ENGINEERING

Overview

Our goal is to create a mutation-specific high-throughput glioma drug screening platform. To reach this goal, culminating in the development of NODES, we followed an iterative engineering design cycle:

Our engineering design cycle is driven by data from testing and stakeholder feedback to allow for effective iteration and prototyping.

1. Designing NODES

Reporter Plasmids

While researching potential biosensors for D-2HG, we found a Nature Communications article by Xiao et al. outlining the discovery of an allosteric transcription factor, DhdR, from Achromobacter denitrificans NBRC 15125, which negatively regulates D-2HG dehydrogenase expression in response to D-2HG. [1] This article was the foundation of our reporter system. We ordered the human-codon optimized DhdR gene from Twist Bioscience, and inserted it into a commercially available pcDNA5/FRT plasmid ( Thermo Fisher, V601020) to serve as our biosensor.

Our reporter constructs consist of dhdO binding sites and a fluorescent (mCherry) reporter gene. Xiao et al. included a series of dhdO binding site sequences and their dissociation constants (KD), which reflect their binding affinities to DhdR [1]. he authors tested 14 different binding site sequences, but our team decided to focus on the two with the lowest KD, dhdO 0# and dhdO 5# (Figure 1).

Figure 1. Optimization of the D-2HG biosensor by mutating the cognate binding site. Figure 4a from “A D-2-hydroxyglutarate biosensor based on specific transcriptional regulator DhdR” [1]

After choosing these two binding site sequences, we designed ten binding site combinations with varying numbers of repeats and spacer sequences to engineer cooperativity in the transcriptional response. Oligonucleotides containing binding site sequences were obtained from Integrated DNA Technologies. The motivation behind this was to optimize the binding kinetics of our system, with the hopes of creating a tunable reporter or introducing positive cooperative binding that enhances reporter activity. Thus, our team hopes to test the ten binding site combinations to determine which variation offers the largest dynamic range of expressions, as this would allow our system to effectively serve as a live cell biosensor for the compound of interest, D-2HG, based on intracellular concentrations (Figure 2).

Figure 2. Graphic outlining the different binding site combinations that were synthesized for optimization

In a wild-type environment, without the presence of DhdR, we expect constitutive expression of the fluorescent protein as driven by CMV promoter expression. However, when DhdR is present, it will bind to the dhdO binding site, acting as a physical roadblock to transcription of our reporter gene. When D-2HG is elevated, as observed in IDH1 mutant cells, it interacts with DhdR, releasing it from the dhdO binding site. This allows for transcription of the downstream reporter protein sequence, resulting in brighter expression that is visible in our in vitro system (Figure 3). Since D-2HG levels are elevated due to the IDH1 mutation, we expect an increase in fluorescence due to the release of the DhdR caused by the binding of the upregulated oncometabolite. When we perform drug screening assays on our completed co-culture system, we will correlate decreased fluorescence with lower levels of D-2HG, corresponding to reduced tumor growth.

Figure 3. This figure outlines the mechanism of the interaction between the DhdR allosteric transcription factor and the dhdO binding site. The top of the figure outlines the normal expression of the reporter sequence, resulting in fluorescing cells. Case 1 is the wild-type condition with no D-2HG in the system. No fluorescence is expected in this case. Case 2 is the IDH1 mutant condition when D-2HG is upregulated. We expect fluorescence expression because of the interaction between D-2HG and DhdR.

2. Building NODES

Reporter Cloning

To develop a high-throughput, dynamically responsive drug screening platform, we needed to determine methods of characterizing cell behavior without lysing our samples. We first selected a reporter gene, mCherry, that has the ability to induce visually identifiable responses. We designed a plasmid that would constitutively express the desired mCherry fluorescence protein. To finalize the construction of the dhdO binding site constructs, we inserted ten variations of the binding site constructs using a restriction digest-ligation protocol into this constitutively expressing fluorescence plasmid, allowing the produced levels of mCherry to vary with the binding of the DhdR transcription factor (Figure 4).

Figure 4: Plasmid maps of the DhdR constructs. Left: CMV with DhdR-NLS-FLAG. Right: CMV with FLAG-NLS-DhDR. Both inserts were added to the pcDNA5 backbone.

