Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles

LGR4 is essential for maintaining β-cell homeostasis through suppression of RANK

Pancreatic β-cell stress contributes to diabetes progression. This study demonstrates that Leucine-rich repeat-containing G-protein-coupled-receptor-4 (LGR4) is critical for maintaining β-cell health and is modulated by stressors. In vitro , Lgr4 knockdown decreases proliferation and survival in rodent β-cells, while overexpression protects against cytokine-induced cell death in rodent and human β-cells. Mechanistically, LGR4 suppresses Receptor Activator of Nuclear Factor Kappa B (NFκB) (RANK) and its subsequent activation of NFκB to protect β-cells. β-cell-specific Lgr4 -conditional knockout (cko) mice exhibit normal glucose homeostasis but increased β-cell death in both sexes and decreased proliferation only in females. Male Lgr4 cko mice under stress display reduced β-cell proliferation and a further increase in β-cell death. Upon aging, both male and female Lgr4 cko mice display impaired β-cell homeostasis, however, only female mice are glucose intolerant with decreased plasma insulin. We show that LGR4 is required for maintaining β-cell health under basal and stress-induced conditions, through suppression of RANK.

Teaser

LGR4 receptor is critical for maintaining β-cell health under basal and stressed conditions, through suppression of RANK.

NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing

BACKGROUND

Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation.

RESULTS

We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed.

CONCLUSIONS

Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.

Pancreatic β-Cell Identity Change through the Lens of Single-Cell Omics Research

The main hallmark in the development of both type 1 and type 2 diabetes is a decline in functional β-cell mass. This decline is predominantly attributed to β-cell death, although recent findings suggest that the loss of β-cell identity may also contribute to β-cell dysfunction. This phenomenon is characterized by a reduced expression of key markers associated with β-cell identity. This review delves into the insights gained from single-cell omics research specifically focused on β-cell identity. It highlights how single-cell omics based studies have uncovered an unexpected level of heterogeneity among β-cells and have facilitated the identification of distinct β-cell subpopulations through the discovery of cell surface markers, transcriptional regulators, the upregulation of stress-related genes, and alterations in chromatin activity. Furthermore, specific subsets of β-cells have been identified in diabetes, such as displaying an immature, dedifferentiated gene signature, expressing significantly lower insulin mRNA levels, and expressing increased β-cell precursor markers. Additionally, single-cell omics has increased insight into the detrimental effects of diabetes-associated conditions, including endoplasmic reticulum stress, oxidative stress, and inflammation, on β-cell identity. Lastly, this review outlines the factors that may influence the identification of β-cell subpopulations when designing and performing a single-cell omics experiment.

Bulk and single-cell transcriptome datasets of the mouse fetal and adult rete ovarii and surrounding tissues

The rete ovarii (RO) is an epithelial structure that arises during development in close proximity to the ovary and persists throughout adulthood. However, the functional significance of the RO remains elusive, and it is absent from recent discussions of female reproductive anatomy. The RO comprises three regions: the intraovarian rete within the ovary, the extraovarian rete in the periovarian tissue, and the connecting rete linking the two. We hypothesize that the RO plays a pivotal role in ovarian homeostasis and responses to physiological changes. To begin to uncover the nature and function of RO cells, we conducted transcriptomic profiling of the RO. This study presents three datasets, and reports our analysis and quality control approaches for bulk, single-cell, and nucleus-level transcriptomics of the fetal and adult RO tissues using the Pax8-rtTA; Tre-H2B-GFP mouse line, where all RO regions express nuclear GFP. The integration and rigorous validation of these datasets will advance our understanding of the RO's roles in ovarian development, female maturation, and adult female fertility.

Intragraft regulatory T cells in the modern era: what can high-dimensional methods tell us about pathways to allograft acceptance?

