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| − | After defining the experimental parameters we were able to test the cytotoxic potential of our azurin-rich bacterial lysate against different cancer cell-lines. Simultaneously, our Freiburg collaborators provided us with a killing curve of purified Azurin against HEK - 293 cells, enabling the comparison between the efficacy of purified azurin and azurin - rich bacterial lysate. | + | <p>After defining the experimental parameters we were able to test the cytotoxic potential of our azurin-rich bacterial lysate against different cancer cell-lines. Simultaneously, our Freiburg collaborators provided us with a killing curve of purified Azurin against HEK - 293 cells, enabling the comparison between the efficacy of purified azurin and azurin - rich bacterial lysate. |
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Revision as of 23:34, 31 October 2017
Anti-Cancer Toxin Experiments
Introduction
Once a tumor environment has been recognized and colonized by our bacteria, the production of an anti-cancer toxin, together with an MRI Contrast Agent agent will be triggered. The module that we engineered to achieve this purpose includes an AND-logic synthetic promoter that recognizes the presence of high lactate and high bacterial density in the tumor environment and allows the expression of the anti-cancer toxin, azurin, and the MRI Contrast Agent, bacterioferritin, from the same operon (Figure 1).
Once the Tumor Sensing has been activated, both the Anti-Cancer Toxin azurin and the MRI Contrast Agent bacterioferritin are produced. Azurin will accumulate inside of the bacteria until it is ready for release. Once the doctor verifies the bacterial colonization of the tumor bacteria via MRI, focused ultrasounds will activate Cell Lysis releasing an effective dosage of azurin to the tumor.
For more details about azurin and its role in our system, go to our description of the Anti-Cancer Toxin.
Overview of the Experiments
In our experiments, we replaced the AND-gate promoter in the genetic circuit depicted in Figure 1 with a well-established inducible promoter, Plux, in order to control the expression of the operon. Moreover, we coupled the expression of azurin with a fluorescence output as we exchanged the bacterioferritin gene with a gene encoding for superfolder GFP. In that way we could indirectly assess the functionality of our operon in a controllable manner (Figure 2). This circuit was transformed in E. coli TOP10 which was used for the production of azurin-rich bacterial lysate. Finally, the application of the bacterial lysate on different cancer-cell lines in vitro helped us to emulate the delivery of the anti-cancer payload via cell-lysis against different solid-tumor types.
Several preliminary experiments were conducted before the application of the bacterial lysate to different cancer-cell lines. Initially we examined the production of azurin from our engineered bacteria after induction with AHL, indirectly by detecting the fluorescence of the co-expressed sfGFP. An SDS-PAGE analysis confirmed the presence of azurin in the cytosolic fragment of E. coli after AHL induction. Further culture scale-up to 50 mL volumes allowed us the production of azurin-rich bacterial lysate via sonication. A second SDS-PAGE confirmed cell-lysis by sonication as all the overexressed azurin and sfGFP were detected together with the native proteins of E. coli within the lysate. Thanks to our collaborators from Freiburg, we were able to quantify the azurin-content of our bacterial lysate, as they provided us with purified azurin, which we used to create a standard curve of purified azurin concentration on the same SDS-PAGE gel.
With our bacterial lysate at hand we had to define the following parameters regarding the experimental set-up of mamalian cell incubation with our lysate:
- Which cancer cell-lines should we use?
- Which is the optimal number of cells to seed in our experiments?
- Will our calcein AM staining assay allow us to distinguish between alive and dead cells efficiently?
- How much of azurin-free bacterial lysate can our cells tolerate?
After defining the experimental parameters we were able to test the cytotoxic potential of our azurin-rich bacterial lysate against different cancer cell-lines. Simultaneously, our Freiburg collaborators provided us with a killing curve of purified Azurin against HEK - 293 cells, enabling the comparison between the efficacy of purified azurin and azurin - rich bacterial lysate.
To read more about each of these experiments, click on the buttons below. For a detailed protocol describing each experiment, visit Protocols.
Fluorescence Measurement to Obtain the AHL Dose-Response Curve
OBJECTIVE
Determine the dose-response curve and the concentration of AHL needed for full induction of the system are by measuring the fluorescence after induction with different concentrations of AHL.
PROCEDURE
Biological triplicates of E. coli Nissle transformed with AHL-inducible promoter that controls the expression of bacterioferritin and GFP (Figure 2) were transferred in a 96-well plate and induced with twelve different concentrations of AHL (from 0 to 10-2 M). Fluorescence and absorbance were measured in a plate reader over a period of 4 hours. A detailed protocol is available in Protocols.
RESULTS
Based on measurements of fluorescence over time, a time point t = 200 minutes was chosen as representative of the plateau region. The relationship of fluorescence at that time point and the concentration of AHL used for induction was plotted to obtain the AHL dose-response curve (Figure 3).
CONCLUSION
After consultation with the modelling team, we decided to use 1E-4 M of AHL for full induction of the system in future experiments. The measurements should be made at t = 200 minutes after induction.
