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Probes for INS

ACD can configure probes for the various manual and automated assays for INS for RNAscope Assay, or for Basescope Assay compatible for your species of interest.

  • Probes for INS (0)
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  • Publications (9) Apply Publications filter
Human Beta Cells Produce and Release Serotonin to Inhibit Glucagon Secretion from Alpha Cells.

Cell Rep.

2016 Dec 20

Almaça J, Molina J, Menegaz D, Pronin AN, Tamayo A, Slepak V, Berggren PO, Caicedo A.
PMID: 28009296 | DOI: 10.1016/j.celrep.2016.11.072

In the pancreatic islet, serotonin is an autocrine signal increasing beta cell mass during metabolic challenges such as those associated with pregnancy or high-fat diet. It is still unclear whether serotonin is relevant for regular islet physiology and hormone secretion. Here, we show that human beta cells produce and secrete serotonin when stimulated with increases in glucose concentration. Serotonin secretion from beta cells decreases cyclic AMP (cAMP) levels in neighboring alpha cells via 5-HT1F receptors and inhibits glucagon secretion. Without serotonergic input, alpha cells lose their ability to regulate glucagon secretion in response to changes in glucose concentration, suggesting that diminished serotonergic control of alpha cells can cause glucose blindness and the uncontrolled glucagon secretion associated with diabetes. Supporting this model, pharmacological activation of 5-HT1F receptors reduces glucagon secretion and has hypoglycemic effects in diabetic mice. Thus, modulation of serotonin signaling in the islet represents a drug intervention opportunity.

Mice harboring the human SLC30A8 R138X loss-of-function mutation have increased insulin secretory capacity.

Proc Natl Acad Sci U S A.

2018 Jul 23

Kleiner S, Gomez D, Megra B, Na E, Bhavsar R, Cavino K, Xin Y, Rojas J, Dominguez-Gutierrez G, Zambrowicz B, Carrat G, Chabosseau P, Hu M, Murphy AJ, Yancopoulos GD, Rutter GA, Gromada J.
PMID: 30038024 | DOI: 10.1073/pnas.1721418115

SLC30A8 encodes a zinc transporter that is primarily expressed in the pancreatic islets of Langerhans. In β-cells it transports zinc into insulin-containing secretory granules. Loss-of-function (LOF) mutations in SLC30A8 protect against type 2 diabetes in humans. In this study, we generated a knockin mouse model carrying one of the most common human LOF mutations for SLC30A8, R138X. The R138X mice had normal body weight, glucose tolerance, and pancreatic β-cell mass. Interestingly, in hyperglycemic conditions induced by the insulin receptor antagonist S961, the R138X mice showed a 50% increase in insulin secretion. This effect was not associated with enhanced β-cell proliferation or mass. Our data suggest that the SLC30A8 R138X LOF mutation may exert beneficial effects on glucose metabolism by increasing the capacity of β-cells to secrete insulin under hyperglycemic conditions.

Calcium-dependent transcriptional changes in human pancreatic islet cells reveal functional diversity in islet cell subtypes

Diabetologia

2022 May 26

Yoon, JS;Sasaki, S;Velghe, J;Lee, MYY;Winata, H;Nian, C;Lynn, FC;
PMID: 35616696 | DOI: 10.1007/s00125-022-05718-1

Pancreatic islets depend on cytosolic calcium (Ca2+) to trigger the secretion of glucoregulatory hormones and trigger transcriptional regulation of genes important for islet response to stimuli. To date, there has not been an attempt to profile Ca2+-regulated gene expression in all islet cell types. Our aim was to construct a large single-cell transcriptomic dataset from human islets exposed to conditions that would acutely induce or inhibit intracellular Ca2+ signalling, while preserving biological heterogeneity.We exposed intact human islets from three donors to the following conditions: (1) 2.8 mmol/l glucose; (2) 16 mmol/l glucose and 40 mmol/l KCl to maximally stimulate Ca2+ signalling; and (3) 16 mmol/l glucose, 40 mmol/l KCl and 5 mmol/l EGTA (Ca2+ chelator) to inhibit Ca2+ signalling, for 1 h. We sequenced 68,650 cells from all islet cell types, and further subsetted the cells to form an endocrine cell-specific dataset of 59,373 cells expressing INS, GCG, SST or PPY. We compared transcriptomes across conditions to determine the differentially expressed Ca2+-regulated genes in each endocrine cell type, and in each endocrine cell subcluster of alpha and beta cells.Based on the number of Ca2+-regulated genes, we found that each alpha and beta cell cluster had a different magnitude of Ca2+ response. We also showed that polyhormonal clusters expressing both INS and GCG, or both INS and SST, are defined by Ca2+-regulated genes specific to each cluster. Finally, we identified the gene PCDH7 from the beta cell clusters that had the highest number of Ca2+-regulated genes, and showed that cells expressing cell surface PCDH7 protein have enhanced glucose-stimulated insulin secretory function.Here we use our large-scale, multi-condition, single-cell dataset to show that human islets have cell-type-specific Ca2+-regulated gene expression profiles, some of them specific to subpopulations. In our dataset, we identify PCDH7 as a novel marker of beta cells having an increased number of Ca2+-regulated genes and enhanced insulin secretory function.A searchable and user-friendly format of the data in this study, specifically designed for rapid mining of single-cell RNA sequencing data, is available at https://lynnlab.shinyapps.io/Human_Islet_Atlas/ . The raw data files are available at NCBI Gene Expression Omnibus (GSE196715).
RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes

