scholarly journals Characterisation of Ppy-lineage cells clarifies the functional heterogeneity of pancreatic beta cells in mice

Diabetologia ◽  
2021 ◽  
Author(s):  
Takahiro Fukaishi ◽  
Yuko Nakagawa ◽  
Ayako Fukunaka ◽  
Takashi Sato ◽  
Akemi Hara ◽  
...  
Keyword(s):  
Gene Expression ◽  
Beta Cell ◽  
Single Cell ◽  
Beta Cells ◽  
Pancreatic Beta Cells ◽  
Endocrine Cells ◽  
Expression Profiles ◽  
Data Availability ◽  
Valuable Insight ◽  
A Minor

Abstract Aims/hypothesis Pancreatic polypeptide (PP) cells, which secrete PP (encoded by the Ppy gene), are a minor population of pancreatic endocrine cells. Although it has been reported that the loss of beta cell identity might be associated with beta-to-PP cell-fate conversion, at present, little is known regarding the characteristics of Ppy-lineage cells. Methods We used Ppy-Cre driver mice and a PP-specific monoclonal antibody to investigate the association between Ppy-lineage cells and beta cells. The molecular profiles of endocrine cells were investigated by single-cell transcriptome analysis and the glucose responsiveness of beta cells was assessed by Ca2+ imaging. Diabetic conditions were experimentally induced in mice by either streptozotocin or diphtheria toxin. Results Ppy-lineage cells were found to contribute to the four major types of endocrine cells, including beta cells. Ppy-lineage beta cells are a minor subpopulation, accounting for 12–15% of total beta cells, and are mostly (81.2%) localised at the islet periphery. Unbiased single-cell analysis with a Ppy-lineage tracer demonstrated that beta cells are composed of seven clusters, which are categorised into two groups (i.e. Ppy-lineage and non-Ppy-lineage beta cells). These subpopulations of beta cells demonstrated distinct characteristics regarding their functionality and gene expression profiles. Ppy-lineage beta cells had a reduced glucose-stimulated Ca2+ signalling response and were increased in number in experimental diabetes models. Conclusions/interpretation Our results indicate that an unexpected degree of beta cell heterogeneity is defined by Ppy gene activation, providing valuable insight into the homeostatic regulation of pancreatic islets and future therapeutic strategies against diabetes. Data availability The single-cell RNA sequence (scRNA-seq) analysis datasets generated in this study have been deposited in the Gene Expression Omnibus (GEO) under the accession number GSE166164 (www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE166164). Graphical abstract

scholarly journals Glucose controls co-translation of structurally related mRNAs via the mTOR and eIF2 pathways in human pancreatic beta cells

2021 ◽  
Author(s):  
Manuel Bulfoni ◽  
Costas Bouyioukos ◽  
Albatoul Zakaria ◽  
Fabienne Nigon ◽  
Roberta Rapone ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Beta Cell ◽  
Beta Cells ◽  
Pancreatic Beta Cells ◽  
Gene Expression Regulation ◽  
Human Cells ◽  
Rodent Models ◽  
Polysome Profiling ◽  
Acute Increase

ABSTRACTPancreatic beta cell response to glucose is critical for the maintenance of normoglycemia. A strong transcriptional response was classically described in rodent models but, interestingly, not in human cells. In this study, we exposed human pancreatic beta cells to an increased concentration of glucose and analysed at a global level the mRNAs steady state levels and their translationalability. Polysome profiling analysis showed an early acute increase in protein synthesis and a specific translation regulation of more than 400 mRNAs, independently of their transcriptional regulation. We clustered the co-regulated mRNAs according to their behaviour in translation in response to glucose and discovered common structural and sequence mRNA features. Among them mTOR- and eIF2-sensitive elements have a predominant role to increase mostly the translation of mRNAs encoding for proteins of the translational machinery. Furthermore, we show that mTOR and eIF2α pathways are independently regulated in response to glucose, participating to a translational reshaping to adapt beta cell metabolism. The early acute increase in the translation machinery components prepare the beta cell for further protein demand due to glucose-mediated metabolism changes.AUTHOR SUMMARYAdaptation and response to glucose of pancreatic beta cells is critical for the maintenance of normoglycemia. Its deregulation is associated to Diabetic Mellitus (DM), a significant public health concern worldwide with an increased incidence of morbidity and mortality. Despite extensive research in rodent models, gene expression regulation in response to glucose remains largely unexplored in human cells. In our work, we have tackled this question by exposing human EndoC-BH1 cells to high glucose concentration. Using polysome profiling, the gold standard technique to analyse cellular translation activity, we observed a global protein synthesis increase, independent from transcription activity. Among the specific differentially translated mRNAs, we found transcripts coding for ribosomal proteins, allowing the cell machinery to be engaged in a metabolic response to glucose. Therefore, the regulation in response to glucose occurs mainly at the translational level in human cells, and not at the transcriptional level as described in the classically used rodent models.Furthermore, by comparing the features of the differentially translated mRNAs, and classifying them according to their translational response, we show that the early response to glucose occurs through the coupling of mRNA structure and sequence features impacting translation and regulation of specific signalling pathways. Collectively, our results support a new paradigm of gene expression regulation on the translation level in human beta cells.