SDS-PAGE to Confirm AHL-Induced Expression of Bacterioferritin
OBJECTIVE
The concentration of AHL needed for full induction of the system was calculated based on fluorescence measurements and the assumption that bacterioferritin is co-expressed alongside GFP upon activation of pLux (Figure 2). To confirm that bacterioferritin is indeed co-expressed, an SDS-PAGE analysis is performed.
PROCEDURE
Protein lysates were obtained from bacteria treated with different concentrations of AHL. To determine the concentrations of proteins, needed to prepare the samples for SDS-PAGE, Bradford protein assay was preformed prior to the SDS-PAGE analysis. A detailed protocol is available in Protocols.
RESULTS
To determine protein concentrations in the lysates via Bradford protein assay, a standard curve was first generated by using a protein standard, bovine serum albumin, and measuring absorbance of different dilutions of the standard. Second, absorbance of the unknown samples was measured and the results were fitted to the curve (Figure 4).
After determining the unknown concentrations, samples were prepared accordingly and subjected to SDS-PAGE analysis. Bands sized approximately 18.4 kDa (which corresponds to bacterioferritin) were visible in the samples treated with AHL. There were no bands in untreated samples or the negative control (Figure 5).
CONCLUSION
As expected, bands corresponding to bacterioferritin were visible in the samples induced with AHL. With this, to co-expression of bacterioferritin and GFP in the test strain for MRI experiments is confirmed.
Magnetic Resonance Imaging of Bacterioferritin-Expressing E. coli Nissle
OBJECTIVE
To visualize the signal change in MRI caused by overexpression of bacterioferritin, bacteria are grown in iron supplemented medium and imaged in an MRI scanner.
PROCEDURE
Biological triplicates of E. coli Nissle transformed with the heme-deleted bacterioferritin (Figure 2) were grown in four different experimental conditions (with and without induction and with and without iron supplementation) and imaged in a 4.7 T small animal MRI scanner. A bacterioferritin-expressing E. coli Top 10 (T7lacO-bfr) was used to compare the effect of the heme-deleted bacterioferritin against the wild-type bacterioferritin. Additionally, a bfr-knockout E. coli K-12 from the Keio collection was tested. A detailed protocol is available in Protocols.
RESULTS
All bacteria grown in iron-supplemented medium showed a drop in the T2 signal intensity, independent of induction of bacterioferritin expression. However, once induced, our bacteria experienced an additional drop in the signal, as predicted. The results are depicted as changes in the T2 relaxation rate, therefore a larger drop represents an increase in the change from the basal level, determined by imaging the bacteria grown without induction and without iron-supplementation (Figure 6).
All the bacteria were resuspended and imaged in PBS, after washing of the culture medium. To test if any unwashed iron could mask the signal, the T2 relaxation rate was compared in pure PBS versus PBS supplemented with iron. Moreover, a bfr-knockout was imaged to see how much the endogenous bacterioferritin contributes to the signal when the bacteria are grown in the presence of iron. The results showed that the free iron in the medium only slightly changes the signal and should not interfere with the measurements. On the other hand, the bfr-knockout strain showed the same behaviour as the wild-type bacteria, suggesting that other iron-storage systems present in the bacteria contribute to iron uptake significantly (Figure 7). The differences in absolute values of the signal changes might be explained by the fact that different strains of E. coli were imaged. T7lacO-bfr is Top 10, pLux-bfr M52L is Nissle, while the bfr-knockout is K-12.
CONCLUSION
A decrease in signal intensity was observed for all bacteria grown in iron supplemented medium, probably due to presence of inherent bacterial iron-storage proteins. However, an additional drop in the signal was observed in samples where bacterioferritin overexpression was induced, as predicted. This result proves the usability of bacterioferritin as an MRI contrast agent in vitro and confirms the potential to use it as an in vivo reporter of tumor sensing.
References
- Forbes, Neil S. "Engineering the perfect (bacterial) cancer therapy." Nature reviews. Cancer 10.11 (2010): 785.
- Cronin, M., et al. "Bacterial vectors for imaging and cancer gene therapy: a review." Cancer gene therapy 19.11 (2012): 731.
- Gilad, Assaf A., and Mikhail G. Shapiro. "Molecular Imaging in Synthetic Biology, and Synthetic Biology in Molecular Imaging." Molecular Imaging and Biology 19.3 (2017): 373-378.
- Lyons, Scott K., P. Stephen Patrick, and Kevin M. Brindle. "Imaging mouse cancer models in vivo using reporter transgenes." Cold Spring Harbor Protocols 2013.8 (2013): pdb-top069864.
- Cohen, Batya et al. “Ferritin as an Endogenous MRI Reporter for Noninvasive Imaging of Gene Expression in C6 Glioma Tumors.” Neoplasia (New York, N.Y.) 7.2 (2005): 109–117. Print.
- Hill, Philip J., et al. "Magnetic resonance imaging of tumors colonized with bacterial ferritin-expressing Escherichia coli." PLoS One 6.10 (2011): e25409.