Cell Metab.

2016 Sep 09

Xin Y, Kim J, Okamoto H, Ni M, Wei Y, Adler C, Murphy AJ, Yancopoulos GD, Lin C, Gromada J.
PMID: 27667665 | DOI: 10.1016/j.cmet.2016.08.018

Pancreatic islet cells are critical for maintaining normal blood glucose levels, and their malfunction underlies diabetes development and progression. We used single-cell RNA sequencing to determine the transcriptomes of 1,492 human pancreatic α, β, δ, and PP cells from non-diabetic and type 2 diabetes organ donors. We identified cell-type-specific genes and pathways as well as 245 genes with disturbed expression in type 2 diabetes. Importantly, 92% of the genes have not previously been associated with islet cell function or growth. Comparison of gene profiles in mouse and human α and β cells revealed species-specific expression. All data are available for online browsing and download and will hopefully serve as a resource for the islet research community.

Use of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells.

Proc Natl Acad Sci U S A.

2016 Mar 07

Xin Y, Kim J, Ni M, Wei Y, Okamoto H, Lee J, Adler C, Cavino K, Murphy AJ, Yancopoulos GD, Lin HC, Gromada J.
PMID: 26951663 | DOI: -

This study provides an assessment of the Fluidigm C1 platform for RNA sequencing of single mouse pancreatic islet cells. The system combines microfluidic technology and nanoliter-scale reactions. We sequenced 622 cells, allowing identification of 341 islet cells with high-quality gene expression profiles. The cells clustered into populations of α-cells (5%), β-cells (92%), δ-cells (1%), and pancreatic polypeptide cells (2%). We identified cell-type-specific transcription factors and pathways primarily involved in nutrient sensing and oxidation and cell signaling. Unexpectedly, 281 cells had to be removed from the analysis due to low viability, low sequencing quality, or contamination resulting in the detection of more than one islet hormone. Collectively, we provide a resource for identification of high-quality gene expression datasets to help expand insights into genes and pathways characterizing islet cell types. We reveal limitations in the C1 Fluidigm cell capture process resulting in contaminated cells with altered gene expression patterns. This calls for caution when interpreting single-cell transcriptomics data using the C1 Fluidigm system.

A single-cell survey of the small intestinal epithelium.

Nature.

2017 Nov 16

Haber AL, Biton M, Rogel N, Herbst RH, Shekhar K, Smillie C, Burgin G, Delorey TM, Howitt MR, Katz Y, Tirosh I, Beyaz S, Dionne D, Zhang M, Raychowdhury R, Garrett WS, Rozenblatt-Rosen O, Shi HN, Yilmaz O, Xavier RJ, Regev A.
PMID: 29144463 | DOI: 10.1038/nature24489

Intestinal epithelial cells absorb nutrients, respond to microbes, function as a barrier and help to coordinate immune responses. Here we report profiling of 53,193 individual epithelial cells from the small intestine and organoids of mice, which enabled the identification and characterization of previously unknown subtypes of intestinal epithelial cell and their gene signatures. We found unexpected diversity in hormone-secreting enteroendocrine cells and constructed the taxonomy of newly identified subtypes, and distinguished between two subtypes of tuft cell, one of which expresses the epithelial cytokine Tslp and the pan-immune marker CD45, which was not previously associated with non-haematopoietic cells. We also characterized the ways in which cell-intrinsic states and the proportions of different cell types respond to bacterial and helminth infections: Salmonella infection caused an increase in the abundance of Paneth cells and enterocytes, and broad activation of an antimicrobial program; Heligmosomoides polygyrus caused an increase in the abundance of goblet and tuft cells. Our survey highlights previously unidentified markers and programs, associates sensory molecules with cell types, and uncovers principles of gut homeostasis and response to pathogens.

Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes.

Cell Metab.