Replacement of diseased organs with transplanted healthy donor ones remains the best and often only treatment option for end-stage organ disease. Immunosuppressants have decreased the incidence of acute rejection, but long-term survival remains limited. The broad action of current immunosuppressive drugs results in global immune impairment, increasing the risk of cancer and infections. Hence, achievement of allograft tolerance, in which graft function is maintained in the absence of global immunosuppression, has long been the aim of transplant clinicians and scientists. Regulatory T cells (Treg) are a specialized subset of immune cells that control a diverse array of immune responses, can prevent allograft rejection in animals, and have recently been explored in early phase clinical trials as an adoptive cellular therapy in transplant recipients. It has been established that allograft residency by Tregs can promote graft acceptance, but whether intragraft Treg functional diversification and spatial organization contribute to this process is largely unknown. In this review, we will explore what is known regarding the properties of intragraft Tregs during allograft acceptance and rejection. We will summarize recent advances in understanding Treg tissue residency through spatial, transcriptomic and high-dimensional cytometric methods in both animal and human studies. Our discussion will explore properties of intragraft Tregs in mediating operational tolerance to commonly transplanted solid organs. Finally, given recent developments in Treg cellular therapy, we will review emerging knowledge of whether and how these adoptively transferred cells enter allografts in humans. An understanding of the properties of intragraft Tregs will help lay the foundation for future therapies that will promote immune tolerance.

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

Prior studies have shown that pancreatic α-cells can transdifferentiate into β-cells, and that β-cells de-differentiate and are prone to acquire an α-cell phenotype in type 2 diabetes (T2D). However, the specific human α-cell and β-cell subtypes that are involved in α-to-β-cell and β-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-β 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-β-transition 1 (AB-Tr1), α-β-transition 2 (AB-Tr2), and α-β (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 β-cell pathways; 4) Trajectory inference analysis of extracted α- and β-cell clusters and RNA velocity/PAGA analysis suggests a bifurcate transition potential for AB towards both α- and β-cells. 5) Gene commonality analysis identifies ZNF385D, TRPM3, CASR, MEG3 and HDAC9 as signature for trajectories moving towards β-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-β-cells in vivo . 7) Analysis of scRNA-seq datasets from adult human T2D donor islets reveals a clear unidirectional transition from β-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 β-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.

Transcriptome analysis of the mouse fetal and adult rete ovarii and surrounding tissues

The rete ovarii (RO) is an epithelial structure that arises during fetal development in close proximity to the ovary and persists throughout adulthood in mice. However, the functional significance of the RO remains elusive, and it has been absent from recent discussions of female reproductive anatomy. The RO comprises three distinct regions: the intraovarian rete (IOR) within the ovary, the extraovarian rete (EOR) in the periovarian tissue, and the connecting rete (CR) linking the EOR and IOR. We hypothesize that the RO plays a pivotal role in maintaining ovarian homeostasis and responding to physiological changes. To uncover the nature and function of RO cells, we conducted transcriptome analysis, encompassing bulk, single-cell, and nucleus-level sequencing of both fetal and adult RO tissues using the Pax8-rtTA; Tre-H2B-GFP mouse line, where all RO regions express nuclear GFP. This study presents three datasets, which highlight RO-specific gene expression signatures and reveal differences in gene expression across the three RO regions during development and in adulthood. The integration and rigorous validation of these datasets will advance our understanding of the RO's roles in ovarian development, female maturation, and adult female fertility.

Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas

Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.

Inferring regulators of cell identity in the human adult pancreas

Cellular identity during development is under the control of transcription factors that form gene regulatory networks. However, the transcription factors and gene regulatory networks underlying cellular identity in the human adult pancreas remain largely unexplored. Here, we integrate multiple single-cell RNA-sequencing datasets of the human adult pancreas, totaling 7393 cells, and comprehensively reconstruct gene regulatory networks. We show that a network of 142 transcription factors forms distinct regulatory modules that characterize pancreatic cell types. We present evidence that our approach identifies regulators of cell identity and cell states in the human adult pancreas. We predict that HEYL, BHLHE41 and JUND are active in acinar, beta and alpha cells, respectively, and show that these proteins are present in the human adult pancreas as well as in human induced pluripotent stem cell (hiPSC)-derived islet cells. Using single-cell transcriptomics, we found that JUND represses beta cell genes in hiPSC-alpha cells. BHLHE41 depletion induced apoptosis in primary pancreatic islets. The comprehensive gene regulatory network atlas can be explored interactively online. We anticipate our analysis to be the starting point for a more sophisticated dissection of how transcription factors regulate cell identity and cell states in the human adult pancreas.

