Difference between revisions of "Team:Fudan/Demonstrate"

Although antigen density heterogeneity has been reported, it has been considered as an obstacle to improve cellular immunotherapy for tumor (1), rather than an opportunity to employ diverse and/or combined treatment. To demonstrate the feasibility of utilizing antigen density heterogeneity, we first established a cell model that is able to stably express different antigen densities on cell surface. We chose surface-expressed EGFP (surEGFP) as representative antigen due to the convenience of detecting, quantifying and observing (Figure 1A).

After viral infection, K562-surEGFP cells were observed by microscopy. Image shows that the endoplasmic reticulum (ER) membrane has strong fluorescence, while the plasma membrane has relative weak signal. It consists with the process that surEGFP is expressed, translocated and matured inside ER lumen with its transmembrane embed in the ER membrane, and later surEGFP is transported and exposed to culture media when fluorescence declines due to oxidation in the extracellular environment. Thus, surEGFP was successfully located to cell membrane (Figure 1B). We sorted stable cell lines depending on EGFP fluorescence intensities (Figure 1C, S1A). The FACS gate set in FSC-SSC channel was relative narrow to insure we can get a group of cells with homogeneous size, to exclude the possibility that the heterogeneous expression of EGFP was due to different cell surface area (Figure S1B, C). We confirm the FASC-ed cell clines with different EGFP expression by Western blotting using an anti-EGFP antibody (Figure 1D). The bands clearly show difference between low-, medium-, high-expression groups (Figure 1D). We also characterized two HCC (hepatocellular carcinoma) cell lines using an anti-GPC3 antibody. We confirmed that SMMC-7721 cells express no GPC3, while Huh-7 cells highly express GPC3 (Figure 1E). These cell lines are our physiological surface antigen density heterogeneity model.

Engineered Notch have been used in previous project (iGEM 2011 MIT). They replaced the intracellular domain of Notch1 by Gal4-VP16 (BBa_K511301). When the extracellular domain of Notch1 binding to the Delta ligand, Gal4-VP64 would be cleavage, located into nuclei, started transcription of its corresponding promoter Gal4-UAS (BBa_K511003). This year, we took a step forward on their achievement. Referring to a latest publication (2), we engineered a SynNotch that could recognize surEGFP and response with tTa (Figure 2).

In HeLa with LaG16-SynNotch-tTa and pTight cells, the tTa, which originally linked to the intracellular domain of SynNotch, after LaG16 (scFv against GFP) binds to surEGFP, will translocate from the plasma membrane into the nucleus. tTas activate pTight promoter and mCherry starts expression. We used the cells highly expressing surEGFP as the sender. Images show that the HeLa expresses mCherry when contacts with K562-surEGFP, while mCherry won’t be seen in the condition that the HeLa don’t contact with K562-surEGFP (Figure 3). Thus, we confirmed our SynNotch is can respond to surEGFP.

To generate an antigen density-dependent tri-response pattern for SwordS, designing the gene transcription network in Stripe plays a central role. We model the transcription network of Stripe (see Model:Network Modelling) to better understand the characters of Stripe. The theoretical basis of our model is explained in detail in Model:Theoretical Basis .
In silico modeling indicates that the key criterion for functional Stripe construction is the matching of orthogonal SynTF-SynPro pairs that enabled sufficient separation of the low and high thresholds. It enlightened us to create and characterize a set of SynTF-SynPro to achieve tunable intervals against tumor antigen with heterogeneity.
To provide further insights of the modelling procedures, we have created an online software to enable you to design and analyse your own gene transcription network (See Software ).