Based on our proposed system design, we then constructed a plasmid to express the allosteric transcriptional repressor DhdR. We have two versions of the construct with different nuclear localization sequences and FLAG tag placements (DhdR-NLS-FLAG vs. FLAG-NLS-DhdR) and cloned them into pcDNA5 plasmids to determine which sequence order allows for better protein expression (Figure 5). Since the DhdR protein is a transcription factor, it has to be localized to the nucleus after expression. Therefore, we added a nuclear localization sequence (NLS) to the construct. In addition, the FLAG tag was attached for ease of Western blotting to validate that the protein was being expressed in mammalian cells. We used the anti-FLAG M2 mouse antibody ( Sigma Aldrich, F1804 to detect our FLAG-tagged protein.

Figure 5. Plasmid map of a Representative dhdO Binding Site Construct.

Additionally, we wanted to replicate the IDH1 mutation in our co-culture system. To do so, we constructed two plasmids: one containing the wild type IDH1 gene, and the other containing the IDH1 R132 mutant gene [2] (Figure 6). Both variations of the gene were inserted into the pcDNA vector backbone.

Figure 6: Plasmid map of the IDH1 WT and IDH1 R132 mutant constructs.

3. Testing NODES

Validating the Amount of D-2HG Present in Various Cell Types

To test the basic expression level of D-2HG in the cell lines we house in the lab, we carried out a D-2HG concentration measurement for cell contents, culture supernatant, and blank media controls. We used the D-2HG assay kit for this measurement ( Sigma Aldrich, MAK320-1KT). All our cell lines, organoids, supernatant, and blank media except for BXM4687 showed D-2HG levels below the detection range. HEK297 and A172 were both negative for intracellular D2HG, and were selected as recipients of the IDH plasmids to quantitatively study intracellular D-2HG production and reporter activity. BXM4687 will be subject to IDH1/2 locus sequencing to test for potential IDH mutations that lead to the accumulation of D-2HG.

Testing the Reporter System with Dual Transfection and Dosing

To test the integration of the various parts of the proposed system, a D-2HG dosing assay was performed. HEK 293T cells were transfected with the dhdO binding site plasmid (specifically, construct #5 from Figure 2). In addition, they were transfected with either GFP plasmid (control) or DhdR-expressing plasmid (experimental), which allowed us to determine whether or not the presence of the DhdR-mCherry construct itself impacts the observed fluorescence levels. Finally, cells in both conditions were dosed with D-2HG at various concentrations (0 µM, 0.01 µM, 0.1 µM, 1 µM, 10 µM, 100 µM, 1000 µM), allowing us to determine how the amount of D-2HG present impacted the measured fluorescence. 48 hours after dosing, cell fluorescence was evaluated through flow cytometry (Figure 7).

Figure 7: Graph showing the fluorescence levels under various conditions.

Testing the Expression of DhdR in Mammalian Cells

Because the DhdR transcription factor was originally identified in a bacterial system, we wanted to validate that this protein would be expressed when translated to a mammalian system. To do this, we transfected the DhdR expression construct into HEK 293T cells and ran a Western blot on the cell lysate in order to validate the presence of the desired transcription factor (Figure 8). Because the DhdR sequence included in our plasmids contained a FLAG tag at the end, an anti-FLAG M2 mouse antibody ( Sigma Aldrich, F1804 was used for the identification of the protein of interest on the blot.

Figure 8: Western blot results from SDS-PAGE of cell lysate, showing the presence of a band around 25 kDa in the 3’ DhdR and 5’ DhdR conditions and the lack of a band in the control condition

The presence of the band around 25 kDa indicated that the DhdR transcription factor of interest was being expressed in the transfected cells, validating that this component of our proposed system could be generated in mammalian cells. Further work would include running a native Western blot, which would allow us to validate that the DhdR transcription factor forms a dimer after expression in our mammalian system, as it does in the original bacterial system.

