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Project Abstracts - CBDS

Drivers and Consequences of Beta Cell DNA Damage in Type 1 Diabetes

Contact PI: Klaus Kaestner, PhD, University of Pennsylvania (UC4 DK116271)

Yuval Dor, PhD, Investigator, Hebrew University of Jerusalem
Ali Naji, MD, PhD, co-Investigator, University of Pennsylvania

 

Summary of Project Abstract & Publications

Start Date: September 20, 2017

 

Abstract

The prevalence of diabetes mellitus has reached epidemic proportions world-wide, and is predicted to increase rapidly in the years to come, putting a tremendous strain on health care budgets in both developed and developing countries. Both major forms of diabetes are associated with decreased beta-cell mass. Exciting recent data have provided evidence that metabolic stress is associated with DNA double strand breaks in multiple models of impaired glycemia.

We propose to develop novel technologies to determine physiological responses to genomic stress in human beta cells, including the potential accumulation of somatic mutations, all at the single cell level. In Aim 1, we will determine the molecular mechanisms that cause beta-cell DNA damage in diabetes, based on our hypothesis that metabolic and/or inflammatory insults and abortive replication attempts result in formation of double-strand breaks in beta-cells, potentially in discrete locations. To this end, we will perform genome-wide CHIP-Seq experiments with antibodies against the DNA damage response proteins 53BP1 and gamma-H2AX, as well as the BLISS method to reveal the location of actual DNA breaks at a single-base resolution in healthy and metabolically stressed beta-cells from mice and humans. In Aim 2, we will analyze the cumulative mutation load of human beta-cells in diabetes, based on our hypothesis that metabolic insults and abortive replication attempts result in the accumulation of somatic mutations, contributing to loss of function and possibly to immunogenicity in diabetes. To accomplish this goal, we will determine the cumulative mutation load of stressed beta-cells using single cell exome-, RNA-, and ATACseq analysis. We will employ cutting-edge and emerging technologies that are already established in our laboratories. We have assembled an outstanding team of scientists with complementary expertise, ranging from human islet transplantation to computational biology, to assemble an atlas of the human endocrine pancreas in health and disease at the single cell level. These datasets and technologies promise to greatly increase our understanding of the human beta cell in health and disease.