such storyline can be applied to our real experimental system by adopting alanine racemase(AR) witch catalyze the conversion of L-alanine to D-alanine(Fig.1)[Walish 1989].
Since D-alanine is used as a necessary component of the peptidoglycan layer of bacterial cell walls, lack of alanine racemase can result in the inhibition of growth of prokaryotes [Azam et.al 2016].
Therefore, alanine racemase is recognized as an attractive target for antibacterial drug development [Azam et.al 2016].
Overview - Assayed the activity of AR in cell-free
We purified alanine racemase and assayed the activity of alanine racemase (AR) using Cell-Free-Protein-Synthesis(CFPS). Since the racemase supplies L-Ala for protein synthesis, its activity can be evaluated through the expression of a reporter protein.
The results demonstrated that GFP could not be synthesized by D-alanine alone, but L-alanine produced by racemase-mediated racemization of D-alanine and L-alanine could be used for translation, creating a situation in which fluorescence was restored by the synthesized GFP.
Alanine racemase is recognized as an attractive target for antibacterial drug development [Azam et.al 2016]. Consequently, we believe that our experimental system would be useful in pharmaceutical development.
Our experiments were conducted following the protocol below.
Cell-free monoterpene synthesis
How can we observers distinguish between zombies and samurai?
In our project we propose one unique identification method, though there is also a method using fluorescent protein.
We propose a method of distinguishing the scents of zombies or samurai.
For this project, we selected monoterpenes, especially limonene and sabinene, as the scented substances produced by zombies and samurai.
In this cell-free monoterpene synthesis, we mixed two E. coli extracts each of which has either first 8 or last 2 enzymes of a pathway from Ac-CoA, which is a major intermediate of cell central metabolism.
Through mevalonate pathway, the former extract one (derived from E. coli into which pBbA5c-MevT-MBI has been introduced) can provide IPP and DMAPP, which can also be used as intermediates for other important biosynthesis. Here we indeed supplemented only glucose and acetate as carbon sources.
In order to take advantage of an engineering principle of synthetic biology we provided two biobrick parts (BBa_K3580101 (New part), BBa_K3580102 (Improved part)) for the source for the latter extract. BBa_K3580101 has GPP synthase (GPPS) and limonene synthase.
Although GPP synthase is shared with BBa_K3580101, BBa_K3580102 has sabinene synthase, which has one point mutation in limonene synthase (Srividya Narayanan et al 2015) and a new coding sequence for Parts registry of iGEM (See here for more details on this experiments).
Cell-free monoterpene synthesis
We confirmed limonene synthesis GC/MS analysis with SIM. In this SIM analysis, ions with four m/z values characteristic in limonene (68 and 93) and sabinene (77 and 91, 93) were analyzed.
By using authentic limonene standard, we confirmed a retention time for GC and the characteristic limonene SIM signal at the specific m/z values. At the same retention time with the standard, limonene-specific m/z value (68, 93) ions were detected in the selected ions.
We also drew a GC chart by summation of the signals from the selected ions. By comparison with a negative control experiment which we omitted the extract containing GPP synthase and limonene synthase, we found clear peak from our limonene synthesis
By similar GC/MS analysis with SIM, we confirmed the world's first report of sabinene synthesis using cell extracts. As well as limonene detection, we firstly confirmed sabinene retention time and SIM signal at the m/z values (77, 91, and 93).
From our cell-free production, we then detected sabinene SIM signal and chromatogram peak which cannot find from the negative control.
Also, from the system containing sabinene synthase and GPP synthase, a peak with the same retention time as the standard limonene product and ions with m/z values characteristic in limonene at that retention time were detected.
Finally, each of monoterpenes were quantified based on peaks of substance having 93 m/z and each monoterpene standard curves.
Taking advantage of the modularity of the combination of extracts, we confirmed whether the yield of monoterpenes could be changed by changing the mixing ratio of the extract containing the enzyme of the mevalonate pathway and the extract containing GPP synthase and monoterpene synthase.
As a result, changes in the yield of monoterpenes due to the mixing ratio of the extracts were observed. The best yield of limonene per reaction solution with limonene synthase contained system was 0.978 µM, and the best yield of sabinene per reaction solution with sabinene synthase contained system was 6.13 µM
In order to promote dialogue with citizens, we exhibited at “RIKOTEN”, the science festival at our University. We asked participants on their awareness of synthetic biology and cell-free system before and after our lecture.
