Patch-Seq Links Single-Cell Transcriptomes to Human Islet Dysfunction in Diabetes

• Published in: Cell metabolism Vol. 31; no. 5; pp. 1017 - 1031.e4
• Main Authors: Camunas-Soler, Joan, Dai, Xiao-Qing, Hang, Yan, Bautista, Austin, Lyon, James, Suzuki, Kunimasa, Kim, Seung K., Quake, Stephen R., MacDonald, Patrick E.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 05.05.2020
• Subjects: alpha cell; beta cell; cryopreservation; diabetes; islet; pancreas; patch-seq; single-cell RNA-seq; T1D; T2D; beta cell; alpha cell; pancreas; T1D; T2D; single-cell RNA-seq; islet; diabetes; patch-seq; cryopreservation
• ISSN: 1550-4131; 1932-7420; 1932-7420
• DOI: 10.1016/j.cmet.2020.04.005

Impaired function of pancreatic islet cells is a major cause of metabolic dysregulation and disease in humans. Despite this, it remains challenging to directly link physiological dysfunction in islet cells to precise changes in gene expression. Here we show that single-cell RNA sequencing combined with electrophysiological measurements of exocytosis and channel activity (patch-seq) can be used to link endocrine physiology and transcriptomes at the single-cell level. We collected 1,369 patch-seq cells from the pancreata of 34 human donors with and without diabetes. An analysis of function and gene expression networks identified a gene set associated with functional heterogeneity in β cells that can be used to predict electrophysiology. We also report transcriptional programs underlying dysfunction in type 2 diabetes and extend this approach to cryopreserved cells from donors with type 1 diabetes, generating a valuable resource for understanding islet cell heterogeneity in health and disease. [Display omitted] •Patch-seq links single-cell transcriptomes with physiology in 1,369 human islet cells•A set of 484 genes can predict β cell electrophysiology•Transcriptomic states of early β cell compensation and impairment in T2D were identified•Applying this approach to cryopreserved islets reveals α cell dysfunctional states in T1D Camunas-Soler, Dai et al. identify genes associated with islet cell function and dysfunction in diabetes by combining single-cell RNA sequencing and patch-clamp electrophysiology in human islet cells.