Objective
The goal of this project is to create detailed blueprints for human natural β cells and stem cell-derived β-like cells (SC-β) by detecting a large number of proteins (>10,000) within the cells using advanced technology. The blueprints will contain each protein’s quantity and location within the cells. This information will tell us the detailed differences inside the cells, so we can find strategies to improve the function of SC-β, thereby advancing cell therapy for type 1 diabetes. Building on our previous research, we will use advanced techniques to analyze proteins in these cells more precisely than ever before.
In the first stage, we aim to detect proteins from different compartments within β cells. We will isolate the natural β cells and SC-β, and then break up the cells to separate different compartments, which will be analyzed with a highly sensitive instrument to identify and quantify proteins.
In the second stage, we aim to build the protein blueprints of the cells and find differences that could improve stem cell-derived β cells. Using sophisticated computational analysis, we will identify specific proteins that are expressed or located differently in SC-β compared to natural β cells. From there, we will identify potential drugs or factors that could enhance the stem cell-derived cells.
Background Rationale
Type 1 diabetes results from the body's immune system attacking its insulin-producing β cells in the pancreatic islets. Insulin is essential for regulating blood sugar levels, and its discovery transformed diabetes from a fatal disease into a manageable condition. Despite this, managing T1D remains costly and challenging. It has been demonstrated that replacing β cells by islet transplantation could control blood sugar levels, but there aren't enough organ donors to meet the demand. Stem cell-derived β-like cells (SC-β) have emerged as a promising alternative, potentially offering an unlimited supply of β cells.
Researchers have produced insulin-secreting SC-β cells from stem cells, which are now being tested in clinical trials. However, SC-β cells made by the current method are not yet as effective as natural β cells in our body. The insulin production and response to glucose in SC-β cells are still inferior. Studies have shown that SC-β cells remain immature compared to natural β cells. Our lab has created the largest dataset of protein profiles from natural and stem cell-derived islets, highlighting their significant differences in protein levels. These findings indicate that more work is needed to produce fully functional SC-β cells.
The locations of proteins within cells are crucial for determining their function. One protein may have different activities at different locations in the cell. By studying the locations of proteins within primary β cells and SC-β cells, we can gain insights into how to improve SC-β cell function.
Recent advancements in the technology have allowed us to detect a larger number of proteins with much greater detail and sensitivity. Our lab has detected approximately 7,000 proteins in natural human islets from 134 cadaveric donors and 25 batches of stem cell-derived islets, creating the largest dataset of its kind. Although it has revealed lots of their difference, we only detected approximately 55% of all proteins expressed in the islets, and we were only able to study all the islet cell types together instead of the β cells alone. In this study, we will separate the β cells and use a more advanced technology to analyze their proteins at many different locations within the cells. We expect to detect more proteins than before (>10,000) and also map their locations. The results will be a detailed blueprint of normal β cells SC-β, which can be used to construct better SC-β.
Description of Project
Type 1 diabetes (T1D) occurs when the body's immune system attacks its insulin-producing β cells in the pancreas. Insulin is essential for regulating blood sugar levels, and while it has been the primary treatment for T1D, managing the disease remains costly and challenging. Replacing β cells through islet transplantation has shown potential for controlling blood sugar levels, but there are not enough organ donors to meet the demand. Stem cell-derived β-like cells (SC-β) offer a promising alternative as they could provide an unlimited supply of β cells. However, current methods of producing SC-β cells do not result in cells that are as effective as natural β cells in our body. Protein locations within cells are crucial for their function, but this aspect has not been extensively studied in either natural or stem cell-derived β cells. Our project aims to understand their differences by analyzing not only the abundance but also the locations of proteins within the cells. We will use powerful technology capable of measuring thousands of proteins at once, rather than just a few at a time, to analyze the proteins across many different locations within the cells. We expect to identify and map more than 10,000 proteins overall. Then, using sophisticated computational methods, we will identify specific proteins that differ in their abundance or location between SC-β and natural β cells. This analysis will help us find potential drugs or factors that could improve SC-β cells. With the support of Breakthrough T1D/JDRF, our project will create a detailed blueprint of both natural and stem cell-derived β cells, highlighting targets to enhance SC-β cell functionality. It will also be a valuable resource for other researchers in the field, contributing to the global effort to produce better β cells and ultimately benefiting people with T1D.
Anticipated Outcome
We expect to identify and measure over 10,000 proteins from primary β cells and stem cell-derived β cells (SC-β), providing a highly detailed protein profile. We will develop reliable methods for isolating β cells and performing protein analysis, which can be used in future research. Using advanced technology and data analysis methods, we will measure the overall abundance and distribution of proteins in various cell compartments, providing a comprehensive view of protein organization. Our analysis will pinpoint where proteins are located within the cells and how their abundance or locations differ between primary β cells and SC-β cells. This will help us understand how to improve the function of SC-β cells. The insights gained will guide future experiments aimed at enhancing the functionality of SC-β cells, potentially leading to better treatments for type 1 diabetes. All our data will be made publicly available, serving as a valuable resource for other researchers in the field.
Relevance to T1D
While insulin therapy has been life-saving since its discovery in 1921, it is not a cure. Replacing β cells could potentially cure T1D, but the donor islets are limited, and the current methods cannot make fully functional SC-β yet. Our project aims to generate a wealth of new information on global protein abundance and locations for natural β cells and SC-β, and identify actionable targets to produce better SC-β cells with improved insulin secretion. By making our data open-source, we hope to empower the field to develop better insulin-producing cells, benefiting people with T1D. By sharing our data as a valuable public resource with other researchers in the field, we hope to accelerate the development of better SC-β cells and cell therapy for T1D.