Results

GCGR Predator Module

The corner stone of the GCGR Predator design is to assume that the ligand-IgG FC fusion protein and endogenous receptors interact within the endomembrane system. Such intracellular ligand-receptor interaction should also be spatiotemporally correct to trigger the Trim21 based protein degradation cascade. To test the such hypothesis, we first performed immunoprecipitation assay to determine if the intracellular ligand-receptor interaction occur. For such matter, HepG2 cells were transfected with Gcg-Fc expressing cassette or GCGR Predator (GCGR Pr) expressing cassette. Immunoprecipitation was performed with IgG-Fc targeting Protein A/G beads 48 h posttranscription followed up by Western blotting analysis probing GCGR and the Gcg-Fc domain of the GCGR Predator (Figure 1a). Results showed that interaction signal between Gcg-Fc and GCGR could be observed on Gcg-Fc transfected group while the non-transfected group showed no corresponding signal. Surprisingly Cells transfected with GCGR Pr plasmids showed significantly weaker interaction signal together with a significantly lower GCGR abundance, we reasoned that might due to the Trim21 mediated GCGR degradation. We then performed Western Blotting to further proof that such interaction is capable of triggering GCGR degradation. Results indicated that GCGR Pr transfected cells showed ~40% lower GCGR level comparing to the vector control (Figure 1c). For a closer mimic to the in vivo application condition, we packed GCGR Predator into Adenovirus for circuit delivery into mouse primary hepatocytes. Western Blotting showed that a 50% GCGR decrease 48 hours post-infection comparing to cells infected by the control Ade-GFP virus (Figure 1d). These results implied that GCGR Predator mediates in vitro and ex vivo GCGR degradation via physically interact with endogenous GCGR.

Figure 1. GCGR Predator mediates GCGR degradation by direct interaction with endogenous GCGR. (a). Schematic representation of co-IP assay; (b). co-IP-blotting analysis; (c). Lipofectamine delivered GCGR Predator mediates GCGR degradation in HepG2 cells. Left panel: representative blotting of GCGR degradation; right panel: statistical gray scale analysis of blotting assays; (d). Adenovirus delivered GCGR Predator mediates GCGR degradation in primary mouse hepatocytes. Left panel: representative blotting of GCGR degradation; right panel: statistical gray scale analysis of blotting assays. “GCGR Pr” stands for GCGR Predator. Relative protein expression levels were calculated by using β-actin expression level as initial normalization and then set the protein expression level in the control groups arbitrarily as 1.0. Error bar represents SD of at least 3 biological replicates, ** p<0.01.

Since changes on glucose metabolic program is expected under GCGR depletion¹, we performed metabolic analysis to determine if our GCGR Predator could generate similar phenotype changes. For such assay, cells were transfected with GCGR Predator by adenovirus (for mouse primary hepatocytes) or lipofectamine (for HepG2 cell line) and stimulated with Glucagon in DMEM medium without glucose (Figure 2a). To measure the overall glucagon sensitivity, glucose concentration in the medium was evaluated by glucose oxidase assay. As shown in Figure 2b, GCGR predator carrying cells showed significantly lower glucose concentration (~20% and ~60% decrease in HepG2 cells and mouse primary hepatocytes respectively) in the culture medium comparing to the control group (vector control for HepG2, and Ad-GFP control virus for mouse primary hepatocytes), indicating a significantly impaired overall glucagon sensitivity mediated by GCGR Predator. To further reveal the metabolic changes generated by GCGR Predator, we used quantitative PCR analysis and Periodic Acid-Schiff (PAS) staining Assay to evaluate the cellular gluconeogenesis and glycogenolysis process. Results showed that GCGR Predator transfection significantly down-regulates the expression of key enzymes in gluconeogenesis pathway, Glucose 6-phosphatase (G6Pase) and Phosphoenolpyruvate carboxykinase (PEPCK) (Figure 2c). Also, significantly higher amount of glycogen could be observed in the GCGR Predator transfected cells under glucose starvation, indicating lower glycogenolysis activity (Figure 2d). Generally, these results indicated that GCGR predator significantly impairs hepatocyte glucagon sensitivity in vitro and ex vivo by affecting metabolic programs downstream of GCGR.