Spinal cord injury regulates circular RNA expression in axons

Introduction

Neurons transport mRNA and translational machinery to axons for local translation. After spinal cord injury (SCI), de novo translation is assumed to enable neurorepair. Knowledge of the identity of axonal mRNAs that participate in neurorepair after SCI is limited. We sought to identify and understand how axonal RNAs play a role in axonal regeneration.

Methods

We obtained preparations enriched in axonal mRNAs from control and SCI rats by digesting spinal cord tissue with cold-active protease (CAP). The digested samples were then centrifuged to obtain a supernatant that was used to identify mRNA expression. We identified differentially expressed genes (DEGS) after SCI and mapped them to various biological processes. We validated the DEGs by RT-qPCR and RNA-scope.

Results

The supernatant fraction was highly enriched for mRNA from axons. Using Gene Ontology, the second most significant pathway for all DEGs was axonogenesis. Among the DEGs was Rims2, which is predominately a circular RNA (circRNA) in the CNS. We show that Rims2 RNA within spinal cord axons is circular. We found an additional 200 putative circRNAs in the axonal-enriched fraction. Knockdown in primary rat cortical neurons of the RNA editing enzyme ADAR1, which inhibits formation of circRNAs, significantly increased axonal outgrowth and increased the expression of circRims2. Using Rims2 as a prototype we used Circular RNA Interactome to predict miRNAs that bind to circRims2 also bind to the 3'UTR of GAP-43, PTEN or CREB1, all known regulators of axonal outgrowth. Axonally-translated GAP-43 supports axonal elongation and we detect GAP-43 mRNA in the rat axons by RNAscope.

Discussion

By enriching for axonal RNA, we detect SCI induced DEGs, including circRNA such as Rims2. Ablation of ADAR1, the enzyme that regulates circRNA formation, promotes axonal outgrowth of cortical neurons. We developed a pathway model using Circular RNA Interactome that indicates that Rims2 through miRNAs can regulate the axonal translation GAP-43 to regulate axonal regeneration. We conclude that axonal regulatory pathways will play a role in neurorepair.

Single-cell sequencing analysis reveals development and differentiation trajectory of Schwann cells manipulated by M. leprae

BACKGROUND

M. leprae preferentially infects Schwann cells (SCs) in the peripheral nerves leading to nerve damage and irreversible disability. Knowledge of how M. leprae infects and interacts with host SCs is essential for understanding mechanisms of nerve damage and revealing potential new therapeutic strategies.

METHODOLOGY/PRINCIPAL FINDINGS

We performed a time-course single-cell sequencing analysis of SCs infected with M. leprae at different time points, further analyzed the heterogeneity of SCs, subpopulations associated with M. leprae infection, developmental trajectory of SCs and validated by Western blot or flow cytometry. Different subpopulations of SCs exhibiting distinct genetic features and functional enrichments were present. We observed two subpopulations associated with M. leprae infection, a stem cell-like cell subpopulation increased significantly at 24 h but declined by 72 h after M. leprae infection, and an adipocyte-like cell subpopulation, emerged at 72 h post-infection. The results were validated and confirmed that a stem cell-like cell subpopulation was in the early stage of differentiation and could differentiate into an adipocyte-like cell subpopulation.

CONCLUSIONS/SIGNIFICANCE

Our results present a systematic time-course analysis of SC heterogeneity after infection by M. leprae at single-cell resolution, provide valuable information to understand the critical biological processes underlying reprogramming and lipid metabolism during M. leprae infection of SCs, and increase understanding of the disease-causing mechanisms at play in leprosy patients as well as revealing potential new therapeutic strategies.