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Iteration 1: Circuit Designing
The math modellers found that the AiiA degradation tag (dtag) could help produce a stronger oscillation, hence is incorporated into the circuit. AiiA then lives just long enough for one round of oscillation, and doesn’t degrade AHL signal when the signal is actually needed, in the start of the next round of oscillation.
Finally, the circuit was finalised as follows.
Iteration 2: Cell Cycle Arrest (CCA)
1. The RNA-RNA Docking showed a directly linear relationship between length of antisense mRNA and the spontaneity (given by the drop in Gibb’s free energy) of the steric blocking.
Fig: Sense-Antisense mRNA Steric Blocking was deemed feasible through a molecular docking simulation.
Fig: The longer the antisense mRNA, the more spontaneous the Steric Blocking is. Of course, the simulation invokes approximations and assumptions, which are detailed in the Wet Lab Engineering Cycle.
2. The Spectrophotometric Assay showed a clear oscillation (note the kink!) of the growth curve in IPTG induction cases, but not in the control, quite in line with the expectation. This was a first remarkable observation for us. For then, the graph raised some questions. Firstly, the OD at which oscillation (or what we expect to be so) was observed, was at the same saturation OD as for the control (IPTG) case. But, in the IPTG cases, the growth was expected to oscillate about a lower saturation OD than in the control.
While analysing the result we obtained, we identified that one of key drawbacks of the experimental design is that, there MAY be manual error creeping in as for every reading, we take the culture off incubation, measure the OD, and keep a manual record of time all while. We switched to microplate reader for the first time.
The most probable take away from the Microplate Reader Assay is that, IPTG alone cannot prominently induce an oscillatory or stunted growth curve for the cells with our PCM construct. But, IPTG+dry tetracycline and IPTG+AHL could induce a fluctuation from the control curve. In fact, we could see a clear oscillation in the growth curve. This evidences our engineererd plasmid is working.
Analyzing the observation, we concluded that our tetR protein may be somewhat constitutively bound to the tetO region before the pTet promoter in the first transcription unit of our PCM construct and so only a very strong induction condition could cause the fluctuation in growth curve viz a viz the controls. A replicate experiment is underway, to confirm the results.
Iteration 3: Circuit Designing: the Linalool Production Module (LPM)
As a part of our human practices, we had attended talks with several synthetic biologists across the globe. Before starting our wet lab work, we wanted solid verification from them. After several brainstorming sessions we came up with certain limitations of our design to produce Linalool. According to them, the MEV pathway can be successfully functioned if the chassis is pre-engineered to bear the stress of such a long enzymatic reactive pathway, alternatively we could order engineered or mutated strains to incorporate the MEV pathway. But due to time constraints and safety purposes, we discarded the solution of ordering a new strain for our experiments. Another path showed up when we were advised to manipulate the Methylerythritol pathway (MEP pathway). The MEP pathway is an innate metabolic pathway in E.coli that also produces isoprene for bacterial growth. Interestingly, the MEV and MEP pathway shares common intermediate substrates (DMAPP and IPP) among them, DMAPP being the former precursor of linalool. As it is clear that we could rather channelise the MEP pathway by just inserting GPPS and LIS into the bacteria to produce Linalool to reduce metabolic burden of the cloned organism.
Iteration 4: Cloning and Expression
The HiFi Assembly Protocol was optimized for a successful engineering of plasmid PCM. The knowledge helped us calculate optimized HiFi assembly reaction mixtures for our future experiments.
Iteration 5: Dry Lab: Initial Model for quorum sensing circuitI
We observed the oscillation in cell population in the presence of the quorum sensing circuit, thus verifying the presence of the negative feedback loop in it. However, we also learned that our population equation could not relate death term, r0ct, with the accumulation of secondary metabolites and the reduction in substrate concentration as both r0 and c are constants and independent of the cell concentration as well as substrate concentration. So, because this model cannot directly relate the accumulation of secondary metabolites and decrease in substrate concentration with the onset of the death phase in the population, we had to look upon developing an even better model.
Iteration 6: Dry Lab: Final Model for quorum sensing circuit
We learned that our new growth model could very efficiently relate the death term of the population equation with the accumulation of toxic secondary metabolites and the reduction in substrate concentration. We also observed that our quorum sensing model is able to give us the desired output of controlling the bacterial population at a threshold level quite below the carrying capacity of the original bacterial population without the quorum sensing circuit, and thereby, the population life/media potential of the culture is getting increased due to less accumulation of secondary metabolites and slower rate of substrate consumption, making the death phase of the population arrive at a much later stage than the original population. Hence, our justification of choosing the later quorum sensing model to determine the bacterial population dynamics is accordingly verified.
