Overview
Our project is divided into three main parts : Eat, Shoot, and Leave. To construct our parts, we used sequences synthesised by IDT and TwistBioscience which allowed us to obtain sequences codon-optimized for our host strain. The sequences are assembled in the desired plasmids with type IIS restriction enzyme.
EAT-SHOOT
Our project emphasized on developing a tunable and dose-dependent biosensor. As a proof-of-concept, we utilized naringenin dose responsive promotor that controls the expression of NarX, a histidine kinase homodimer that phosphorylates NarL when nitrate is present. When NarL is phosphorylated, it will activate PNarL that drive the expression of a red fluorescence protein, mKATE. We introduced NarX mutant in another compatible plasmid with a constitutive promotor. The mutant is able to interact with wild type NarX but doesn’t phosphorylate NarL (Cavicchioli et al., 1995). Thus, acting as a quencher. We designed our biosensor this way to control the NarL activity and mKATE expression.
All of the experiments were done in E. coli K12 MG1665 as E. coli is easier to manipulate and a common lab strain. However, the final application will be done in Lactobacillus spp. which is a probiotic and part of the gut microbiome. In application, naringenin promotor can be replaced by colorectal cancer biomarker-driven promotors in an AND gate system. While mKATE will be replaced by a therapeutic protein allowing a targeted therapy delivery. Some of the constructs have been cloned into the E. coli K12 MG1665 but further fluorescence testing is needed to generate data for modelling. Due to the limited data of mKATE readout, our dry-lab team utilized the raw data of De Paepe et al. (2018) to test our model.
Our modeling focus on determining the threshold of naringenin to produce high concentrations of wildtype NarX to surpass the quencher, NarX mutant. In practice, it gives data of biomarker concentrations that will activate the therapeutic proteins. It will also provide predictions to guide experiments to tune the biosensor. In a broader perspective, the model and biosensor circuit can help other researchers develop a biosensor for various diseases.
LEAVE
Our project also focused on the biocontainment of the biosensor. For this purpose, we utilized the type II toxin-antitoxin system, CcdA/CcdB, which is toxic for bacteria but not for humans. In the body, at 37 °C, the antitoxin is expressed and able to neutralize the toxin. However, it is inactivated outside of the body at a lower temperature. To control the expression, we tested three different temperature-dependent riboswitches: Hsp17, RpoH, and PrfA that naturally control the expression of native heat shock proteins in various bacteria (Johansson et al., 2002; Kortmann et al., 2011; Morita et al., 1999).
In our design, CcdB is constitutively expressed while CcdA will be regulated by the riboswitches. Inside the body (37°C), CcdA is expressed. However, the riboswitch will form a secondary hairpin structure at lower temperatures (<37°C). As a result, the RBS is hidden and CcdA is not translated. Thus, the toxin CcdB takes over and the cell is killed. Both constructs are tested in parallel in separate pLO plasmids.
For the proof of concept, both CcdB and CcdA are linked to GFP to see their expressions. The riboswitches that control the expression of CcdA are tested in different temperatures ranging from 20-42°C. From all of our constructs with different riboswitches, Hsp17 showed the most promising results in deactivating the CcdA translation and could be implemented in the further development of the project.
On the other hand, CcdB is controlled by a tetracycline-inducible promoter and a Lac operon. Two inducers, anhydrotetracycline and IPTG, are needed to activate the downstream translation. As a third control element, a stopcodon region within the CcdB gene, flanked by restriction enzyme sites (SalI), is implemented to minimalize leaky expression of the toxin thus having an effect on the viability of the bacteria during the cloning phase. After cloning, the stopcodon region is deleted to complete the design. Fluorescence and OD measurements were observed with different concentrations and combinations of inducers. From these measurements, there can be assumed that the toxin is translated upon induction and possibly also kills the bacteria.
Please take a look at the Results and Engineering page for more information.
References
- Cavicchioli, R., Schröder, I., Schröder, S., Constanti, M., & Gunsalus, R. P. (1995). The NarX and NarQ Sensor-Transmitter Proteins of Escherichia coli Each Require Two Conserved Histidines for Nitrate-Dependent Signal Transduction to NarL. JOURNAL OF BACTERIOLOGY, 177(9), 2416–2424.
- De Paepe, B., Maertens, J., Vanholme, B., & de Mey, M. (2018). Modularization and Response Curve Engineering of a Naringenin-Responsive Transcriptional Biosensor. ACS Synthetic Biology, 7(5), 1303–1314. https://doi.org/10.1021/ACSSYNBIO.7B00419/ASSET/IMAGES/MEDIUM/SB-2017-00419D_M005.GIF
- Johansson, J., Mandin, P., Renzoni, A., Chiaruttini, C., Springer, M., & Cossart, P. (2002). An RNA thermosensor controls expression of virulence genes in Listeria monocytogenes. Cell, 110(5), 551–561. https://doi.org/10.1016/S0092-8674(02)00905-4
- Kortmann, J., Sczodrok, S., Rinnenthal, J., Schwalbe, H., & Narberhaus, F. (2011). Translation on demand by a simple RNA-based thermosensor. Nucleic Acids Research, 39(7), 2855. https://doi.org/10.1093/NAR/GKQ1252
- Morita, M. T., Tanaka, Y., Kodama, T. S., Kyogoku, Y., Yanagi, H., & Yura, T. (1999). Translational induction of heat shock transcription factor σ32: evidence for a built-in RNA thermosensor. Genes & Development, 13(6), 655. https://doi.org/10.1101/GAD.13.6.655