The survey results showed that participants were able to clarify their opinion on the topic after our exhibition.
Through dialog, we also found that the cell-free system is perfect for citizens to take the first step to understand synthetic biology.
Thus, we thought that by carrying out a cell-free system based project, we could promote safeness of synthetic biology with entertaining aspect of synthetic biology that we, iGEMers, enjoy.
Integration of Human Practices
Since the project began, we have continued to connect with the public.
At times, as educators, we have taught high school students. (Go to the Education page.)
At other times, as an entrepreneur, We carefully researched and brushed up on real-world programs. (Go to Entrepreneurship page.)
Through the interview about monoterpene business, we pivotted a business model of cell-free substance detection kit.
This kit is cheaper than existing kits and it can detect rapidly and robustly.
This kit is that it allows us to easily determine the balance of substances in a sample. This is our original technology made possible by our iGEM project.
We also will provide a software to support th DNA designing process.
Then, anyone create customized detection kit for yourself !
Interview - Future clients & Expert
1. Check the balance of the Bacteria used in sewage treatments. 2. Measure the Balance of malignant Substances in sewage treatment. 3. Simple kit for each household to ensure high quality tap water.
We interviewed experts who may become our future clients. Through the interview, we found three demands.
After the interview, we asked an expert on environmental bacteria for advice in the future. He asserted that he did't see any apparent technical problems and also mentioned the conditions in which testing must be conducted upon.
Future - We're already ready to launch!
Our project has a big potential, but through these interviews, we discovered some points that we should focus on. For example, the suggested need to check the operation of the kit in a mixture-rich environment led us to pay special attention as we progressed with crosstalk experiments.
Appendix - Further progress of our business from wiki
(B) Interview with the Sewerage Department of Tokyo
4. Specific strategies
AO (Anaerobic Oxic) and A2O (Anaerobic Anoxic Oxic) methods are used for sewage water treatment.
In these methods, phosphorus-storing bacteria are used to remove phosphorous (P) and nitrifying and denitrifying bacteria are used to remove nitrogen (N). However, both P and N are removed by the AO method. However, the removal of P and N are opposite functions. Therefore, if one of them becomes too strong, the removal of the other becomes insufficient. Under normal conditions, the rate of change is slow, but precipitation significantly changes the situation. Precipitation causes three to five times as much sewage to flow into the sewage treatment plant at once. When this happen, the condition of the activated sludge tank changes
greatly due to changes in the balance of the sewage components. There are many problems caused by the condition of activated sludge tanks in particular.
One major problem is the growth of malignant bacteria, such as actinomycetes. Actinomycetes surround the bacteria with mycolic acid, which prevents the bubbles from popping and causes bubbles to increase on the surface of the water. Since the acid is a substance that cannot be biologically treated, it remainsfloating on the surface of the water together with the activated sludge, which is unfavorable for solid-liquid separation in the sedimentation basin. In addition, suppressing the amount of air supply to prevent foaming causes problems such as not being able to supply the oxygen necessary for treatment, which worsens the quality of treated water, and the scum that remains on the surface of the water causes flies and odors to be generated.
In order to prevent these problems, there was a need to determinethe amount of actinomycetes and mycolic acid in the activated sludge and to measure the balance between them and various bacteria. They also pointed out that the kit may also be used as household tap water quality checking device.
(C) Advice from the academic side
In answering this demand, we asked Dr. Nishida, an expert on environmental bacteria, for advice on whether our detection kit is technically unfeasible and what we should consider in the future.
Dr. Nishida said that he did not see any apparent technical problems that were absolutely unattainable and we were ready to conduct a demonstration of our kit. He also advised us to focus on the operation in a confined environment (e.g., sewage) and the quantitative nature of the materials to be tested.
Appendix - SAMURAI System
ODEs used in the modeling of IFFL.
we constructed a heatmap to check how much time (t) of the pulse peak is delayed as we change the parameters Kx and Ky simultaneously in the folula (3). Fig. 4-2-4 is the results.
Other parameters are fixed as Table 4-2-4.