2016 Oct 11

Segerstolpe Å, Palasantza A, Eliasson P, Andersson EM, Andréasson AC, Sun X, Picelli S, Sabirsh A, Clausen M, Bjursell MK, Smith DM, Kasper M, Ämmälä C, Sandberg R.
PMID: 27667667 | DOI: 10.1016/j.cmet.2016.08.020

Hormone-secreting cells within pancreatic islets of Langerhans play important roles in metabolic homeostasis and disease. However, their transcriptional characterization is still incomplete. Here, we sequenced the transcriptomes of thousands of human islet cells from healthy and type 2 diabetic donors. We could define specific genetic programs for each individual endocrine and exocrine cell type, even for rare δ, γ, ε, and stellate cells, and revealed subpopulations of α, β, and acinar cells. Intriguingly, δ cells expressed several important receptors, indicating an unrecognized importance of these cells in integrating paracrine and systemic metabolic signals. Genes previously associated with obesity or diabetes were found to correlate with BMI. Finally, comparing healthy and T2D transcriptomes in a cell-type resolved manner uncovered candidates for future functional studies. Altogether, our analyses demonstrate the utility of the generated single-cell gene expression resource.

Lineage dynamics of murine pancreatic development at single-cell resolution.

Nat Commun.

2018 Sep 25

Byrnes LE, Wong DM, Subramaniam M, Meyer NP, Gilchrist CL, Knox SM, Tward AD, Ye CJ, Sneddon JB.
PMID: 30254276 | DOI: 10.1038/s41467-018-06176-3

Organogenesis requires the complex interactions of multiple cell lineages that coordinate their expansion, differentiation, and maturation over time. Here, we profile the cell types within the epithelial and mesenchymal compartments of the murine pancreas across developmental time using a combination of single-cell RNA sequencing, immunofluorescence, in situ hybridization, and genetic lineage tracing. We identify previously underappreciated cellular heterogeneity of the developing mesenchyme and reconstruct potential lineage relationships among the pancreatic mesothelium and mesenchymal cell types. Within the epithelium, we find a previously undescribed endocrine progenitor population, as well as an analogous population in both human fetal tissue and human embryonic stem cells differentiating toward a pancreatic beta cell fate. Further, we identify candidate transcriptional regulators along the differentiation trajectory of this population toward the alpha or beta cell lineages. This work establishes a roadmap of pancreatic development and demonstrates the broad utility of this approach for understanding lineage dynamics in developing organs.

The Microbiota-Produced N-Formyl Peptide fMLF Promotes Obesity-Induced Glucose Intolerance.

Diabetes

2019 Apr 22

Wollam J, Riopel M, Xu YJ, Johnson AMF, Ofrecio JM, Ying W, El Ouarrat D, Chan LS, Han AW, Mahmood NA, Ryan CN, Lee YS, Watrous JD, Chordia MD, Pan D, Jain M, Olefsky JM.
PMID: 31010956 | DOI: 10.2337/db18-1307

The composition of the gastrointestinal (GI) microbiota and associated metabolites changes dramatically with diet and the development of obesity. Although many correlations have been described, specific mechanistic links between these changes and glucose homeostasis remain to be defined. Here we show that blood and intestinal levels of the microbiota-produced N-formyl peptide, formyl-methionyl-leucyl-phenylalanine (fMLF), are elevated in high fat diet (HFD)-induced obese mice. Genetic or pharmacological inhibition of the N-formyl peptide receptor Fpr1 leads to increased insulin levels and improved glucose tolerance, dependent upon glucagon-like peptide-1 (GLP-1). Obese Fpr1-knockout (Fpr1-KO) mice also display an altered microbiome, exemplifying the dynamic relationship between host metabolism and microbiota. Overall, we describe a new mechanism by which the gut microbiota can modulate glucose metabolism, providing a potential approach for treatment of metabolic disease.

X
Description
sense
Example: Hs-LAG3-sense
Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe.
Intron#
Example: Mm-Htt-intron2
Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection
Pool/Pan
Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G)
A mixture of multiple probe sets targeting multiple genes or transcripts
No-XSp
Example: Hs-PDGFB-No-XMm
Does not cross detect with the species (Sp)
XSp
Example: Rn-Pde9a-XMm
designed to cross detect with the species (Sp)
O#
Example: Mm-Islr-O1
Alternative design targeting different regions of the same transcript or isoforms
CDS
Example: Hs-SLC31A-CDS
Probe targets the protein-coding sequence only
EnEmProbe targets exons n and m
En-EmProbe targets region from exon n to exon m
Retired Nomenclature
tvn
Example: Hs-LEPR-tv1
Designed to target transcript variant n
ORF
Example: Hs-ACVRL1-ORF
Probe targets open reading frame
UTR
Example: Hs-HTT-UTR-C3
Probe targets the untranslated region (non-protein-coding region) only
5UTR
Example: Hs-GNRHR-5UTR
Probe targets the 5' untranslated region only
3UTR
Example: Rn-Npy1r-3UTR
Probe targets the 3' untranslated region only
Pan
Example: Pool
A mixture of multiple probe sets targeting multiple genes or transcripts

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