Iteration 7: Choosing Best Length of the Antisense
Optimisation of PCR Protocol for Small Parts:
The following modifications were incorporated:
1. The PCR reaction mixture was kept on ice. The PCR machine was allowed to preheat to 98°C, and then the PCR tubes were promptly put into the thermocycler. This reduced off-site binding.
2. Increasing Template (PCM extracted) concentration. That reduced primer dimers.
3. A control was kept with no template. The idea is that the primers, unreacted, would come down the gel electrophoresis and create primer dimers to help distinguish them in the other wells.
And excellent bright desired bands were observed in the gel.
The Microplate Reader Assay did show some excellent oscillatory growth curve upon induction, which was not there in the control case. For both 150 and 393 bp, the induction and fluctuations (oscillations) are visible. This indicates a success for our experiment.
We could not conclude if the assay of 150 or 393 bp showed a better oscillation, as both showed a similarly good result. We are yet to troubleshoot the 277 bp case.
Design
Iteration 1: Circuit Designing
Parallel to the linalool production module (LPM), we wanted an auto-regulated cell cycle regulation by another co-transformed plasmid. This plasmid will let each bacterium sense the cell density around itself. So that, when the bacterial density reaches an optimal threshold, a signal will trigger a feedback loop mechanism- which will cause cell cycle ‘arrest’. We needed two things.
Firstly, we needed a signalling molecule- which can be produced in proportion to the cell density outside- inside each bacterium itself. With the help of literature study, we came across the AHL molecule,
We identified the AHL to be utilised into the LuxI-LuxR Quorum Sensing Machinery of Vibrio fischeri1- which fulfilled our second need of the feedback loop, as well. All we needed to do was to transform this system into E. coli strain BL21.
Iteration 2: Cell Cycle Arrest (CCA)
Multiple strategies to trigger cell cycle arrest were discussed and tallied against our criteria of arrest- reversibility, speed, and non-toxicity to cells. A cell cycle death was hence ruled out, due to the rapid build up of toxic wastes that would make our (limited) food medium unusable.3 Hence, we went for a ‘softer’ strategy- simple, steric blocking of a key protein of cell cycle at its mRNA stage itself. Unlike DICER, etc. this strategy does NOT cleave the mRNA- it just prevents its translation. The following questions were raised: Which gene to silence? We discussed an array of proteins involved in the replication fork of bacterial division4. Ultimately, we narrowed down to two- DnaB (a helicase) vs DnaA (initiator of cell replication). The knockout of the DnaB molecule was reportedly irreversible 5, pushing us to go for DnaA protein. Further, the DnaA molecule was BLASTed by our bio modellers and found to be a largely conserved protein- allowing us to silence the protein across a variety of strains of E. coli- including our expression strain BL21. Which part of the DnaA’s mRNA should be sterically blocked? It was a million-dollar question. It was reported for a similarly long gene that about 400 bp long gene of the initial 5’ region (wrt coding strand), and also covering the Shine Dalgarno sequence upstream was sterically blocked and the gene’s expression could be silenced. 6 BLASTing, we could not find any information for the Shine Dalgarno sequence of this gene dnaA. How long should the antisense mRNA be? Antisense Oligonuleotides were ruled on reported accounts of wide off site targeting despite their short size.6 A longer mRNA would mean more chances of effective blocking, but also more chances of secondary loop formation. We had to do our odds. The above paper6 motivated us into experimenting forward with the first 400 bp case. We decided to silence the first 400 bp of the dnaA gene. (dnaA is the gene, DnaA is the protein). We designed a DNA sequence, under a pLux promoter, which coded for the antisense mRNA against the first 400 bp of the dnaA gene. It would sterically block its sense mRNA and hence stop dnaA at translation. Needless to say, no ribosome binding site was given. As we anyway don’t want its protein to be expressed.
Iteration 3: Circuit Designing: the Linalool Production Module (LPM)
After thorough research for finding a biodegradable, eco-friendly, harmless overall green measure to manufacture our innovative cosmetic approach, we have found the most appropriate molecule fulfilling our desired properties in Linalool, a monoterpenoid mostly found in plants as a fragrant metabolite, moreover having antifungal and antimicrobial properties, a perfect combination for total foot care. Delving deep, we found that the plant enzymatic pathway known as Mevalonate Pathway (MEV Pathway) produces the Linalool where the direct enzyme Linalool synthase converts Geraniol diphosphate to Linalool. The MEV pathway is extensively researched and manipulated for different monoterpene production. We are grateful to the iGEM KEYSTONE China Team for their improved part for MEV pathway plasmid. Literature shows successful production of Linalool by incorporating the whole MEV pathways in bacteria. So we moved on building our model based on the design.
Iteration 4: Cloning and Expression
We decided to go with the proprietary Hi Fi assembly offered by New England Biolabs. It is scarless, remarkably accurate and the we could leverage the experience of ex iGEMers from IISER-K and our advisors in this method. We identified that many of the Kit 2024 parts- had pSB13C backbone, with inserts at the same position. The backbone was chosen to be a pSB13C one, and the pair of linearization primers were cleverly designed so that they could linearise the backbones of most of those kit parts having pSB13C.