Figure 2. GCGR predator impairs hepatocyte glucagon sensitivity in vitro and ex vivo by affecting GCGR-downstream metabolic programs. (a). Schematic representation of the functional assay workflow; (b). Glucose production analysis of HepG2 cells or mouse primary hepatocytes transfected with GCGR predator; (c). Quantitative PCR assay of G6Pase and PEPCK in HepG2 cells or mouse primary hepatocytes transfected with GCGR predator; (d). Representative glycogen staining microscopy of GCGR predator transfected HepG2 cells or mouse primary hepatocytes. “GCGR Pr” stands for GCGR Predator. Relative gene expression was calculated using the 2^-ΔΔCT method, with initial normalization of genes against Hprt1 mRNA within each group. The expression levels of each gene in the control groups were arbitrarily set to 1.0. Error bar represents SD of at least 3 biological replicates, * p<0.05, ** p<0.01.

Glucose Sensing Module

(See the design of this module here)

To optimize the design of our glucose sensing module, four promoters were designed with different number of CHREBP binding motif (Figure 1a). To characterize the CHREBP activation, Glucose sensing promoters (GSPs) were cloned into pGL3 vector to control the expression of firefly luciferase. Corresponding plasmids were co-transfected into HepG2 cell line with SV40-rluc internal control plasmid. As is shown in Figure 3b, comparing to mini-Promoter, 3x GSP, 6x GSP and 9x GSP all showed significant increase of luciferase signal. The transcriptional strength showed a significant or margnially significant improvement of 9×GSP comparing to that of 3×GSP or 6×GSP counterparts. To validate the glucose responsiveness, we challenged the 9x GSP-luciferase carrying cells by culturing cells in 5mM or 20mM glucose after overnight starvation. Results showed a ~1.5-fold increase of luciferase signal in 20 mM treatment group comparing to the 5 mM group.

To further characterize the glucose sensing module, we generated a 9x GSP-GFP reporter plasmid to increase the detection throughput. By using CMV-mcherry to normalize the effect of glucose on general exogenous gene expression level, we demonstrated that the 9x GSP is capable of activating gene expression in a glucose dose dependent manner (Figure 3d).

Figure 3. Glucose sensing by CHREBP binding hybrid promoter. (a) Schematic representation of the promoter design; (b). Transcriptional strength analysis of different GSPs; (c) Glucose response of 9x GSP-luc cassette; (d) Glucose response profiling of 9x GSP-GFP cassette. Fluorescent intensity of GFP or RFP was calculated by imaging gray scale analysis. Relative luminance was calculated by normalizing to Renilla luciferase signal, relative Fluorescent Intensity was calculated normalizing RFP signal. To calculate fold changes, levels of each control groups (minip or low glucose groups) were arbitrarily set to 1.0. Error bar represents SD of at least 3 biological replicates, * p<0.05, ** p<0.01.

Integrated Analysis

(See the design of this module here)

To further understand how our two modules may work together and to validate the in vivo performance of our circuit, we developed a set of mathematical models on molecular, cellular and whole-body level. To be specific, a cellular glucose sensing model, a protein degradation model, and a whole-body glucose-insulin-glucagon model were built based on fundamental biochemical and physiological principles (Figure 4a). By integrating three models, we obtained glycemia simulation results under different conditions. Healthy object showed stabled glycemia level at around 96 mg/dL. By decreasing insulin sensitivity by 50%, object showed significant hyperglycemia at around 133 mg/dL. When GCGR-Predator is introduced into the model with a strong constitutive promoter, object showed mild hypoglycemia (~53 mg/mL), which is consistent with the suggestions provided by HP expert interview as well as previous literatures^1-3. However, when GCGR Predator system is controlled by glucose sensing device, which provides feed-back control over the degradation of GCGR, simulation showed that the glycemia level would be stabled at around 86.7 mg/dL, indicating that the close-loop controlling system may provide a more robust control over the glycemia level (Figure 4b).

Figure 4. Glucose sensor-GCGR Predator chimera restores glucose homeostasis of T2D patients in silico. (a). Schematic representation of the modeling structure; (b). Glycemia simulation under different conditions.

Future Plan

Further characterize and optimize glucose sensing devices;
Combine the glucose sensing module with the GCGR predator module in wet lab, test the combined system on HepG2 and mouse primary hepatocytes;
We’re currently applying for animal use and ethical consent from IACUC for animal usage and in vivo experiments.

Reference

1 Christine, L. et al. Liver-specific disruption of the murine glucagon receptor produces α-cell hyperplasia: evidence for a circulating α-cell growth factor. Diabetes 62, 1196-1205 (2013).

2 Lok, S., . et al. The human glucagon receptor encoding gene: structure, cDNA sequence and chromosomal localization. Gene 140, 203-209 (1994).

3 Rivero-Gutierrez, B. et al. Deletion of the glucagon receptor gene before and after experimental diabetes reveals differential protection from hyperglycemia. Molecular metabolism 17, 28-38, doi:10.1016/j.molmet.2018.07.012 (2018).