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<ul> | <ul> | ||
<li>Based on previous work done on quorum sensing: how strongly should LuxR and LuxI be expressed? <br> | <li>Based on previous work done on quorum sensing: how strongly should LuxR and LuxI be expressed? <br> | ||
− | <em>Quick answer:</em> Each 10 times stronger than the ones characterized <a href="https://2014.igem.org/Team:ETH_Zurich/expresults">here</a>.</li> | + | <em>Quick <a href="https://2017.igem.org/Team:ETH_Zurich/Model/Environment_Sensing/parameter_space#parameter_search">answer</a>:</em> Each 10 times stronger than the ones characterized <a href="https://2014.igem.org/Team:ETH_Zurich/expresults">here</a>.</li> |
<li>Similarly, what expression levels of LldP/LldR should be achieved in order to get enough sensitivity to differentiate tumor and non-tumor tissue?<br> | <li>Similarly, what expression levels of LldP/LldR should be achieved in order to get enough sensitivity to differentiate tumor and non-tumor tissue?<br> | ||
<em>Quick answer:</em> ...</li> | <em>Quick answer:</em> ...</li> |
Revision as of 13:49, 30 October 2017
Tumor Sensor Experiments
Introduction
We incorporated a module into our system that would allow our engineered bacteria to autonomously decide if they are in tumor tissue or not . This decision is taken upon AND-logic integration of two inputs: AHL and Lactate (Figure 1). Only if both these chemicals are present, the downstream modules are activated.
For details about our synthetic AND-gate promoter, visit the Tumor Sensor page.
Initial System Design
Before we started any designing, cloning or experimentation on the tumor sensor module, we sat together with our modellers to find key parameters relevant for design and experimentation.
KEY QUESTIONS
- Based on previous work done on quorum sensing: how strongly should LuxR and LuxI be expressed?
Quick answer: Each 10 times stronger than the ones characterized here. - Similarly, what expression levels of LldP/LldR should be achieved in order to get enough sensitivity to differentiate tumor and non-tumor tissue?
Quick answer: ... - At what density of the colony under experimental conditions should the quorum sensing system be activated?
Quick answer: At an OD of 0.005. This turned out to be problematic to assess experimentally.
Overview of the Experiments
To build and characterize an AND-gate that would allow to differentiate between healthy and tumor tissue, we ran a sequence of experiments:
- We transformed E. Coli with plasmids containing only the quorum sensing system. We let these colonies grow to different densities and evaluated their response.
- We evaluated the response of our AND-gate designs to varying amounts of lactate and AHL.
- Finally, we transformed E. Coli with plasmids containing the whole tumor sensor system and evaluated the how the colonies behave over time under conditions corresponding to healthy and tumorous tissue.
To read more about each of these experiments, click on the buttons below. For a detailed protocol describing each experiment, visit Protocols.
Quorum Sensing End-Point Characterization
OBJECTIVE
Determine the population density at which the quorum system gets activated and provide the modellers with data to infer aLuxI, the production rate of LuxI.
PROCEDURE
We transformed E. Coli with a regulator and an actuator plasmid, containing constitutive LuxR and Plux, sfGFP, mCherry and LuxI respectively (Figure 2).
Subsequently, we let these colonies grow to different final population densities. This was achieved by varying glucose concentrations in a defined medium. [1] Population density was assessed by measuring absorbance at 600 nm wavelength. Fluorescence emitted by sfGFP and mCherry served as a read-out of the level of activation. A detailed protocol is available in Protocols.
RESULTS
CONCLUSION
- We can modulate the density a bacterial population reaches in defined medium by varying the amount of glucose.
- The quorum sensing system shows a response to increasing population densities.
AND-gate without Quorum Sensing
OBJECTIVE
Determine expression levels of GFP production under the control of the AND-gate with different inducer concentrations. In this experiment we wanted to assess whether our designs would be capable to distinguish healthy and tumor tissue based on lactate and expected AHL concentrations.
PROCEDURE
Two plasmids required for the AND-gate were transformed into E. coli Top 10 (Figure 4). Cultures were grown in microtiter plates under combinations of 8 different AHL and 8 different lactate concentrations and measured after 5.5 hours. A detailed protocol is available in Protocols.
RESULTS
The different conditions cleary have an impact on expression levels of sfGFP under control of the AND-gate promoter. All three designs show increasing activation with increasing inducer concentration, even if the second inducer is not present. The highest fold-change for all designs however, is observed if both inducers are present in high amounts.
CONCLUSION
- Leakiness of the synthetic promoter increases with increasing amounts of either inducer in the absence of the other.
- Increasing AHL amounts have a greater influence on the leakiness in absence of lactate.
- All three AND-gates exhibit highest inductions in presence of both inducers.
- At lactate levels found in healthy tissue and low AHL concentrations, all designs are only weakly activated.
- Design B performed best at distinguishing “healthy tissue lactate”, low AHL vs. “tumor tissue lactate”, high AHL. Design C, on the other hand, performed worst.
AND-gate with Quorum Sensing
OBJECTIVE
Verify the findings of the AND-gate characterization without quorum sensing with strains of E. Coli that contain additionally to the AND-gate also LuxI, the enzyme that catalzyes AHL production.
PROCEDURE
Two plasmids required for the AND-gate were transformed into E. coli Top 10 (Figure 6). Cultures were grown in microtiter plates in media with varying lactate concentrations. Density and fluorescence measurements were taken every 15 minutes to ensure a high enough time-resolution. A detailed protocol is available in Protocols.
RESULTS
The data is very noisy and it’s hard to make general statements about this systems behaviour. Despite this, a clear trend is visible for GFP to be higher expressed under lactate concentrations similar to tumor tissue than under those resembling healthy tissue or no lactate at all. With increasing population densities this effect becomes less pronounced (Figure 7).
CONCLUSION
- Due to a lot of noise in the data, conclusions have to be drawn with caution
- Under lactate concentration mimicking tumor tissue, GFP gets stronger expressed than under lactate levels associated with healthy tissue.
- Fold-changes are around 4 for design B and 2 for design A which is considerably less than observed in Figure 5. This might be due to a somewhat different experimental setup.
References
- Contois, D. E. "Kinetics of bacterial growth: relationship between population density and specific growth rate of continuous cultures." Microbiology 21.1 (1959): 40-50. doi: 10.1099/00221287-21-1-40