Testing Primary Cell Transfection

Although transfections are widely used to transfer plasmid DNA into common cell lines such as HEK 293T cells, plasmid transfections of glioma cells have not been well studied. Limited synthetic biology work has been performed on primary cells, including glioma cell lines, and in organoid co-culture settings. From our lipofection and electroporation experiments, we concluded that the 250V condition had the best balance of transfection efficiency and fluorescence expression (Figure 9).

Figure 9. Electroporation of Patient-derived Glioma Cells using different voltage conditions (200V, 250V, and 300V) with FUGW-GFP

Testing Tumor-Organoid Co-culture Drug Screening

To test and demonstrate the robustness of the co-culture system, we set up a drug assay experiment that mimicked the process of testing drugs with patient-derived cancer cell lines in a clinical setting. We used a patient-derived medulloblastoma cell line, D425-GFP, labeled with green fluorescent reporters. This line is known to be a fast-growing cancer cell line that is resistant to temozolomide (TMZ) at high doses. The drug assay using our co-culture system showed this trend as there were no significant differences in killing between the two TMZ doses (Figure 10).

Figure 10. TMZ drug assay over the course of 14 hours. There were no significant differences between the two doses.

We tested another drug, medroxyprogesterone acetate (MPA), which has been confirmed to have potent killing effects on D425-GFP, to show that the co-culture system conferred the same results as in previous studies. The drug was verified in patient-derived xenograft (PDX) models and pre-established cell lines and has been shown to cause strong and fast killing of the D425 cell line. Our co-culture system confirmed this trend and had results that agreed with previously published data (Figure 11).

Figure 11. The comparison between the killing effect of MPA over the course of 14 hours. Note that the two higher concentrations had no obvious differences in the killing.

The co-culture system also had the ability to demonstrate cell interactions and migrations visually. In a co-culture system, cancer cells migrate towards healthy cells, which is the target interaction some drugs inhibit. Upon introduction of cancer cells in the co-culture system, they tend to migrate towards healthy cells and invade the interior of healthy organoids. A drug that inhibits such an effect should then cause the cancer cells to remain dispersed randomly in the system, preventing the typical congregation of cancer cells at the edges of the organoids. We tested this idea in the co-culture system and it was clear that one verified drug, tazemetostat (EPZ), demonstrated this effect (Figure 12).

Figure 12. Comparison of invasion distance between the cancer cells and the normal mini brains in untreated control and two different doses of EPZ groups. Note the different distances between the cancer cells and mini brains (arrows) increasing as the drug concentration increases, and the different total amount of cancer cells (green) in each condition.

This demonstrated the functionality of our current co-culture platform, as it accurately recapitulated the differences between drug effects in varying doses and visually provided evidence that indicates inhibition of cancer cell migration. From this drug assay, we conclude that there is a high likelihood that our co-culture system holds accurate predictive power in regard to forecasting drug responses in vivo, and has a potential application in clinical settings.

4. Refining NODES

Despite being the most common malignant brain tumor, clinical treatment of glioma is severely limited by the lack of a scalable, physiologically-relevant model for testing therapeutics. To fully understand the implications of this problem, our team talked with researchers and individuals who work directly with patients to understand how our project scope should be refined to best address the needs of key stakeholders.

Throughout our engineering design process, we integrated stakeholder feedback to guide the development of our drug screening platform. Based on what we learned from the interviews, we verified the need for a glioma drug screening platform, pivoted to a preclinical trial drug screening tool, and shifted to a mutation-specific reporter system. To learn more about how we integrated stakeholder feedback to refine our project scope and execution, see the Human Practices page.

Figure 13. Refining project scope and execution

References

  1. Xiao, D., Zhang, W., Guo, X., Liu, Y., Hu, C., Guo, S., Kang, Z., Xu, X., Ma, C., Gao, C., & Xu, P. (2021). A D-2-hydroxyglutarate biosensor based on specific transcriptional regulator DHDR. Nature Communications, 12(1). https://doi.org/10.1038/s41467-021-27357-7
  2. Molenaar, R. J., Maciejewski, J. P., Wilmink, J. W., & van Noorden, C. J. (2018). Wild-type and mutated IDH1/2 enzymes and therapy responses. Oncogene, 37(15), 1949–1960. https://doi.org/10.1038/s41388-017-0077-z