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Transcriptomic profiling of pancreatic alpha, beta and delta cell populations identifies delta cells as a principal target for ghrelin in mouse islets

View Article: PubMed Central - PubMed

ABSTRACT

Aims/hypothesis: Intra-islet and gut–islet crosstalk are critical in orchestrating basal and postprandial metabolism. The aim of this study was to identify regulatory proteins and receptors underlying somatostatin secretion though the use of transcriptomic comparison of purified murine alpha, beta and delta cells.

Methods: Sst-Cre mice crossed with fluorescent reporters were used to identify delta cells, while Glu-Venus (with Venus reported under the control of the Glu [also known as Gcg] promoter) mice were used to identify alpha and beta cells. Alpha, beta and delta cells were purified using flow cytometry and analysed by RNA sequencing. The role of the ghrelin receptor was validated by imaging delta cell calcium concentrations using islets with delta cell restricted expression of the calcium reporter GCaMP3, and in perfused mouse pancreases.

Results: A database was constructed of all genes expressed in alpha, beta and delta cells. The gene encoding the ghrelin receptor, Ghsr, was highlighted as being highly expressed and enriched in delta cells. Activation of the ghrelin receptor raised cytosolic calcium levels in primary pancreatic delta cells and enhanced somatostatin secretion in perfused pancreases, correlating with a decrease in insulin and glucagon release. The inhibition of insulin secretion by ghrelin was prevented by somatostatin receptor antagonism.

Conclusions/interpretation: Our transcriptomic database of genes expressed in the principal islet cell populations will facilitate rational drug design to target specific islet cell types. The present study indicates that ghrelin acts specifically on delta cells within pancreatic islets to elicit somatostatin secretion, which in turn inhibits insulin and glucagon release. This highlights a potential role for ghrelin in the control of glucose metabolism.

Electronic supplementary material: The online version of this article (doi:10.1007/s00125-016-4033-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

No MeSH data available.


Transcriptomic profiling of pancreatic alpha, beta and delta cells. RNA was extracted from purified populations of alpha, beta and delta cells, and converted to cDNA or prepped for RNA sequencing. (a) Populations of alpha (black bars), beta (grey bars) and delta (white bars) cells were checked for Ins, Gcg and Sst enrichment, respectively, using qPCR analysis. Data are presented as the geometric mean, with error bars (SEM) calculated from log2 data. Each column represents the average expression from three separate samples. Significance comparisons were calculated by one-way ANOVA with Bonferroni post hoc comparison; ***p < 0.001. (b) RNA from five alpha cell samples, four beta cell samples and six delta cell samples was sequenced using SE50 sequencing. Differential gene expression was determined using edgeR, and a principle component analysis plot was constructed using a false discovery rate of 5% and a sensitivity threshold of FPKM values >1. (c) Pie chart showing the cellular distribution of genes differentially expressed between islet cell types. (d) Pie chart showing the distribution of differentially expressed genes found at the plasma membrane. (e) Heatmap showing the top 40 most differentially expressed genes found at the plasma membrane. Data are presented as log2 FPKM
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Fig1: Transcriptomic profiling of pancreatic alpha, beta and delta cells. RNA was extracted from purified populations of alpha, beta and delta cells, and converted to cDNA or prepped for RNA sequencing. (a) Populations of alpha (black bars), beta (grey bars) and delta (white bars) cells were checked for Ins, Gcg and Sst enrichment, respectively, using qPCR analysis. Data are presented as the geometric mean, with error bars (SEM) calculated from log2 data. Each column represents the average expression from three separate samples. Significance comparisons were calculated by one-way ANOVA with Bonferroni post hoc comparison; ***p < 0.001. (b) RNA from five alpha cell samples, four beta cell samples and six delta cell samples was sequenced using SE50 sequencing. Differential gene expression was determined using edgeR, and a principle component analysis plot was constructed using a false discovery rate of 5% and a sensitivity threshold of FPKM values >1. (c) Pie chart showing the cellular distribution of genes differentially expressed between islet cell types. (d) Pie chart showing the distribution of differentially expressed genes found at the plasma membrane. (e) Heatmap showing the top 40 most differentially expressed genes found at the plasma membrane. Data are presented as log2 FPKM

Mentions: We separated populations of alpha and beta cells via FACS from Glu-Venus mice and populations of delta cells from Sst-Cre/Rosa26EYFP mice. Quantitative PCR (qPCR) analysis of the relative expression of Ins, Gcg and Sst in cDNA isolated from these purified populations of islet cells confirmed the enrichment of Ins in beta cells, Gcg in alpha cells and Sst in delta cells (Fig. 1a).Fig. 1


