Difference between revisions of "Team:Utrecht/Design"

In order to achieve our goal of creating a biosensor for the detection of pharmaceutical pollution, a structured approach to our design process was necessary. Determining the requirements for such a biosensor to be functional, and finding the right opportunities and systems to implement these requirements in, resulted in our choice for a three-step approach. On this page, you will find explanations of these three different components that constitute our project, as well as the reasoning behind our choice for a chemotaxis-based biosensor.

Bioluminescence Resonance Energy Transfer Pairs

To measure the concentration of ligand present, the activity of wild type and modified Tar receptors have to be measured. Therefore, we designed a Bioluminescence Resonance Energy Transfer (BRET) based sensor, inspired by a previously made chemotaxis BRET-pair (Cui et al. 2014). BRET is a technique where photons produced by a luciferase are used to excite a fluorophore. We opted to use Renilla luciferase (RLuc) since it produces photons that can excite eYFP. In addition, the substrate for this protein, coelenterazine, is permeable to the cell which makes it perfect for E. coli based bioassays. For energy transfer to occur, the RLuc and eYFP proteins must be less than 10 nm apart. Thus by measuring the ratio of light emitted by the two molecules, we can detect whether they are physically close, as can be seen in figure 2.

By fusing the RLuc to CheZ and eYFP to CheY, the bioluminescence can be used as a proxy to demonstrate whether the chemotaxis proteins interact (Figure 3). When no ligand is bound to the Tar receptor, CheA is active and phosphorylates CheY. Because of this, the phosphorylated eYFP::CheY can interact with CheZ::Rluc, bringing RLuc and eYFP in close proximity of each other. This can be measured as a BRET signal when the RLuc substrate is added. Upon binding of a ligand to the Tar receptor, CheA becomes inactivated, ultimately leading to a decrease of the BRET signal. Importantly, the signal can be readily measured by using an affordable bioluminescence assay.

Figure 1: The Chemotaxis Pathway of E. coli. A) The active pathway. B) The inactive pathway.

Figure 3: The implementation of the BRET-pair in the Chemotaxis pathway. A) the BRET-pair is able to get in close proximity when no ligand is bound to the receptor. B) Upon binding of ligand to the receptor, the pathway is inactivated. CheY and CheZ no longer bind, therefore YFP will not be excited by Luciferase.

Figure 2: BRET-pair activity. A) When CheZ and CheY do not interact, the distance between Luciferase and eYFP is too large for Luciferase to excite eYFP. As a consequence, only Luciferase emits light. B) Upon interaction of CheZ and CheY, Luciferase and eYFP are in close proximity. eYFP is excited by photons produced by luciferase, leading to luminescence of eYFP.

Methylation of the Tar receptor

Broader concentration measurements by methylation mimicking

Jos van der Vosse (TNO) suggested quantifiable measurements. Since we did not know the sensitivity of our light signal system at that time, we decided to implement an additional method, facilitating the measurement of set ranges of concentrations. This method is based on the methylation state of the Tar receptor, which influences its sensitivity to ligands.

In the unmethylated state, the receptor transduces the ligand binding signal to an inactivated pathway (Figure 4A and 4B). Upon receptor methylation, the conformational change required to transduce the inactivation signal, is energetically less favorable, resulting in lower occurrence. Therefore, when the same amount of ligand is present, the level of pathway inactivation is lower than in the unmethylated receptor state. Since the Tar receptor has four acidic residues that can be methylated (Q295, E302, Q309, E491), there are in total sixteen different combinations of methylation states, each one resulting in a slightly different sensitivity (Figure 4C).

Application of methylation in our biosensor

The methylation of glutamine (Q) or glutamic acid (E) residues can be mimicked by mutating these residues to alanine (A) (Krembel et al. 2015). The different possible combinations of methylation mimicking alanine mutations yields a wide range of potential sensitivities, which we predicted with our computational ODE-model. As a proof of concept, we chose three different methylation states:

1. The wild type state, the unmethylated Tar receptor (QEQE, most sensitive);
2. A Tar receptor with one mimicked methylation site (QEAE, average sensitivity);
3. A Tar receptor with two mimicked methylation sites (QEAA, least sensitive).

The Tar receptor that we received from a collaboration with iGEM team Groningen was mutated using site-directed mutagenesis and expressed in E. coli strains UU1250 and VS181, which do not express any chemotaxis receptors. In addition, VS181 does not express the methyltransferases CheW and CheB, resulting in a fixed methylation state. The E. coli strains were kindly provided by Shuangyu Bi from the lab of V. Sourjik at the Max Planck Institute for Terrestrial Microbiology in Marburg.

Next, the sensitivity of E. coli for aspartate could be measured. This was achieved by addition of a range of aspartate concentrations and subsequent luminescence measurements by using the self-designed BRET-pair. Our model can be verified and corrected based on these measurements. BRET measurements were validated using a FRET-pair received from Marburg.

Figures will come soon