Here, we present an approach to design customized mammalian synthetic transcription factor (SynTF) –synthetic promoter (SynPro) pairs. SynTFs enable binding to user-specified DNA sequences (response elements, REs), SynPros, and silence or activate the transcription after SynPros. The SynTFs we designed were in a unified style containing three core domains from N-terminal to C-terminal: DNA binding domain (DBD), nuclear location sequence (NLS), and transcription regulating domain. We chose (G4S) as the linker to add between DBD and SV40 NLS (3) to provide region flexibility (4). We chose KRAB (5) or VP64 (6) as transcription regulating domain to construct silencing- or activating-form of SynTFs, named SynTF(S)s or SynTF(A)s. Their corresponding silencing- or activating-form SynPros, SynPro(S)s or SynPro(A)s, were pSV40-N*RE or N*RE-minCMV (Figure R3-1A). The critical step in choosing optimal SynTF group is to find enough specific and orthogonal DBDs. We used two approaches. First, we did reference search for those commonly used DBD originating from different species. Secondly, we in-house designed based on artificial zinc-finger (ZF). For the first approach, we chose Gal4DBD (2), PIP (7), ZFHD1 (8). For the second approach, we utilized a modified 3-tandem Cys2-His2 ZF (9) as protein chassis. By replacing the DNA-interactional amino residues on ZF modules (10), we have generated RE-specific mammalian synthetic ZF (SynZF) (Figure R3-1B). The DBDs and their corresponding REs we used were listed in (Table R1) The SynTF-SynPro pairs we wired were listed in (Table R2)

After co-transfected SynTFs, the mCherry expressions controlled by corresponding SynPros were significantly reduced. The functional SynPros’ silencing fold arranged from 6-23 (compared to cells without SynTFs) (Figure R3-2A). We found that the RE repeats inserted after pSV40 3’ end can influence the basal expression of SynPros even without co-transfecting corresponding SynTFs. Above 7 SynTFs-SynPros we constructed and tested, 2 of them didn’t work. (1) It probably was due to the RE of SynPro(S)-42-10 couldn’t been recognized by SynZF-42-10 (Figure SR2-2A, B). Thus, the expression after co-transducing SynTF(S)-42-10 was higher than the solo-expression of some SynPros. (2) RE of SynPro(S)-54-8 might be antagonized by unknown proteins inside cells. Thus, the expression without or with SynTF were both low. We test our guess by co-transfecting different SynTFs with SynPro(S)42-10 and SynPro(S)-54-8 (Figure SR2-2B).

The zinc finger is a highly structured motif. In tandem with multiple zinc finger motif, the recognition precision can be enhanced as its extensive usage in genome editing (10). We applied this strategy to construct tunable SynTF-SynPro pairs. With more RE repeats, our SynTF has stronger inhibiting activity (Figure R3-2B).

To construct Stripe, two pairs of SynTF-SynPro are needed. The interaction between the pairs is not allowed. We did orthogonality experiments to check that. We confirmed that all of the 5 pairs were truly orthogonal (Figure R3-2C), as you could see the grids on the diagonal were always the darkest. Three DBDs that are commonly used in previous works performed well in our hands. However, the expression level of the RE loaded SynPros were relative low compared to SynPro(S)-ZF serials. As the blue rectangle in the lower right corner of the orthogonality may showed the SynPro(S)-ZF has high basic expression with unpaired SynTFs, but could be silenced to the similar fold of commonly used DBDs corresponding SynPros. The SynPro(S)-ZF was likely won’t be target by other unpaired DBD, hence the purple appeared on the bottom rows.

In summary, we successfully constructed a SynTF-SynPro repertoire whose expression features could be finely tuned by either using different DBDs with REs or changing the number of RE repeats. Meanwhile, among all the orthogonal SynTF-SynPro pairs we constructed and test, our favorite ones were SynTF(S)-PIP-SynPro(S)-PIP;4* and SynTF(S)-ZF43-8-SynPro(S)-ZF43-8;8*. The combining results in pink rectangels show that they are both with low leakage, and the thresholds were far separated (PIP: -71 folds; ZF43-8: -8 folds) (Figure R3-2C, S3-2C). So far, we have characterized and obtained two promising SynTF-SynPro pairs to use in the Stripe module.

First, we have established a cell model with heterogeneous surEGFP expression and characterized the expression pattern of two HCC cell line (Huh-7, SMMC-7721) with different GPC3 expression level as our physiological model. Second, we engineered a functional SynNotch and proved they can generate response upon binding to their corresponding ligands. Third, we have mathematically modeled our transcription network in the Stripe model, and confirmed our design will generate tri-response with one heterogeneous antigen. Fourth, we used two approaches to wire SynTF-SynPro pair. We constructed, characterizes a set of pairs and obtain two optimal SynTF-SynPro pairs. We are still one step away from demonstrating the feasibility of SynNotch-Stripe experimentally, and we are doing it right now. We believe it is a promising platform for the next generation cellular immunotherapy.