scholarly journals Mitochondrial and insulin gene expression in single cells shape pancreatic beta cells’ population divergence

2020 ◽  
Author(s):  
H. Medini ◽  
T. Cohen ◽  
D. Mishmar
Keyword(s):  
Gene Expression ◽  
Beta Cell ◽  
Beta Cells ◽  
Pancreatic Beta Cells ◽  
Single Cells ◽  
Insulin Gene ◽  
Population Divergence ◽  
Cell Populations ◽  
Alpha Cells ◽  
Insulin Gene Expression

AbstractMitochondrial gene expression is pivotal to cell metabolism. Nevertheless, it is unknown whether it diverges within a given cell type. Here, we analysed single-cell RNA-seq experiments from ∼4600 human pancreatic alpha and beta cells, as well as ∼900 mouse beta cells. Cluster analysis revealed two distinct human beta cells populations, which diverged by mitochondrial (mtDNA) and nuclear DNA (nDNA)-encoded oxidative phosphorylation (OXPHOS) gene expression in healthy and diabetic individuals, and in newborn but not in adult mice. Insulin gene expression was elevated in beta cells with higher mtDNA gene expression in humans and in young mice. Such human beta cell populations also diverged in mt-RNA mutational repertoire, and in their selective signature, thus implying the existence of two previously overlooked distinct and conserved beta cell populations. While applying our approach to alpha cells, two sub-populations of cells were identified which diverged in mtDNA gene expression, yet these cellular populations did not consistently diverge in nDNA OXPHOS genes expression, nor did they correlate with the expression of glucagon, the hallmark of alpha cells. Thus, pancreatic beta cells within an individual are divided into distinct groups with unique metabolic-mitochondrial signature.

scholarly journals Single cell transcriptomics reveal trans-differentiation of pancreatic beta cells following inactivation of the TFIID subunit Taf4

2021 ◽  
Vol 12 (8) ◽  
Author(s):  
Thomas Kleiber ◽  
Guillaume Davidson ◽  
Gabrielle Mengus ◽  
Igor Martianov ◽  
Irwin Davidson
Keyword(s):  
Transcription Factors ◽  
Beta Cell ◽  
Single Cell ◽  
Beta Cells ◽  
Pancreatic Beta Cells ◽  
Cell Function ◽  
Insulin Signalling ◽  
Regulation Of Gene Expression ◽  
Chromatin Remodelling ◽  
Rna Seq

AbstractRegulation of gene expression involves a complex and dynamic dialogue between transcription factors, chromatin remodelling and modification complexes and the basal transcription machinery. To address the function of the Taf4 subunit of general transcription factor TFIID in the regulation of insulin signalling, it was inactivated in adult murine pancreatic beta cells. Taf4 inactivation impacted the expression of critical genes involved in beta-cell function leading to increased glycaemia, lowered plasma insulin levels and defective glucose-stimulated insulin secretion. One week after Taf4-loss, single-cell RNA-seq revealed cells with mixed beta cell, alpha and/or delta cell identities as well as a beta cell population trans-differentiating into alpha-like cells. Computational analysis of single-cell RNA-seq defines how known critical beta cell and alpha cell determinants may act in combination with additional transcription factors and the NuRF chromatin remodelling complex to promote beta cell trans-differentiation.

scholarly journals Analysis of Clonal Evolution/Heterogeneity of MDS By Simultaneous Detection of Both Mutation and Gene Expression By Single Cell Sequencing

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1800-1800
Author(s):  
Masahiro Marshall Nakagawa ◽  
Ryosaku Inagaki ◽  
Yasuhito Nannya ◽  
Lanying Zhao ◽  
Yutaka Kuroda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Profiles ◽  
Clonal Evolution ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Intratumor Heterogeneity ◽  
Single Cell Sequencing ◽  
Genome Wide ◽  
A Minor