Transcriptomic profiling of pancreatic alpha, beta and delta cell populations identifies delta cells as a principal target for ghrelin in mouse islets
Transcriptomic profiling of pancreatic alpha, beta and delta cells. RNA was extracted from purified populations of alpha, beta and delta cells, and converted to cDNA or prepped for RNA sequencing. (a) Populations of alpha (black bars), beta (grey bars) and delta (white bars) cells were checked for Ins, Gcg and Sst enrichment, respectively, using qPCR analysis. Data are presented as the geometric mean, with error bars (SEM) calculated from log2 data. Each column represents the average expression from three separate samples. Significance comparisons were calculated by one-way ANOVA with Bonferroni post hoc comparison; ***p < 0.001. (b) RNA from five alpha cell samples, four beta cell samples and six delta cell samples was sequenced using SE50 sequencing. Differential gene expression was determined using edgeR, and a principle component analysis plot was constructed using a false discovery rate of 5% and a sensitivity threshold of FPKM values >1. (c) Pie chart showing the cellular distribution of genes differentially expressed between islet cell types. (d) Pie chart showing the distribution of differentially expressed genes found at the plasma membrane. (e) Heatmap showing the top 40 most differentially expressed genes found at the plasma membrane. Data are presented as log2 FPKM
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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Fig1: Transcriptomic profiling of pancreatic alpha, beta and delta cells. RNA was extracted from purified populations of alpha, beta and delta cells, and converted to cDNA or prepped for RNA sequencing. (a) Populations of alpha (black bars), beta (grey bars) and delta (white bars) cells were checked for Ins, Gcg and Sst enrichment, respectively, using qPCR analysis. Data are presented as the geometric mean, with error bars (SEM) calculated from log2 data. Each column represents the average expression from three separate samples. Significance comparisons were calculated by one-way ANOVA with Bonferroni post hoc comparison; ***p < 0.001. (b) RNA from five alpha cell samples, four beta cell samples and six delta cell samples was sequenced using SE50 sequencing. Differential gene expression was determined using edgeR, and a principle component analysis plot was constructed using a false discovery rate of 5% and a sensitivity threshold of FPKM values >1. (c) Pie chart showing the cellular distribution of genes differentially expressed between islet cell types. (d) Pie chart showing the distribution of differentially expressed genes found at the plasma membrane. (e) Heatmap showing the top 40 most differentially expressed genes found at the plasma membrane. Data are presented as log2 FPKM
Mentions: We separated populations of alpha and beta cells via FACS from Glu-Venus mice and populations of delta cells from Sst-Cre/Rosa26EYFP mice. Quantitative PCR (qPCR) analysis of the relative expression of Ins, Gcg and Sst in cDNA isolated from these purified populations of islet cells confirmed the enrichment of Ins in beta cells, Gcg in alpha cells and Sst in delta cells (Fig. 1a).Fig. 1

View Article: PubMed Central - PubMed

ABSTRACT

Aims/hypothesis: Intra-islet and gut&ndash;islet crosstalk are critical in orchestrating basal and postprandial metabolism. The aim of this study was to identify regulatory proteins and receptors underlying somatostatin secretion though the use of transcriptomic comparison of purified murine alpha, beta and delta cells.

Methods: Sst-Cre mice crossed with fluorescent reporters were used to identify delta cells, while Glu-Venus (with Venus reported under the control of the Glu [also known as Gcg] promoter) mice were used to identify alpha and beta cells. Alpha, beta and delta cells were purified using flow cytometry and analysed by RNA sequencing. The role of the ghrelin receptor was validated by imaging delta cell calcium concentrations using islets with delta cell restricted expression of the calcium reporter GCaMP3, and in perfused mouse pancreases.

Results: A database was constructed of all genes expressed in alpha, beta and delta cells. The gene encoding the ghrelin receptor, Ghsr, was highlighted as being highly expressed and enriched in delta cells. Activation of the ghrelin receptor raised cytosolic calcium levels in primary pancreatic delta cells and enhanced somatostatin secretion in perfused pancreases, correlating with a decrease in insulin and glucagon release. The inhibition of insulin secretion by ghrelin was prevented by somatostatin receptor antagonism.

Conclusions/interpretation: Our transcriptomic database of genes expressed in the principal islet cell populations will facilitate rational drug design to target specific islet cell types. The present study indicates that ghrelin acts specifically on delta cells within pancreatic islets to elicit somatostatin secretion, which in turn inhibits insulin and glucagon release. This highlights a potential role for ghrelin in the control of glucose metabolism.

Electronic supplementary material: The online version of this article (doi:10.1007/s00125-016-4033-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

No MeSH data available.