1. We have tested a set of SynTF(S)–SynPro(S) pairs and has achieved good results. Similar, there should be a set of SynTF(A)–SynPro(A) pairs. Though, we didn’t have time to test them all before freezing due to limiting schedule, we will confirm them in the future.

2. Use SynTF(S)-PIP–SynPro(S)-PIP;4* and SynTF(S)-43-8–SynTF(S)-43-8;8* to construct a Stripe prototype and test its tri-response with EGFP coated beads.

3. Couple SynNotch module with Stripe module to construct a SwordS prototype and test its tri-response with different densities of surEGFP.

4. Test SwordS with HCC cells with different surface densities of GPC3. Currently, we have two cell lines, and our collaborators are actively searching for the third one.

5. Replace response product A and B with therapeutic factor I as IL-12, II as IL-18. Test its therapeutic effect on HCC cell lines.

In silico modeling indicates that the key criterion for functional Stripe construction was the matching of orthogonal SynTF X and SynTF Y that enabled sufficient separation of the low and high thresholds. Although previous published workshas reported a synthetic Stripe-like circuit in bacterial⁽²¹⁾ or in mammalian⁽²²⁾ cells,a tunable system has not yet been created. Their output responses to signal intensity are relative fixed, which means they response to high, moderate, and low levels of input with constant intervals. However, tunable intervals should be built so that the system can be tuned to against tumor antigen with heterogeneity.We created and characterized SynTF-SynProto response to desired intervals. This set is a powerful toolbox to construct customized signaling sorting characteristics.

Liver cancer, including HCC (hepatocellular carcinoma), is an extraordinarily heterogeneous disease because of its diversity. As a result, individualized therapy isgreatly needed⁽²³⁾. Antigen expression pattern is related to HCC progression and prognosis. High expression of HCC-associated tumor antigen was associated with better prognosis(16):EpCAMwhose positive or negative expression can be an indicator to distinguish HCC subtype⁽²⁴⁾and the expression of GPC3 is more frequently observed in moderately or poorly states HCC than in well state one⁽²⁵⁾.Executing combinationalimmunotherapy is believed to be a dramatic improvement of treatment to HCC^{(26, 27)}. With SwordS and the known tumor antigen GPC3, we propose to release therapeutic factor I when GPC3 is mediam and release therapeutic factor II when GPC3 is high. For example, when the expression of tumor antigen is high, the acquired immune system is easier to identify tumor, a therapeutic factor which can enhance acquired immune system might generate a better therapeutic effect; a therapeutic factor which can enhance inherent immune system might have a better effect when the tumor antigen expression is low. Thus, weassumethat designating therapeutic factor I as IL-12 (which can drive potent innate immune responses to cancer) and designating therapeutic factor II as IL-18 (which can promote CD8⁺ T cells is a rational combination for SwordS.

When the expression of the tumor antigen is high, acquired immune system is relatively easy to identify tumor cells, a therapeutic factor which can enhance acquired immune system might be beneficial for the treatment. Thus, we propose IL-18 as the designating therapeutic factor II, which is secreted protein and promotes the proliferationof CD8⁺ T cells⁽²⁸⁾. When the tumor antigen expression is mediam, expressing a therapeutic factor that can enhance innate immune system and facilitate the recognition by acquired immune system might be better. Thus, we propose IL-12 as the designating therapeutic factor I, which could drive potent innate immune responses to cancer⁽²⁹⁾. In summary, with SwordS, we are able to differential express either IL-12 or IL-18 depending the surface antigen destiny, to strategically kill tumor cells

We did a lot of workto demonstrate the feasibility of our project and preliminarily characterized SynTF-SynPro set.

We believe SwordS is a universal solution for various cancers. When we need to demonstrate our idea in one specific cancer, we picked the one with highest risk for Chinese popultion, HCC.