PART.1 Background

Type I diabetes (T1D) is an auto-immune disease characterized by the destruction of β cells in the islets of Langerhans, leading to an absolute deficiency in insulin secretion.

Figure 1. Distribution of type l diabetes patients in the global population

Table 1. Top 10 countries or territories for estimated number of incident (new)cases of type 1 diabetes in children and adolescents (0-19 years) per annum

 Type I diabetes affects a significant portion of the global population. In China alone, 25% of diabetic patients are diagnosed with T1D. The incidence and prevalence of T1D are rising annually, comprising 5% to 10% of all diabetic cases. Notably, the incidence rate among individuals aged 0-14 years in China is 1.93 per 100,000, higher than in other age groups (Weng et al., 2018; Mobasseri et al., 2020).

Table 2. Challenges with the diagnosis of adult-onsettype 1 diabetes

 The risk factors for T1D include genetic predisposition, toxins, immune system disorders, and viral infections. Specific HLA alleles have been closely associated with the development of T1D (Riddell et al., 2017).

Figure 2. Age distribution of type I diabetes patients in the global population

 T1D can lead to various complications, including acute ketoacidosis, chronic diabetes-related foot issues, and complications involving other organ systems. Studies also indicate that adults with T1D have an increased risk of developing other auto-immune diseases, with about 30% of adults showing thyroid auto-immunity (Riddell et al., 2017).

Figure 3. The risk factors of type I diabetes

Currently, the treatment of T1D includes drug therapy and transplantation therapy. Insulin remains the primary medication, necessitating multiple daily injections or the use of automated insulin delivery systems like insulin pumps, with continuous blood sugar monitoring. These treatments require lifelong commitment and can cause side effects such as injection site pain, subcutaneous fat hyperplasia, and hypoglycemia (Mobasseri et al., 2020; Shaw et al., 2002).

Transplantation therapies, including pancreas, islet, and stem cell transplants, offer an ideal solution but are limited by immune response challenges and donor scarcity. Therefore, new therapeutic approaches are needed to address these limitations (Nissim et al., 2017).

PART.2 Our Project

Our project involves developing a sophisticated glucose-sensitive insulin production system using the synthetic biology. The core components include:

(1) GI-GAL4 and LOV-VP16 Genes: the expression of these genes are controlled by the glucose-sensitive GIP promoter, which is activated in response to elevated glucose levels.

(2) Insulin Gene: the expression of insulin gene is regulated by the UAS promoter, which is activated by the GAL-VP16 transcription factor.

(3) A blue light, which is switched on when  the glucose level reaches to the pathological levels. The blue light then catalyzes the covalent conjugation of GI-GAL4 and LOV-VP16 proteins to form an active GAL4-VP16 transcription factor, which in turn promotes the insulin gene expression (Yazawa et al., 2009; Mansouri et al., 2021).

In our project, we design an AND logic to ensure the insulin expression only under pathological glucose level.
First, GI-GAL4 and LOV-VP16 proteins were induced under relatively high glucose level due to the glucose-sensitive GIP promoter at their upstream regulatory regions. However, these proteins are not active as Gal4 DNA-binding domain and VP16 transactivator domain are seperatedly expressed.

Figure 4. System Overview

Then, we built a hardware, which can measure the glucose level and switch the blue light when glucose level reaches a pathological level. As a result, the blue light promotes the the covalent conjugation of GI-GAL4 and LOV-VP16 proteins to form an active GAL4-VP16 transcription factor, which induce the insulin gene expression under a UAS promoter control.

Figure 5. System Overview

Furthermore, we constructed a braking system to avoid potential hypoglycemia due to the  persistent induction of insulin expression by the Gal4-VP16 transcription factor. First, a microRNA binding site (miR-BS) was constructed at the 3’-UTR of Insulin gene. And microRNA was constantly expressed under the control of U6 promoter. Second, a sponge, which can absorb miRNA, was expressed under the control of GIP promoter. Therefore, when glucose level is relative high, sponge was expressed and aborbed the miRNA, ensuring the expression of insulin. However, when the glucose level drops, the expression of sponge was decreased and miRNA was released to inhibit the expression of insulin by binding to the 3’-UTR of Insulin gene (Yazawa et al., 2009).

Figure 6. System Overview

(1) Designer Cells: the genetic components will be transfected into human cell lines, such as 293T cells. The designer cells can be encapsulated in materials like microcapsules, hollow fiber membrane tubes, and sodium alginate gel, and used for subcutaneous implantation.

(2) The hardware which can sense the glucose level and switch on the blue ligh, can be improved to a watch-like wearable device in the future.  

(3) Regulated Insulin Secretion: This setup aims for
precise control of insulin release, adapting to blood
glucose fluctuations and improving diabetes
management.  

PART.3: More Details

Lab Notebook:https://2024.igem.wiki/csu-china/lab-notebook

Model:https://2024.igem.wiki/csu-china/model

Human Practices:https://2024.igem.wiki/csu-china/hp-overview

PART.4: Applications

 Our project envisions the subcutaneous implantation of Designer cells encapsulated in materials such as microcapsules, hollow fiber membrane tubes, and

sodium alginate gel. This setup aims to achieve regulated insulin secretion and blood glucose control.

PART.5: Significance

(1) An AND logic, including gentic circuits and biosensors, to precisely control insulin synthesis based on blood glucose concentration.
(2) A miRNA-Sponge system to prevent hypoglycemia due to persistent induction of insulin expression by the Gal4-VP16 transcription factor.

PART.6: References

1. Mobasseri, M., et al. (2020). Prevalence and incidence of type 1 diabetes in the world: a systematic review and meta-analysis. *Health Promotion Perspectives*, 10(2), 98-115. doi: 10.15171/hpp.2020.18
2. Weng, J., et al. (2018). Incidence of type 1 diabetes in China, 2010-13: population based study. *BMJ*, 360, j5295. doi: 10.1136/bmj.j5295
3. Boylan, M. O., Jepeal, L. I., Jarboe, L. A., & Wolfe, M. M. (1997). Cell-specific expression of the glucose-dependent insulinotropic polypeptide gene in a mouse neuroendocrine tumor cell line. *Journal of Biological Chemistry*, 272(28), 17438-17443. doi: 10.1074/jbc.272.28.17438
4. Yazawa, M., Sadaghiani, A. M., Hsueh, B., & Dolmetsch, R. E. (2009). Induction of protein-protein interactions in live cells using light. *Nature Biotechnology*, 27(10), 941-945. doi: 10.1038/nbt.1569 5. Mansouri, M., Hussherr, M. D., Strittmatter, T., Buchmann, P., Xue, S., Camenisch, G., & Fussenegger, M. (2021). Smart-watch-programmed green-light-operated percutaneous control of therapeutic transgenes. *Nature Communications*, 12(1), 3388. doi: 10.1038/s41467-021-23572-4
6. Riddell, M. C., Gallen, I. W., Smart, C. E., Taplin, C. E., Adolfsson, P., Lumb, A. N., Kowalski, A., Rabasa-Lhoret, R., McCrimmon, R. J., Hume, C., Annan, F., Fournier, P. A., Graham, C., Bode, B., Galassetti, P., Jones, T. W., Millán, I. S., Heise, T., Peters, A. L., Petz, A., & Laffel, L. M. (2017). Exercise management in type 1 diabetes: a consensus statement. *Lancet Diabetes & Endocrinology*, 5(5), 377-390. doi: 10.1016/S2213-8587(17)30014-1