Team:NTU-Singapore/Project/Proposal

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Our Solution


Contents


In the previous section, we have identified the gene sequences we will be working with for our prototype construction.

In this research proposal, we will detail the methods by which we plan to achieve the construction, testing and characterization of our devices & parts.

Aim

We wish to design constructs that can eventually be deployed in modified T-helper cells, that will :

  1. detect plaque in vessels using a nitric oxide sensitive promoter.
  2. release cholesteryl ester degrading enzymes to break down the lipid core in plaque.
  3. identify and locate the plaque site in vivo with a novel infrared reporter protein.
  4. dilate the vessel to provide immediate relief using nitric oxide synthase.


Due to time & equipment shortage during the iGEM period, we will only demonstrate the proof-of-concept system using the E.Coli K12 strain.

We will concentrate our efforts on making our parts individually and in various combinations into standard Biobrick parts so that they can be readily used in future.


Research Methodology

In our project pLaqUe Out!, we will be dealing with 4 devices to arrive at a complete system.

The 4 devices are :

  1. Sense device with nitric oxide sensing promoter (pNO)
  2. Degradation device for cholesteryl esterase (CHE) production
  3. Imagine device for infrared-fluorescent protein (IFP) production
  4. Dilation device for nitric oxide synthase (NOS) production


Sense device

'pNO is NorR-regulated sigma-54 promoter. NorR is a transcription factor which is highly responsive to the presence of nitric oxide. Therefore, we would be regulating the expression of a gene downstream of our pNO by varying the input of nitric oxide.


In order to realize this sub-system, we will have our gene for pNO directly synthesized from GeneART.

We will characterize the pNO by the expression of downstream green-fluorescent protein (GFP). The protocols for this are available on the OpenWetWare (OWW) website and we will optimize them for our use. We will have sodium nitroprusside (SNP) as the source of nitric oxide, and we will vary the concentrations of SNP accordingly to obtain our desired input values.

Thus, we will be able to characterize the activity of our pNO via the GFP output in fluorescence time course (fluorescence versus time), absorbance time course (absorbance versus time) and fluorescence/OD600 versus time.


Degradation device

This sub-system will secrete cholesteryl esterase (CHE) which is able to catalyze the hydration reactions of cholesteryl esters into free cholesterol and fatty acids. The degradation of cholesteryl esters through these reactions will lead to the size reduction of the atherolsclerotic plaque.

This gene for CHE, originally obtained from Pseudomonas aeruginosa, will be directly synthesized from GeneART.

Since the ultimate objective of this sub-system is to characterize the functionality and activity of CHE, we will induce the expression of CHE via constitutive promoters such as Part BBa_J23101 and Part BBa_J23119 from the Registry.

With this construct, we can readily perform functionality test with the Amplex(R) Red Cholesterol Assay Kit from Invitrogen to quantitatively analyse the enzyme activity of CHE. Nevertheless, SDS-PAGE will also be carried out to confirm the expression of the cholesteryl esterase of our construct.


Imaging device

This sub-system will control the expression of infrared-fluorescent protein (IFP) via a constitutive promoter. IFP however would not be stable in the absence of biliverdin IXα (BV). Hence, we will have our construct incorporated with heme-oxygenase 1 (HO-1) which is responsible in generating BV from heme group.

In order to realize this sub-system, we will have our gene for infrared-fluorescent protein directly synthesized from GeneART, and subsequently ligated to HO-1 which is taken from the Registry (Part BBa_I15008).


We propose to have constitutive promoters such as Part BBa_J23101 and Part BBa_J23119 to induce the co-expression of HO-1 and IFP. The gene sequence for IFP is in fact from Tsien’s Lab, University of California, San Diego (UCSD). We hope to have their plasmid with HO-1 and IFP1.4 incorporated sent to us so that we can induce the expression of IFP1.4 and thus using their infrared fluorescence signal as a control to gauge the infrared fluorescence signal for our construct.


We are proposing to have an experimental setup to detect the infrared fluorescence signal. Because the maximal excitation wavelength for IFP is at 684 nm, we intend to use a 660 nm laser in our lab to shine onto the cell culture for excitation.

An optical fibre connected to a spectrometer will then detect the infrared signal (maximal emission wavelength) and we will be able to see the emission spectrum on the spectrograph. SDS-PAGE will also be carried out to confirm the expression of both proteins; HO-1 and IFP, of our construct.


Dilation device

Our team has designed this construct for the sake of completing the logical funtion of the overall system. However, due to the time limitation, this proposed construct will not be pursued.


Modelling Approach

Part of our predictions come from the strength of our models, which we mathematically deduce in the form of ordinary differential equations. The ODEs will relate the concentration of mRNA, protein and GFP output of the gene sequence of interest w.r.t time. We will use known and/or empirical constants such as maximum translation rate, maximum transcription rate, dissociation constants etc to assume for maximum efficiency case.

These equations for each construct are then re-constructed as a Simulink subsystem, which in turn are displayed as blackboxes in the Simulink version of the final system.


The modelling process is almost entirely theoretical, except for abovementioned constants which are literature-derived.

So firstly predicted outputs from the model can actually help us to envision the scale at which the system works. This is important to verify if the system can even ideally be used in the application that we want.

Furthermore, by identifying larger deviations in output of the actual system compared to predicted model, the model can also help as a “debugger”.

The models can also help us to enhance the system by identifying bottlenecks; identifying the assumptions made in simplifying calculations can indirectly point us to the potential sources of error in experimental verification.


Conclusion

All in all, we hope to have a fruitful time in working towards meeting our research goals, and we look forward to presenting our results at the Jamboree.


Literature / References

Please proceed here to view our full list of references.



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