Abstract Recent advances in single-cell sequencing (sc-Seq) technologies have enabled high-throughput transcriptome analysis in thousands of cells to understand the heterogeneity among cancer populations in terms of genome-wide gene expression. However, its application to the analysis of clonal evolution of cancer populations is largely limited by the lack of an efficient sc-Seq platform that allows for accurate detection of gene mutations at the same time with transcriptome analysis. The major challenge here is a frequent allele dropout of just two copies per single cell, which results in an inaccurate genotype assignment for many cells, preventing identification of relevant genotype-phenotype correlations. To overcome this, we developed a novel sc-Seq platform (scMutSeq) that allows for precise determination of both genotype and genome-wide gene expression simultaneously with negligible allele dropouts, on the basis of the Fluidigm C1 Single-Cell mRNA Seq HT system and applied it to the analysis of clonal evolution and intratumor heterogeneity of myelodysplastic syndromes (MDS) characterized by frequent clonal evolution to acute amyloid leukemia (AML). We first evaluated the performance of our plat form using an AML-derived cell line with heterozygous SF3B1K700E mutation, HNT-34, for which efficiency of the detection of both wild-type and mutant allele, together with global gene expression, was evaluated. Among 400 cells subjected to scMutSeq analysis, a total of 125 passed QC, in which cell viability was assessed in terms of expression of mitochondrial genes. Global gene expression and heterozygous SF3B1mutation were successfully detected in all the QC-confirmed cells with none of the cells showing the wild-type allele or homozygous SF3B1mutation, where evaluable transcript reads (unique molecular identifier >=1) were obtained for a median of 2,753 genes, designated as nGene. The performance was also tested for flow-sorted hematopoietic stem/progenitor cells (HSPCs) (Lin−CD34+) from an MDS patient positive for the SF3B1K700E mutation. Gene expression was successfully analyzed all the QC-confirmed cells (n=81) with a median nGene of 1,953. No substantial allele dropouts were suspected, because none of the cells genotyped had homozygous SF3B1mutation. We then applied scMutSeq to the analysis of TP53-mutated AML/MDS with complex karyotype, including del(5q) and del(7q), for which longitudinal samples were obtained for the assessment of clonal evolution. scMutSeq successfully analyzed the mutation status of TP53and global gene expression profiles at a single-cell level, where copy number abnormalities were also evaluated on the basis of gene expression. We identified two discrete clones in the HSPC fraction, carrying both del(5q) and del(7q) and del(5q) alone, respectively, even though the analysis of bulk DNA had failed to detect the latter clone, indicating that a minor clone having a distinct genotype came under detection with scMutSeq. Moreover, the HSPCs with both del(5q) and del(7q) showed aberrant expression of erythroid and megakaryocytic genes, increased expression of inflammatory signals and decreased expression of cell cycle-related genes, exhibiting a clear genotype phenotype correlation. Subsequent analysis of samples at later time points further disclosed evolution of clones having discrete del(5q) deletions and expression, revealing a complexity of clonal evolution in MDS. Next, to investigate the early process of MDS development, we analyzed clonal hematopoiesis found in a minor fraction (1.2-12%) of bone marrow samples from three elder individuals having hip replacement surgery, in which DNMT3A(n=1) (R882H) and TET2(n=2) (D905fs and Q1540fs) mutations had been detected by ddPCR or targeted deep sequencing, respectively. scMutSeq analysis of the HSPCs from these individuals revealed that mutant HSPCs showed distinct gene expression profiles, depending on the type of CHIP mutations. To summarize, our single-cell sequencing platform enables to detect both genetic and transcriptional heterogeneities, providing a powerful clue to understand clonal evolution and intratumor heterogeneity of MDS. Disclosures Nakagawa: Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Inagaki:Sumitomo Dainippon Pharma Co., Ltd.: Employment. Yoda:Chordia Therapeutics Inc.: Research Funding.

scholarly journals DNA Methylation Patterning and the Regulation of Beta Cell Homeostasis

2021 ◽  
Vol 12 ◽  
Author(s):  
Nazia Parveen ◽  
Sangeeta Dhawan
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Beta Cell ◽  
Beta Cells ◽  
Pancreatic Beta Cells ◽  
Expression Patterns ◽  
Cell Phenotype ◽  
Gene Expression Patterns ◽  
Postnatal Life ◽  
Methylation Patterns

Pancreatic beta cells play a central role in regulating glucose homeostasis by secreting the hormone insulin. Failure of beta cells due to reduced function and mass and the resulting insulin insufficiency can drive the dysregulation of glycemic control, causing diabetes. Epigenetic regulation by DNA methylation is central to shaping the gene expression patterns that define the fully functional beta cell phenotype and regulate beta cell growth. Establishment of stage-specific DNA methylation guides beta cell differentiation during fetal development, while faithful restoration of these signatures during DNA replication ensures the maintenance of beta cell identity and function in postnatal life. Lineage-specific transcription factor networks interact with methylated DNA at specific genomic regions to enhance the regulatory specificity and ensure the stability of gene expression patterns. Recent genome-wide DNA methylation profiling studies comparing islets from diabetic and non-diabetic human subjects demonstrate the perturbation of beta cell DNA methylation patterns, corresponding to the dysregulation of gene expression associated with mature beta cell state in diabetes. This article will discuss the molecular underpinnings of shaping the islet DNA methylation landscape, its mechanistic role in the specification and maintenance of the functional beta cell phenotype, and its dysregulation in diabetes. We will also review recent advances in utilizing beta cell specific DNA methylation patterns for the development of biomarkers for diabetes, and targeting DNA methylation to develop translational approaches for supplementing the functional beta cell mass deficit in diabetes.

