Genome editing of human pancreatic beta cell models: problems, possibilities and outlook

Abstract

Understanding the molecular mechanisms behind beta cell dysfunction is essential for the development of effective and specific approaches for diabetes care and prevention. Physiological human beta cell models are needed for this work. We review the possibilities and limitations of currently available human beta cell models and how they can be dramatically enhanced using genome-editing technologies. In addition to the gold standard, primary isolated islets, other models now include immortalised human beta cell lines and pluripotent stem cell-derived islet-like cells. The scarcity of human primary islet samples limits their use, but valuable gene expression and functional data from large collections of human islets have been made available to the scientific community. The possibilities for studying beta cell physiology using immortalised human beta cell lines and stem cell-derived islets are rapidly evolving. However, the functional immaturity of these cells is still a significant limitation. CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9) has enabled precise engineering of specific genetic variants, targeted transcriptional modulation and genome-wide genetic screening. These approaches can now be exploited to gain understanding of the mechanisms behind coding and non-coding diabetes-associated genetic variants, allowing more precise evaluation of their contribution to diabetes pathogenesis. Despite all the progress, genome editing in primary pancreatic islets remains difficult to achieve, an important limitation requiring further technological development.

Keywords: Beta cells; CRISPR-Cas9; Cell models; Diabetes; Genome editing; Human islets; Pancreas; Review; Stem cells.

Fig. 1

The central role of human beta cell models in the functional analysis of diabetes-associated genotypes. Genetic variants identified in people affected with diabetes (via genetic studies) can be interpreted using integrated functional genomic data (databases, prediction tools, epigenetic data, etc.). Candidate genetic variants require validation in relevant experimental models. Genome engineering technologies (e.g. gene knockout, base editing and genetic recombination) facilitate the genetic manipulation of cellular models to elucidate the role of the candidate genetic variants. In particular, genome engineering using CRISPR-Cas9 systems (consisting of two parts: a Cas9 endonuclease protein and gRNAs) have recently opened exciting new avenues for interrogating the functional impact of diabetes-associated genetic variants. These genome engineered models might also be utilised as scalable drug-screening platforms. Understanding the functional impact of diabetes-associated genetic variants will allow better diagnosis and stratification of diabetes cases, implementation of more effective interventions for diabetes prevention and more optimal personalised treatment for people affected by diabetes. KO, knockout; RNAseq, RNA sequencing; WES, whole exome sequencing; WGS, whole genome sequencing. This figure is available as a downloadable slide