Human Pancreatic α-Cell Heterogeneity and Trajectory Inference Analysis Using Integrated Single Cell- and Single Nucleus-RNA Sequencing Platforms.

ABSTRACT

Prior studies have shown that pancreatic α-cells can transdifferentiate into ß-cells, and that ß-cells de-differentiate and are prone to acquire an α-cell phenotype in type 2 diabetes (T2D). However, the specific human α-cell and ß-cell subtypes that are involved in α-to-ß-cell and ß-to-α-cell transitions are unknown. Here, we have integrated single cell RNA sequencing (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) of isolated human islets and human islet grafts and provide additional insight into α-ß cell fate switching. Using this approach, we make seven novel observations. 1) There are five different GCG -expressing human α-cell subclusters [α1, α2, α-ß-transition 1 (AB-Tr1), α-ß-transition 2 (AB-Tr2), and α-ß (AB) cluster] with different transcriptome profiles in human islets from non-diabetic donors. 2) The AB subcluster displays multihormonal gene expression, inferred mostly from snRNA-seq data suggesting identification by pre-mRNA expression. 3) The α1, α2, AB-Tr1, and AB-Tr2 subclusters are enriched in genes specific for α-cell function while AB cells are enriched in genes related to pancreatic progenitor and ß-cell pathways; 4) Trajectory inference analysis of extracted α- and ß-cell clusters and RNA velocity/PAGA analysis suggests a bifurcate transition potential for AB towards both α- and ß-cells. 5) Gene commonality analysis identifies ZNF385D, TRPM3, CASR, MEG3 and HDAC9 as signature for trajectories moving towards ß-cells and SMOC1, PLCE1, PAPPA2, ZNF331, ALDH1A1, SLC30A8, BTG2, TM4SF4, NR4A1 and PSCK2 as signature for trajectories moving towards α-cells. 6) Remarkably, in contrast to the events in vitro , the AB subcluster is not identified in vivo in human islet grafts and trajectory inference analysis suggests only unidirectional transition from α-to-ß-cells in vivo . 7) Analysis of scRNA-seq datasets from adult human T2D donor islets reveals a clear unidirectional transition from ß-to-α-cells compatible with dedifferentiation or conversion into α-cells. Collectively, these studies show that snRNA-seq and scRNA-seq can be leveraged to identify transitions in the transcriptional status among human islet endocrine cell subpopulations in vitro , in vivo , in non-diabetes and in T2D. They reveal the potential gene signatures for common trajectories involved in interconversion between α- and ß-cells and highlight the utility and power of studying single nuclear transcriptomes of human islets in vivo . Most importantly, they illustrate the importance of studying human islets in their natural in vivo setting.