LINKING ISLET CELL FUNCTION TO SINGLE CELL TRANSCRIPTOMICS IN TISSUE TO IDENTIFY MOLECULAR MARKERS OF DIABETES

Single-cell RNA sequencing gives access to virtually every transcript in a cell, allowing us to monitor cellular states and cell identities.

However, methods to simultaneously profile transcriptome and cell function are scarce, making it difficult to establish direct links to cellular dysfunction in disease.

Similarly, it is difficult to connect these measurements to the cell environment, such as cell-to-cell interactions or metabolic and paracrine cues.

Here we will develop methods to simultaneously measure transcriptomes and high-throughput functional measurements with single-cell resolution. The goal being to obtain spatially-resolved information of tissue function and transcriptome. We will investigate pancreatic islets which regulate glucose levels and whose dysfunction is associated to diabetes.

The islet is a heterogenous mini-organ where vasculature, innervation and paracrine interactions determine hormone secretion, making it an ideal tissue to study the relationship between molecular heterogeneity and microenvironment. Moreover, diseases such as diabetes are associated to significant tissue remodeling.

We will leverage high-density microelectrode arrays and transcriptomics to quantify spatially-defined molecular heterogeneity within the human islet and identify changes that lead to dysfunctional cellular states in diabetes.

These methods could be extended to other excitable tissues where cell-type specific compartmentalization is essential to physiology.