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Perturb-Seq using T2D islets

ABSTRACT: Type 2 diabetes is associated with defective insulin secretion and reduced β-cell mass. Available treatments provide a temporary reprieve, but secondary failure rates are high, making insulin supplementation necessary. Reversibility of b-cell failure is a key translational question. Here, we reverse-engineered and interrogated pancreatic islet-specific regulatory networks to discover T2D-specific subpopulations characterized by metabolic-inflexibility and endocrine-progenitor/stem cell features. Single-cell gain- and loss-of-function and glucose-induced Ca++ flux analyses of top candidate MR in islet cells validated transcription factor BACH2 and associated epigenetic effectors as a key driver of T2D cell states. BACH2 knockout in T2D islets reversed cellular features of the disease, restoring a non-diabetic phenotype. BACH2-immunoreactive islet cells increased ~4-fold in diabetic patients, confirming the algorithmic prediction of clinically relevant subpopulations. Treatment with a BACH inhibitor lowered glycemia and increased plasma insulin levels in diabetic mice, and restored insulin secretion in diabetic mice and human islets. The findings suggest that T2D-specific populations of failing b-cells can be reversed and indicate pathways for pharmacological intervention, including via BACH2 inhibition.

ORGANISM(S): Homo sapiens

PROVIDER: GSE137766 | GEO | 2021/11/11

REPOSITORIES: GEO

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Project description:Pancreatic islet (dys)function is central to glucose homeostasis and type 2 diabetes (patho)physiology. Human islets consist of multiple endocrine (alpha, beta, delta, gamma), endothelial, and resident/inflitrating immune cells whose coordinated functions modulate glucose mobilization or disposal. Single cell transcriptome profiling (scRNA-seq) studies have been applied to dissect human islet cellular heterogeneity, identify islet cell (sub)populations, and define their molecular repertoire. However, precise understanding of cell type-specific alterations in type 2 diabetic vs. non-diabetic individuals is lacking, due in part to the limited number of individuals or single cell transcriptomes per individual profiled for comparison. Here, we create a comprehensive single cell transcriptome atlas of 245,878 human islet cells from 48 individuals spanning non-diabetic (ND), pre-diabetic (PD), and type 2 diabetic (T2D) states and matched for sex, age, and ancestry and define marker gene sets that are robustly expressed across disease states for each of the 14 cell types identified. We observe significant decreases in the number of beta cells sampled from T2D vs. ND or PD donors. Two of eight putative beta cell subpopulations, with ‘high functioning’ and ‘senescent’ cell gene signatures, increase and decrease in T2D donor islets, respectively. Importantly, we identify 511 differentially expressed genes in beta cells from T2D vs. ND donors. This includes monogenic and type 2 diabetes effector genes, such as HNF1A, DGKB, ST6GAL1, and FXYD2, for which genetic and environmental effects on their expression is concordant. Human beta cell and islet knockdown of selected newly-identified down-regulated genes impairs beta cell viability or function. Together, this study provides new and robust, cell type-resolved insights on the cellular and molecular changes in healthy vs. diabetic human islets and represents a valuable resource to the islet biology and type 2 diabetes communities.

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Perturb-Seq using T2D islets

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