scholarly journals Age-related islet inflammation marks the proliferative decline of pancreatic beta-cells in zebrafish

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Sharan Janjuha ◽  
Sumeet Pal Singh ◽  
Anastasia Tsakmaki ◽  
S Neda Mousavy Gharavy ◽  
Priyanka Murawala ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Beta Cell ◽  
Beta Cells ◽  
Pancreatic Beta Cells ◽  
Beta Cell Proliferation ◽  
Related Gene ◽  
Age Related ◽  
Islet Inflammation ◽  
Low Activity

The pancreatic islet, a cellular community harboring the insulin-producing beta-cells, is known to undergo age-related alterations. However, only a handful of signals associated with aging have been identified. By comparing beta-cells from younger and older zebrafish, here we show that the aging islets exhibit signs of chronic inflammation. These include recruitment of tnfα-expressing macrophages and the activation of NF-kB signaling in beta-cells. Using a transgenic reporter, we show that NF-kB activity is undetectable in juvenile beta-cells, whereas cells from older fish exhibit heterogeneous NF-kB activity. We link this heterogeneity to differences in gene expression and proliferation. Beta-cells with high NF-kB signaling proliferate significantly less compared to their neighbors with low activity. The NF-kB signalinghi cells also exhibit premature upregulation of socs2, an age-related gene that inhibits beta-cell proliferation. Together, our results show that NF-kB activity marks the asynchronous decline in beta-cell proliferation with advancing age.

4 Molecularly guided multiplexed digital spatial analysis reveals differential gene expression profiles in the WNT-β-catenin pathway between melanoma and prostate tumors

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A4-A4
Author(s):  
Anushka Dikshit ◽  
Dan Zollinger ◽  
Karen Nguyen ◽  
Jill McKay-Fleisch ◽  
Kit Fuhrman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Single Molecule ◽  
Spatial Information ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fluorescence Assay ◽  
Differentially Expressed ◽  
Tumor Type ◽  
Prostate Tumors

BackgroundThe canonical WNT-β-catenin signaling pathway is vital for development and tissue homeostasis but becomes strongly tumorigenic when dysregulated. and alter the transcriptional signature of a cell to promote malignant transformation. However, thorough characterization of these transcriptomic signatures has been challenging because traditional methods lack either spatial information, multiplexing, or sensitivity/specificity. To overcome these challenges, we developed a novel workflow combining the single molecule and single cell visualization capabilities of the RNAscope in situ hybridization (ISH) assay with the highly multiplexed spatial profiling capabilities of the GeoMx™ Digital Spatial Profiler (DSP) RNA assays. Using these methods, we sought to spatially profile and compare gene expression signatures of tumor niches with high and low CTNNB1 expression.MethodsAfter screening 120 tumor cores from multiple tumors for CTNNB1 expression by the RNAscope assay, we identified melanoma as the tumor type with the highest CTNNB1 expression while prostate tumors had the lowest expression. Using the RNAscope Multiplex Fluorescence assay we selected regions of high CTNNB1 expression within 3 melanoma tumors as well as regions with low CTNNB1 expression within 3 prostate tumors. These selected regions of interest (ROIs) were then transcriptionally profiled using the GeoMx DSP RNA assay for a set of 78 genes relevant in immuno-oncology. Target genes that were differentially expressed were further visualized and spatially assessed using the RNAscope Multiplex Fluorescence assay to confirm GeoMx DSP data with single cell resolution.ResultsThe GeoMx DSP analysis comparing the melanoma and prostate tumors revealed that they had significantly different gene expression profiles and many of these genes showed concordance with CTNNB1 expression. Furthermore, immunoregulatory targets such as ICOSLG, CTLA4, PDCD1 and ARG1, also demonstrated significant correlation with CTNNB1 expression. On validating selected targets using the RNAscope assay, we could distinctly visualize that they were not only highly expressed in melanoma compared to the prostate tumor, but their expression levels changed proportionally to that of CTNNB1 within the same tumors suggesting that these differentially expressed genes may be regulated by the WNT-β-catenin pathway.ConclusionsIn summary, by combining the RNAscope ISH assay and the GeoMx DSP RNA assay into one joint workflow we transcriptionally profiled regions of high and low CTNNB1 expression within melanoma and prostate tumors and identified genes potentially regulated by the WNT- β-catenin pathway. This novel workflow can be fully automated and is well suited for interrogating the tumor and stroma and their interactions.GeoMx Assays are for RESEARCH ONLY, not for diagnostics.

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