Iteration 5: Dry Lab: Initial Model for quorum sensing circuitI
We wanted to determine the bacterial population dynamics using a set of deterministic ODEs. We chose all the necessary entities whose concentrations would be important to us, namely LuxI, LuxR, AHL, AiiA, A2R2 (AHL-LuxR complex), tetR, CCA (Antisense mRNA), N (Population concentration), S (Substrate concentration).
Iteration 6: Dry Lab: Final Model for quorum sensing circuit
We proceeded to develop a population equation which could more efficiently relate the accumulation of secondary metabolites and decrease in substrate concentration with the onset of the death phase in the bacterial population. For that, we though of introducing an extra term to the logistic growth equation which would govern the onset of the death phase in the bacterial population.
Iteration 7: Choosing Best Length of the Antisense
Though we did incorporate a Cell Cycle Arrest (CCA) gene of length 400 bp length, we realized later that an empirical attempt at determining an even better Cell Cycle Arrest genes can be made.
We stuck to DnaA reversible steric blocking, but now we decided to alter the length of the CCA gene, and hence the antisense mRNA. Ordering the replicates of the same PCM plasmid with different lengths of CCA was discarded in favour of a simple experiment. We wanted to put CCA genes of various lengths, such that they are expected to produce antisense mRNA against the first 150 bp, 278 bp, and 393 bp of the DnaA gene, starting from its AUG - each under an inducible promoter.
The part M20 of Kit Plate 1 of the 2024 Distribution kit had an IPTG inducible promoter pTac and LacO operator, we noticed after going through the Airtable. It also had a His operon terminator. So, we decided to leverage its backbone - we shall insert antisense of a certain length between this pTac + His operon terminator. We shall repeat this HiFi assembly for three such lengths of the CCA sequence.
Build
Iteration 1: Circuit Designing
Once the circuit was built, the question of reversibility of Cell Cycle Arrest posed before us. Consider a situation wherein, the AHL concentration has been now enough to trigger cell cycle arrest, and so has happened. The signal is anyway getting produced, as per our circuit planned so far. But now, the signal is no more needed! How to decrease this signal? Moreover, once the AHL signal is reduced, and as the cell density falls below the aforementioned threshold due to inevitable cell death, a reverse mechanism should restart Cell Cycle- which would then trigger another round of cell cycle arrest, and so on. We, thus, expect an oscillatory growth curve for the bacteria, oscillating around the logarithmic growth phase. How to have this reversibility? We used the tetR negative regulation of the Quorum Sensing. We also decided to integrate a gene coding for the AiiA molecule, which is reported 2 to degrade the signal AHL. When cell cycle arrest occurs, tetR and AiiA both are produced. tetR represses pTetpromoter and hence downregulates AHL production, while AiiA degrades any AHL persistent in the environment at the moment.
Iteration 2: Cell Cycle Arrest (CCA)
The 3rd fragment of our Population Control Module (PCM) circuit contained this Cell Cycle Arrest (CCA) sequence. It was ordered from our sponsor Twist BioScience and then, alongwith the other fragments, HiFi assembled into a pSB1C3 backbone. The assembled plasmids were then transformed into bacteria.
Iteration 3: Circuit Designing: the Linalool Production Module (LPM)
We had put a little modification to the already built plasmid of the KEYSTONE Team according to our need i.e. to produce Linalool. We proposed to put GPPS and LIS gene by knocking out the idi gene from their design. The plan is to put DMAPP as a substrate of GPPS to produce the precursor of LIS (Linalool Synthase). For cloning the desired functional plasmid we ordered the pBbA5c-MevT (CO)-T1-MBIS(CO, ispA) . We have planned to knock out the ispA gene and insert GPPS and LIS in it. Hence we have ordered the mentioned plasmid from Addgene. (Plasmid ordered from addgene: https://www.addgene.org/35152/sequences/)
Iteration 4: Cloning and Expression
We decided to keep blunt overhangs in each fragment, so that they are Hi Fi compatible. The inserts of quorum sensing circuit were ordered in three parts from our sponsors- Twist Biosciences. The backbones were linearized out from Kit parts, as said.
Iteration 5: Dry Lab: Initial Model for quorum sensing circuitI
We built the ODE system for the quorum sensing model to determine the bacterial population dynamics with time. The population equation in the presence of the quorum sensing circuit was formulated by modifying the logistic growth equation as such :- \[ dN/dt = r0*((1-μ[CCA])-ct/(1+(n*(CAA))^n))N(1-N/K)\] Here, r0 is the cell growth term and r0ct is the cell death term due to reduction in substrate concentration and accumulation of secondary metabolites, which eventually brings about the death phase in the population. The \(r0*(1-μ[CCA])\) term was incorporated to denote the reduction in the population growth rate due to the cell cycle arrest antisense mRNA (CCA). The \(r0*ct/(1+(n*(CAA))^n)\) term was incorporated to denote the increase in the population life of the bacteria due to the population being controlled at a lower threshold.
