Single‐cell transcriptomes reveal characteristic features of human pancreatic islet cell types

Li, Jin; Klughammer, Johanna; Farlik, Matthias; Penz, Thomas; Spittler, Andreas; Barbieux, Charlotte; Berishvili, Ekaterine; Bock, Christoph; Kubicek, Stefan

doi:10.15252/embr.201540946

Cited by 222 publications

(216 citation statements)

References 34 publications

Supporting

Mentioning

201

Contrasting

Order By: Relevance

“…S1). The expression of ATF5 in β cells of the murine pancreatic islet is consistent with several single-cell transcriptomic studies that identified Atf5 transcript in murine and human β cells (27)(28)(29).…”

Section: Resultssupporting

confidence: 87%

ATF5 regulates β-cell survival during stress

Juliana

Yang

Rozo

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

The stress response and cell survival are necessary for normal pancreatic β-cell function, glucose homeostasis, and prevention of diabetes. The homeodomain transcription factor and human diabetes gene pancreas/duodenum homeobox protein 1 (Pdx1) regulates β-cell survival and endoplasmic reticulum stress susceptibility, in part through direct regulation of activating transcription factor 4 (Atf4). Here we show that Atf5, a close but less-studied relative of Atf4, is also a target of Pdx1 and is critical for β-cell survival under stress conditions. Pdx1 deficiency led to decreased Atf5 transcript, and primary islet ChIP-sequencing localized PDX1 to the Atf5 promoter, implicating Atf5 as a PDX1 target. Atf5 expression was stress inducible and enriched in β cells. Importantly, Atf5 deficiency decreased survival under stress conditions. Loss-of-function and chromatin occupancy experiments positioned Atf5 downstream of and parallel to Atf4 in the regulation of eIF4E-binding protein 1 (4ebp1), a mammalian target of rapamycin (mTOR) pathway component that inhibits protein translation. Accordingly, Atf5 deficiency attenuated stress suppression of global translation, likely enhancing the susceptibility of β cells to stress-induced apoptosis. Thus, we identify ATF5 as a member of the transcriptional network governing pancreatic β-cell survival during stress.educed pancreatic β-cell number and function characterize all forms of diabetes. Insulin-secreting β cells are notoriously susceptible to stress, including endoplasmic reticulum (ER), cytokine, and oxidative stress (1-4). Thus, understanding apoptotic cell-fate decisions during stress could provide new targets that could be exploited for the prevention or amelioration of diabetes.In secretory cells such as the β cell, the unfolded protein response (UPR) and regulation of translation, particularly in response to stress, are key factors in maintaining cellular homeostasis, as clearly demonstrated in mouse models with deficiencies of critical regulators such as protein kinase R-like ER kinase (PERK) and EIF2α (5-7). In humans, PERK mutation causes Wolcott-Rallison syndrome, a rare autosomal recessive disorder characterized by permanent neonatal diabetes (8, 9). Downstream of PERK, the basic leucine zipper (bZIP) transcription factor activating transcription factor 4 (ATF4) regulates the expression of 4ebp1, a member of the eukaryotic translation initiation factor 4E (eIF4E)-binding protein family (4EBPs). 4EBP1 is the most abundant mammalian isoform in the pancreas (10) and functions as an inhibitor of translation initiation by binding the capbinding protein eIF4E, thereby preventing formation of the eIF4F translational initiation complex (11,12). Expression of 4EBP1 is induced by stress, and 4ebp1 deficiency results in deregulated translational control and increased susceptibility to ER stressmediated apoptosis in β cells (13).We previously demonstrated that the homeodomain transcription factor and human diabetes gene pancreas/duodenum homeobox protein 1 (Pdx1) regulates p...

show abstract

Section: Resultssupporting

confidence: 87%

ATF5 regulates β-cell survival during stress

Juliana

Yang

Rozo

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

show abstract

“…Five islet endocrine cell types have been assigned based on exclusive and robust expression of the peptide hormone genes INS (beta), GCG (alpha), SST (delta), PPY (PP/gamma), and GHRL (epsilon) (Baetens et al 1979;Nussey and Whitehead 2001;Zhao et al 2008;Li et al 2016;Xin et al 2016;Wang et al 2016). The pancreas also contains three exocrine cell types-acinar, stellate, and ductal-that critically support digestion through synthesis and transport of digestive enzymes (Pandol 2011;Reichert and Rustgi 2011).…”

