Contribution from our Team
HKUST 2022 Team has made many contributions for iGEM this year.
The contributions we have made can be summarized as follows.
Part Contribution
| Contribution | Link |
|---|---|
| Characterize the activation threshold of oxySp (BBa_K4225001) |
Experiment - Circuit Design |
| Characterize the activation threshold of katGp (BBa_K4225004) |
Experiment - Circuit Design |
| Create 2 modulable peroxide sensors (BBa_K4225003 and BBa_K4225006) |
Experiment - Circuit Design |
| First team to characterize a shielding sequence for LVA tag that can be removed with TEV protease (BBa_K4225019) |
Experiment - Circuit Design |
Additional Contribution
| Contribution | Link |
|---|---|
| Characterisation of OxySp and KatGp | Circuit Design |
| Modulable Enzyme-Coupled H2O2 sensor | Circuit Design |
| Detailed guideline for ninhydrin optimisation | Hardware |
| Template for cell-free biosensors | Prototype |
| Model and simulate of the growth of C. Freundii to correlate it with the production of bioamine |
Modelling |
| Partnership with Science Museum for future SynBio education | Reach |
Characterization of oxySp and katGp
Figure 1.1 Fluorescence of GFP v/s [H2O2]
Figure 1.2 Fluorescence of RFP v/s [H2O2]
Figure 1.3 Fold Change of Normalized Fluorescence v/s [H2O2]
Figure 1.1, 1.2 and 1.3 shows the characterization of our composite parts, oxySp-GFP-Pc-OxyR(BBa_K4225003) and katGp-RFP-Pc-OxyR(BBa_K4225006) that contains our basic parts, oxySp(BBa_K4225001) and katGp(BBa_K4225004). From Figure 1.1 and 1.2, we observed that our composite parts have higher fluorescence than their positive and negative control respectively. This shows that our composite part works, and the coupling of oxyR and oxySp or katGp is required to produce a high fluorescence output.
In addition, we can see from figure 1.3, that oxySp has an activation threshold at around 0 - 40 μM [H2O2], which is higher than katGp which has an activation threshold at around 40-200μM.
Modulable Enzyme-coupled H2O2 Sensor
In the prototype of Fisherly, we specifically developed a highly modulable bioamine detector that informs the quality of fish through distinguishable colorimetric outputs. Notably, not limiting to the spoilage detection, we found that the signal conversion module conducted by rat diamine oxidase (rDAO) is exceptionally adaptable to various sensor targets, simply by replacing the transducer enzyme with other enzymes that feature the production of hydrogen peroxide from the target molecules. H2O2 is regarded as a suitable candidate to act as an intermediate signal for several reasons. First, H2O2 is a pivotal metabolite and byproduct of a significant amount of enzymatic reactions, which allow the linkages between H2O2-responsive circuits and many metabolites. Characterized by Peroxihub, 1788 enzymatic reactions to date exhibit good specificity and applicability of them as metabolic transducers, including sarcosine oxidase, choline oxidase, and l-lactate oxidase whose substrates have been identified as effective disease biomarkers and also of great interest in other fields[1]. Moreover, in contrast to other metabolites like amino acids or cofactors like NAD and Coenzyme A, H2O2 is not involved in the reservoir of cell-free synthesis, namely the buffer supplements, which possess limited interference with the biosensor. Last but not least, H2O2-responsive transcription factors and corresponding promoters have been identified, providing considerable space for exploring and optimizing an H2O2- response system.
However, this diversified corresponding promoter library has yet a long way to go in order to achieve a ready-to-use toolbox for biosensing. Thus, to enrich this promoter library and enhance its utility, we investigated a transcription factor named OxyR, the master regulator of oxidative stress in E. coli, and set out to research different OxyR-inducible promoters, with oxySp and katGp promoters chosen as the two main candidates in our project. As indicated by the work of Jacob R. Rubens et.al., oxySp promoter has a significantly lower activation threshold than katGp promoter, which inspired our preliminary design of a distinguishable dual-output biosensor for warning the spoilage of food. Through our extensive experiments and modeling, we successfully characterized and verified the behaviors of these two promoters in a total-fluorescence manner, which possesses more practical meaning than the FACS-driven results in the aforementioned paper since flow cytometer has exceptionally high sensitivity towards light.