Iteration 6: Dry Lab: Final Model for quorum sensing circuit
We formulated the new population equation of the quorum sensing model, from the logistic growth model as :- \[dN/dt= r0*N/(1+(m*[CAA])^r3)-r0*(N^2)/K - aNt^4/((t^4+b^4)*(1+(c*S)^n))\] Here, the first term is the growth term, being repressed proportionately by the concentration of the antisense mRNA (CCA). The second term is the natural death term, as usual. The third term is the death term due to reduction in substrate concentration and the accumulation of secondary metabolites, which is responsible for bringing about the death phase in the bacterial population. It is multiplied to N as well as has a Hill term with respect to time to denote that the accumulation of secondary metabolites increases with increase with the cell population as peaks after a certain time. The term is also inversely proportional to the substrate concentration to indicate that the reduction in the amount of substrate amplifies the death phase of the population.
Iteration 7: Choosing Best Length of the Antisense
Build: CCA of three different lengths - viz, 150 bp, 277 bp, and 393 bp - were amplified out, using primers, which were overlapping with the linearized M20 Backbone, from the main construct PCM (already having the maximum 400 bp arbitrary CCA sequence). And then one by one, they were HiFi assembled into three different plasmids. Let them be code named M20+CCA sequences of lengths 150 bp, 277 bp, and 393 bp, respectively.
During the amplification, the initial attempts at amplifying such small parts (100-400 bp) posed a challenge to us. We were initially unsuccessful in amplifying out CCA sequences of such short lengths. In the gel electrophoresis data, huge off-site binding and primer dimers were saddening us. By optimisation of protocol for PCR, we could successfully amplify them. Then on, the experiment proceeded smoothly.
Test
Iteration 1: Circuit Designing
Our math modellers ran an in-silico kinetic study on the above circuit.
Iteration 2: Cell Cycle Arrest (CCA)
The testing of its efficacy was done through: RNA-RNA Docking Wet Lab: Once the Population Control Module (PCM) was constructed through Hifi Assembly, two assays were done to check the pattern of growth curve- whether an oscillatory growth is at all visible? a spectrophotometric growth curve analysis, with IPTG induction. Three identical secondary cultures- one control, one with IPTG induction at 0th time point, and another with IPTG induction after 2 hours of setting the secondary culture, were given, for the E. coli strain BL21 cells transformed with PCM/Main Construct Hifi Assembled plasmid. Microplate Reader Assay: A 96 well microplate was preplanned to contain transformed E. coli BL21 cells with the PCM, and then IPTG, IPTG+AHL, IPTG+Anhydrous Tetracycline in various concentrations in various wells, and in some wells, we had no inducer (as control).
Iteration 3: Circuit Designing: the Linalool Production Module (LPM)
Due to time constraint, we could not perform the experiment regarding our newer approach to produce Linalool before our wiki submission, however, we have designed required primers in silico to linearize M20 plasmid from iGEM kit, amplify the gene insert GPPS and LIS and HiFi assembly the inserts with the plasmid backbone. The detailed primers and cloned in silico plasmids are documented in the Material part of our website.
Iteration 4: Cloning and Expression
The HiFi Assembly was successfully done. Colony PCRs revealed the same. The plasmids were extracted and successfully transformed into DH5-alpha E. coli to increase copies. The plasmids extracted from their primary culture was then transformed into competent E. coli strain BL21 expression host. The construct has also been sent for a sequencing. We used this construct as the template for GFP characterization experiments and for the experiment to have an empirical idea on the best length of antisense mRNA. This is a successful engineering.
Iteration 5: Dry Lab: Initial Model for quorum sensing circuitI
We ran a simulation of the model to determine the population dynamics of the bacteria with time. The N vs t plot is given below :-
Iteration 6: Dry Lab: Final Model for quorum sensing circuit
We ran a simulation of the model to determine the population dynamics of the bacteria with time. The plots are given below:
The plots without the quorum sensing circuits are also given below:
Iteration 7: Choosing Best Length of the Antisense
That the three assemblies were successful was confirmed through Colony PCRs and the plasmids were sent for sequencing. The plasmids were then transformed into DH5-alpha E. coli, extracted, and transformed into expression hosts E. coli strain BL21. Successful colonies were observed on chloramphenicol marker plates for 150 and 393 bp but NOT for 277 bp.
A similar microplate reader assay with induction by IPTG in various concentrations was done for 150 and 393 bp. And controls were given with no inducer.
