Intercellular communication in pseudoislets: shaping the dynamics of insulin secretion

Glucose is the primary source of energy for the human body. When we eat, food is ultimately broken down into the necessary glucose and so, over the course of a full day, the amount of glucose in the blood varies. Both too high and too low blood glucose levels can cause potentially life threatening conditions. Blood glucose levels are regulated by two key chemicals: insulin, which lowers the level, and glucagon, which raises it. Both of these are produced naturally in the body in structures known as the islets of Langerhans, which are located in the pancreas.

Within the islets, the beta cells are responsible for the production and secretion of insulin. Insulin secretion is dependent on the synchronised electrical activity of all beta cells within an islet, which is achieved through communication between them. This communication arises primarily due to physical connections between neighbouring cells. If these connections are disrupted, the ability of the islets to secrete enough insulin to properly regulate blood glucose may become compromised.

Both forms of diabetes are associated with a loss of proper functioning of the islets. In type 1 diabetes, the beta cells are destroyed by the body's own immune cells. Below a critical beta cell mass, the body can no longer regulate blood glucose levels and patients become reliant on the administration of externally produced insulin. In type 2 diabetes, the functional changes are more subtle but may be caused by disruptions to the synchronised electrical response across an islet. One potential new therapy for type 1 diabetes involves the transplantation of beta cells into patients to compensate for the loss of their own cells.

We now have the capability to grow human beta cells in structures that mimic the islets of Langerhans in laboratories. This allows us to study the exact coupling between cells and observe the synchronisation of activity across the islet. We can also alter the laboratory grown islets in terms of their size, shape and the coupling between cells within them. In doing so, we can rigorously examine how how the connections between the cells quantitatively affect the secretion of insulin within an islet.

Mathematical models of biological networks provide powerful tools to simplify the analysis of large networks of cells. These models are constructed by considering mathematical descriptions of key biophysical processes that occur within and between the beta cells. Once developed, they can be used to investigate the mechanisms behind observed behaviours and, more importantly, they offer predictions about how changes to the communication between cells that occur during type 1 and 2 diabetes affect the secretion of insulin from the islet. Importantly, the connections between cells have been recently been highlighted as potential target for treatment of both forms of the disease. The predictions from the model will then be tested by performing similar alterations in the lab-grown islet.

Using the mathematical model, this project will investigate the prognoses of type 1 diabetes by considering how cellular communication is disrupted as the beta cells are destroyed, and how this impacts upon the secretory properties of the islets. It will also identify optimal sizes and configurations of islets with respect to insulin secretion to aid in the development of transplantation therapies for type 1 diabetes.

Insulin, one of the key hormonal regulators of blood glucose levels, is secreted into the blood by beta cells in the islets of Langerhans. Intercellular communication is critical to the secretory response of the islets. In particular, efficient insulin secretion has been linked to the synchronisation of electrical activity of beta cells across an islet, which is achieved through communication, primarily via physical connections between adjacent cells. Disruptions to the network structure can result in a loss of normal functioning of the islet.

This project will explore the mechanisms by which a network's size and structure impact its synchronisation properties using pseudoislets cultured from human beta (EndoC-BH1) cells. Pseudoislets are populations of beta cells that are grown in three dimensional structures that approximate real islets. Through the development of a detailed mathematical model of the pseudoislet, incorporating all relevant ion channels, I will examine in a systematic way how cellular communication affects synchronisation of the islets and ultimately, their secretory response. To calibrate the model, I will collect data from pseudoislets to characterise the electrically excitability of EndoC-BH1 cells using electrophysiology techniques and map out the connections between them using immunohistochemical staining procedures.

After identifying the key network components, I will use the model to generate predictions about how manipulations to network size and structure will impact insulin secretion and perform experiments to test these and thus validate the model. I will then predict how the function of real islets becomes compromised as beta cells are lost during type 1 and 2 diabetes. Finally, I will identify the optimal size and configuration of an islet with respect to insulin secretion. This is particularly important as islet transplantation has been identified as a potential therapy for type 1 diabetes.

This research will provide concrete results about the link between structure and function of the islets of Langerhans and may identify potential new therapeutic pathways to treat type 1 diabetes that currently has only limited, expensive and lifelong options available. Furthermore, given that type 2 diabetes can also be caused by poor secretory function of the islets, this research may also elucidate new approaches to treat this form of the disease. This work may thus lead to positive impacts for a variety of beneficiaries.

Firstly, both patients of type 1 and type 2 diabetes and clinicians who treat these groups will benefit from better understanding of the respective impact of the disease on islet function and vice versa. Through this deeper understanding, the prognoses of the disease will improve by understanding how beta cell loss and the subsequent breakdown in cellular communication quantitatively affects insulin secretion. Even if a true cure does not result, improved management plans that require fewer interventions, may ultimately arise from any identified mechanisms to improve islet function.

The economic cost in terms of both treatment and lost income arising from type 1 diabetes is estimated to be £1bn and for type 2 diabetes is £9bn. Finding improved treatment plans will help to significantly reduce these costs. Furthermore, each year over £50m is annually invested into researching diabetes. Extensions of this project will ultimately provide a detailed in mathematical model of an islet that can be used to test potential pharmacological interventions in silico, thus acting as a screening process before significant money is invested for subsequent development and clinical trials, thus maximising the use of the relatively small amount of funding available.

The development of treatments involving transplantation of cultured beta cells into patients to mitigate the loss of patients' existing ones will be enhanced by the use of mathematical models to predict what size and configuration of islets are optimal in terms of their secretory function in response to glucose. This will both reduce the cost and increase the speed of the development of these treatments.

Whilst this project is focussed on beta cells, the research methodologies that will be developed are relevant to other biological problems, for example, the treatment of neural system disorders such as epilepsy and Parkinson's disease by neural prostheses, or understanding of disorders of the neuroendocrine system, such as hyperthyroidism. Thus, whilst not directly related to this project, researchers in these fields may also benefit from this project.

Through the various public engagement events planned during this project, the benefits of integrated approaches, together with the findings and methodology of current state-of-the-art research will be divulged to the public. The feedback and response from stakeholders in diabetes will ultimately play a role in shaping the translational aspirations of my long term research programme by focussing it on the treatment pathways that these groups desire. Finally, by improved public understanding of the causes of diabetes, I hope that the stigma associated with the diseases will be reduced.