Considering multiple factors such as social perception and working efficiency, we decided on BL21 cell lysate based cell-free system as the stage of our circuit implementation. The cell-free synthetic system has drawn much attention as an efficacious tool to harness and expand the capabilities of natural biological components in various applications, such as the comprehension of fundamental metabolic pathways, implementation of genetic circuitries, and so forth. It’s well-symbolized by the direct accessibility of inner working machinery and minimal interference of endogenous genetic background, which signifies its predictably far-reaching employment, essentially in the biosensing tract. The prominent readiness and freedom of control design relative to intact live cells are sparking diverse biosensor designs catering to the demand for convenient quantification of a broad spectrum of analytes[2]. Through months of work, we dedicated ourselves to establishing the best-optimized reaction environment in order to harbor our desired circuit by manipulating the vital components in master mix and cell extracts. We also developed a master mix optimization model coupled with our standardized cell extract preparation protocols to boost the test-cycle progression of future iGEM teams. By the utilization of an optimized cell free system, we believe our continuous work would contribute to more efficient characterization workflows, and ultimately the construction of a H2O2-inducible promoter toolbox suitable for a wide-ranging metabolite detection which would have profound applicational significance in different industries.
Detailed guideline for ninhydrin optimisation
In order to characterise the sample extraction efficiency of our biosensor prototype, ninhydrin was used to react with bioamines. This produces Ruhemann’s purple that can be measured at 570 nm. After learning through research that the optimal conditions for ninhydrin can vary depending on the sample being tested, we experimented different settings and subsequently designed a ninhydrin assay protocol specific to bioamines. We tested five different factors that contribute to ninhydrin’s performance: pH buffer ratio, buffer type, ninhydrin concentration, pH, and heating temperature.
The final ninhydrin assay protocol designed after a series of optimisation processes were also used in the circuit design team’s experiment to characterise the functionality of rDAO. Since ninhydrin is a commonly used chemical to quantify amino acids, ammonia, and amines, or any traces of proteins, we believe that our detailed procedures for optimising the ninhydrin assay protocol will be a helpful tool for iGEM teams looking for a method to quantify chemicals or proteins of interest.
Template for cell-free biosensors
Cell-free system is a tool widely used to study biochemical reactions and their mechanisms. Considering the characteristic of cell-free system, which is the requirement of a rehydration step to revive the cellular functions halted by lyophilisation, we designed a prototype so that the cell-free biosensor can be placed at the lower cap and be rehydrated easily by unscrewing it to reveal the sample outlet. As the design of our product enables simple and easy rehydration, not to mention the ease of implementation achieved by benchmarking a widely used COVID-19 rapid antigen test kits, will ensure high user-friendliness and convenience. We are confident that our prototype will be a good reference for future hardware designers.
Modeling of Citrobacter freundii
We successfully model C.freundii growth using Generalized Logistic Growth Function with real life data. It includes various temperatures too. In the future, if any Hong Kong iGEMs teams need to work with C.freundii, they can refer to our model easily.
Contribution to Future Hong Kong iGEM Teams
Partnership with the Hong Kong Science Museum
Not only did we receive positive feedback from different Synthetic Biology workshops with high school and middle school students, but we were also approached with an opportunity to form a long-term partnership with the Hong Kong Science Museum, one of the most popular museums in Hong Kong with over 500 interactive exhibits.
As we were finishing up the second workshop session, Mr. Brian Ip, the Assistant Curator of the museum, walked over and expressed that he was impressed by how interactive and exciting our activities were for the young audience. With some biology background himself, we discussed in-depth our genetic circuit, what specific problems it solves, and some challenges we faced throughout the journey.
Mr. Ip then explained to us that the Science Museum is currently planning to dedicate a new section in the exhibition to Biobricks and Synthetic Biology, and they would like to consult us on the content and ways to deliver knowledge in this seemingly distant field to the general public, seeing how successful our workshops were. Although their project is still in the preparatory stage, we were still excited to hear about this new platform to educate the public, especially the younger generations.
With the influence and publicity that the Science Museum offers, we are happy to be the first local iGEM team to initiate a long-term collaboration with them in providing educational and entertaining Synthetic Biology content to the local community. We hope that this collaboration would serve as a stepping stone for other local iGEM teams to educate the public on synthetic biology through the Science Museum.
References
[1] Soudier, P., Duigou, T., Voyvodic, P. L., Zúñiga, A., Bazi-Kabbaj, K., Kushwaha, M., Bonnet, J., & Faulon, J.-L. (2022, January 1). PeroxiHUB: A modular cell-free biosensing platform using H2O2 as signal integrator. bioRxiv. Retrieved October 7, 2022, from https://www.biorxiv.org/content/10.1101/2022.03.16.484621v1.full
[2] Hodgman, C. E., & Jewett, M. C. (2011, September 17). Cell-free synthetic biology: Thinking outside the cell. Metabolic Engineering. Retrieved October 7, 2022, from
https://www.sciencedirect.com/science/article/pii/S1096717611000929?via%3Dihub