Furthermore, in order to evaluate the balance of the pulse shape, we calculated the ratio of the peak concentration and the following steady-state concentration for each parameter and presented it in a heat map.This is called the ratio heatmap. (Fig 4-2-5). The ratio is calculated as the formula (4).
Based on these two indicators,wemultiplied the cross heatmap by the value of the time heatmap and the ratio heatmap for each parameter in order to find out which parameter has both time difference and balance, comprehensively (Fig 4-2-6 right).To make this cross heatmap, we subtracted a certain constant number of time values from the time heatmap because we have to make the time delay above a certain level. If the time heatmap is negative, it is treated as 0.Let us call thistime_processed heatmap.Fig 4-2-6(left) is the time processed heat map, calculated by subtracting 4 from the all value of the time heatmap.The values of the cross heatmap were calculated as the formula (5).
We selected the optimal parameter for the multi IFFL in the resulting match heatmap as the one with the highest score. Two pulses were generated using the optimal parameter in practice (Fig 4-2-7) (Table 4-2-5, 4-2-6). Yellow indicates the temporal variation of the concentration of Z1 and green indicates that of Z2. As a result, we have succeeded in creating pulses with a time difference.
At initial stage of our iGEM activity, we realized that not only those with little scientific knowledge but also students who aspired to be scientists didn’t recognize synthetic biology. As iGEMers, who mainly work with synthetic biology, we felt the need to spread the knowledge of its potential to produce world-changing results in both engineering and physiological sciences.
This year, we’re attracting attention with an interesting story whose subject is gene circuit.
We tried to spread toggle switch, which was core of the circuit and starting point of synthetic biology.
We developed a smartphone application for better understanding of mathematical modeling of synthetic biology for the synthetic biology beginners.
Mathematical modeling is fundamental in synthetic biology, for engineering principle requires such modeling. We fortunately had a chance to lecture Waseda University High School students.
The lecture was held through a widely used video communication service, zoom.
Special achievement - World's first report!
* Confirmed rhl system activity and crosstalk in a cell-free system.
* Modeled in the cell-free system including crosstalk
* Sabinene synthesis using cell extracts.
* Our original methodology, based on the substrate specificity of the racemase, was able to demonstrate the high accuracy of the experimental PURE system.
* Proposal of substance detection kit to detect balance. (Business)
1. Competition Deliverables
We have created a Wiki page and a Poster page, released a Presentation Video and a Project Promotion Video, submitted the judging form. 2. Attributions
We have received lots of help from professors and other people during the development of our project. 3. Project Description
We conducted the project through DBTL, such a dialogue with general public, modeling, and wet experiments. 4. Contribution
We revealed that Prhl(RR)-GFP (BBa_K1529321) can work in vitro.
1. Engineering Success
We have proven that the functions of a constructed Alanine Racemase (BBa_K3580200) parts work as expected. 2. Collaboration
We collaborated with the 2019 iGEM Qdai Team to help each other's modeling. 3. Human Practices
Since the project began, we talked with the general public and confirmed the “safety” and “ethics” of our project around cell-free system. For more info, please refer to our Human Practices page (Wiki & Poster). 4. Proposed Implementation
We have proposed a business model based on the "SAMURAI System" (our project). For more info, please refer to our Implementation page (Wiki), Entrepreneurship page (Wiki & Poster).
1. Improvement of an Existing Part
To see the improvement in degradation effect by ssrA tagging, we construct a improved part (BBa_K3580003) by modification of an existing part: Plux/tet-GFP (BBa_K934025). For more info, please refer to our Degradation-tag page (Poster, Zombie vs Samurai 4). 2. Project Modeling
We modeled the genetic circuit for the Zombie and Samurai war. Then, We have also achieved more robust modeling that reflects the results of the wet experiment. For more info, please refer to our Zombie vs Samurai page (Wiki & Poster). 3. Integrated Human Practices
We have repeated dialogs and created a business model for socially implementing the project. For more info, please refer to our Entrepreneurship page (Wiki & Poster). 4. Science Communication
We have taught high school students what synthetic biology is. For more info, please refer to our Education page (Wiki & Poster). 5. Excellence in Another Area
We have created a concept art work to help many people get inspiration for our projects and synthetic biology.