Section: Resultsmentioning

confidence: 99%

Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes

et al. 2016

View full text Add to dashboard Cite

Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type-specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis.[Supplemental material is available for this article.]Pancreatic islets of Langerhans are clusters of at least four different hormone-secreting endocrine cell types that elicit coordinatedbut distinct-responses to maintain glucose homeostasis. As such, they are central to diabetes pathophysiology. On average, human islets consist mostly of beta (54%), alpha (35%), and delta (11%) cells; up to a few percent gamma/pancreatic polypeptide (PP) cells; and very few epsilon cells (Brissova et al. 2005;Cabrera et al. 2006;Blodgett et al. 2015). Human islet composition is neither uniform nor static but varies between individuals and across regions of the pancreas (Brissova et al. 2005;Cabrera et al. 2006;Blodgett et al. 2015). Cellular heterogeneity complicates molecular studies of whole human islets and may mask important role(s) for less common cells in the population (Dorrell et al. 2011b;Bramswig et al. 2013;Nica et al. 2013;Blodgett et al. 2015;Liu and Trapnell 2016). Moreover, it complicates attempts to identify epigenetic and transcriptional signatures distinguishing diabetic from nondiabetic (ND) islets, leading to inconsistent reports of genes and pathways affected (Gunton et al. 2005;Marselli et al. 2010;Taneera et al. 2012;Dayeh et al. 2014). Conventional sorting and enrichment techniques are unable to specifically purify each human islet cell type (Dorrell et al. 2008;Nica et al. 2013;Bramswig et al. 2013;Hrvatin et al. 2014;Blodgett et al. 2015), thus a precise understanding of the transcriptiona...

show abstract

“…This method is reminiscent of the method for assessment of cross-contamination between cell types in single cells described previously 24 . We identified genes associated with TCR response (signature genes), selected cells assigned to a non-targeting control gRNA as representatives of the unperturbed stimulation (control cells), produced in silico mixtures of gene expression profiles of increasingly more stimulated cells based on the control cells from both conditions (mix profiles), and identified the mixed profile that best matched the expression profile of each single cell (signature position).…”

Section: Transcriptome Signature Analysismentioning

confidence: 99%

Pooled CRISPR screening with single-cell transcriptome read-out

Datlinger

Schmidl

Rendeiro

et al. 2016

Preprint

Self Cite

View full text Add to dashboard Cite

CRISPR-based genetic screens have revolutionized the search for new gene functions and biological mechanisms. However, widely used pooled screens are limited to simple read-outs of cell proliferation or the production of a selectable marker protein. Arrayed screens allow for more complex molecular read-outs such as transcriptome profiling, but they provide much lower throughput. Here we demonstrate CRISPR genome editing together with single-cell RNA sequencing as a new screening paradigm that combines key advantages of pooled and arrayed screens. This approach allowed us to link guide-RNA expression to the associated transcriptome responses in thousands of single cells using a straightforward and broadly applicable screening workflow. Main textPooled CRISPR screening is a powerful and widely used method for identifying critical genes involved in biological mechanisms such as cell proliferation 1, 2 , drug resistance 3 , and viral infection 4,5 . Cells are infected in bulk with a library of guide-RNA (gRNA) encoding vectors, and the distribution of gRNAs is monitored before and after applying a selective challenge (Fig. 1a). Pooled CRISPR screens work well for mechanisms that affect cell survival and proliferation, and they can be extended to measure the activity of individual genes (e.g., by using engineered reporter cell lines). However, they cannot be combined with complex molecular read-outs such as transcriptome profiling, which is one of the most comprehensive and informative measures of cellular response 6 . Arrayed screens, in which only one gene is targeted at a time, make it possible to use RNA-seq as read-out 7 , but at the cost of a much lower throughput given that individual gRNAs have to be physically separated (Fig. 1b).Here we propose a third and complementary screening paradigm, single-cell CRISPR screens, based on the idea that gRNAs and their cellular response are already compartmentalized within single cells. Detecting each cell's gRNA along with the corresponding single-cell transcriptome thus enables the derivation of gene expression signatures for individual gene knockouts in a complex pool of cells (Fig. 1c). Our CRISPR Drop-seq (CROP-seq) method comprises a gRNA vector that makes individual gRNAs detectable in single-cell RNA-seq experiments, a high-throughput assay for single-cell RNA-seq 8 , a computational pipeline for assigning single-cell transcriptomes to gRNAs, and a bioinformatic method for analyzing and interpreting gRNA-induced transcriptional profiles. Combining these building blocks, CROP-seq enables pooled screens with single-cell transcriptome read-out, for example for dissecting complex signaling pathways that are not easily reduced to a single selectable marker (Fig. 1d).peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/083774 doi: bioRxiv preprint first posted online Oct. 27, 2016; 2 gRNAs are typically transcribed by RNA polymerase III ...

show abstract

Single‐cell transcriptomes reveal characteristic features of human pancreatic islet cell types

Cited by 222 publications

References 34 publications

ATF5 regulates β-cell survival during stress

ATF5 regulates β-cell survival during stress

Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes

Pooled CRISPR screening with single-cell transcriptome read-out

Contact Info

Product

Resources

About