Page 1 of 48 Diabetes
Chronic β cell depolarization impairs β cell identity by disrupting a network of Ca2+ regulated genes
Jennifer S. Stancill1,2, Jean Philippe Cartailler2, Hannah W. Clayton1,2, James T. O’Connor2, Matthew T. Dickerson3, Prasanna K. Dadi3, Anna B. Osipovich2,3, David A. Jacobson3, Mark A. Magnuson1,2,3,*
1Department of Cell and Developmental Biology, 2Center for Stem Cell Biology, 3Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
2+ Running title: Effects of chronically elevated β cell [Ca ]i
*Corresponding author
9465 MRB IV 2213 Garland Avenue Nashville, TN 37232 0494 United States 615 322 7006 (p) 615 322 6645 (f) [email protected]
Word Count: 4,000 Number of Tables and Figures: 7
Diabetes Publish Ahead of Print, published online May 26, 2017 Diabetes Page 2 of 48
Abstract
We used mice lacking Abcc8, a key component of the β cell KATP channel, to analyze the
2+ 2+ effects of a sustained elevation in the intracellular Ca concentration ([Ca ]i) on β cell identity and gene expression. Lineage tracing analysis revealed the conversion of β cells lacking Abcc8 into PP cells, but not to α or δ cells. RNA Seq analysis of FACS purified Abcc8-/- β cells
confirmed an increase in Ppy gene expression, and revealed altered expression of over 4,200 genes, many of which are involved in Ca2+ signaling, the maintenance of β cell identity, and cell
adhesion. The expression of S100a6 and S100a4, two highly up regulated genes, is closely
correlated with membrane depolarization, suggesting their use as markers for an increase in
2+ [Ca ]i. Moreover, a bioinformatics analysis predicts that many of the dysregulated genes are
regulated by common transcription factors, one of which, Ascl1, was confirmed to be directly
controlled by Ca2+ influx in β cells. Interestingly, among the upregulated genes is Aldh1a3, a putative marker of β cell de differentiation, and other genes associated with β cell failure. Taken
2+ -/- together, our results suggest that chronically elevated β cell [Ca ]i in Abcc8 islets contributes to the alteration of β cell identity, islet cell numbers and morphology, and gene expression, by disrupting a network of Ca2+ regulated genes.
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In Type 2 Diabetes (T2D), pancreatic β cells fail to respond appropriately to metabolic
stresses brought on by age, obesity, and genetic risk factors. The mechanisms by which chronic
metabolic stress, including insulin resistance, glucotoxicity, and lipotoxicity (1 3) impair β cell
function are not understood. While metabolic stress is usually considered to be exogenous to the
β cell, chronic stimulation leads to changes within the β cell, impairing function. One such factor
2+ is chronic elevation in [Ca ]i, sometimes called excitotoxicity (4), which may be triggered by
sustained β cell depolarization due to chronic stimulation.
Ca2+ is a ubiquitous second messenger that is central to regulating cellular dynamics of
many cell types, including β cells. Genetic and pharmacological perturbations that either
stimulate or impair Ca2+ signaling have dramatic effects on β cell function. For instance, the
disruption of calcineurin, a Ca2+ dependent phosphatase, or either CaMKII or CamKIV, two
Ca2+ dependent kinases, profoundly impairs β cell function, likely by modulating the activity of
Ca2+ responsive transcription factors such as NFAT, CREB, and TORC2 (5 9). Conversely, the
constitutive activation of calcineurin or calmodulin, a Ca2+ binding protein, also causes marked
β cell dysfunction (3; 10; 11).
Acutely, glucose metabolism induces ATP sensitive potassium (KATP) channel closure,
2+ 2+ membrane depolarization, opening of voltage gated Ca channels, a rise in [Ca ]i, and insulin
2+ secretion. However, sustained elevation in [Ca ]i has multiple effects on β cell function that can
either be adaptive or maladaptive. β cell proliferation induced by glucose metabolism (12) is an
2+ example of an adaptive response to sustained elevations in [Ca ]i. However, chronically
2+ 2+ elevated [Ca ]i can also induce maladaptive responses, since prevention of Ca influx in the
setting of insulin resistance prevents β cell death (13). In either case, mice lacking KATP channels
Diabetes Page 4 of 48
exhibit disrupted islet morphology, characterized by α cells being located in the islet core (14;
15), suggesting either loss of β cell identity or impairments in cell adhesion.
Here, we show that β cells in Abcc8-/- mice exhibit chronic membrane depolarization and
2+ a sustained elevation in [Ca ]i and dysregulation of over 4,200 genes, many of which are involved in cell adhesion, Ca2+ binding and Ca2+ signaling, and maintenance of β cell identity.
We also report that Abcc8-/- mice exhibit β cell to PP cell trans differentiation and have increased expression of Aldh1a3, a gene recently suggested as a marker of de differentiating β cells. Additionally, we show that S100a6 and S100a4, two EF hand Ca2+ binding proteins, are acutely regulated in β cells by membrane depolarization agents, suggesting that they may be markers for β cell excitotoxicity. Finally, we performed a computational analysis to predict components of the gene regulatory network that may govern the observed gene expression changes and found that one of the predicted regulators, Ascl1, is directly regulated by Ca2+ influx in β cells.
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Research Design and Methods
Mouse lines. All animal experimentation was approved by the Vanderbilt Institutional
Animal Care and Use Committee. Abcc8-/- (Abcc8tm1.1Mgn, MGI: 2388392), RIP-Cre (Tg.Ins2-
cre25Mgn, MGI: 2176227), and R26LSL.YFP (Gt(ROSA)26Sortm1(EYFP)Cos, MGI: 2449038) mice were
congenic C57BL/6 and genotyped as previously described (16 18). MIP-GFP mice (Tg(Ins1-
EGFP/GH1)14Hara, MGI: 3583654) were congenic CD 1 and genotyped as previously described
(19).
Glucose tolerance testing. Following 16 hour fast, male Abcc8+/+ and Abcc8-/- C57BL/6
mice were given intraperitoneal injection of D glucose (2mg/g body weight). Blood glucose was
measured using a BD Logic glucometer.
Verapamil administration. Adult Abcc8+/+; MIP-GFP and Abcc8-/-; MIP-GFP mice were
given either Splenda (2%) or a combination of Verapamil (1mg/mL, Sigma, V4629) and Splenda
in their drinking water for three weeks. Splenda was used to mask the taste of Verapamil.
Immunofluorescence microscopy. Pancreata were fixed in 4% paraformaldehyde, frozen,
and sectioned at a depth of 8 m. Immunofluorescence staining was performed as previously
described (20). Antibodies are listed in the Online Supplemental Material. Images were
acquired using an Olympus FV 1000 confocal microscope, pseudo colored using ImageJ, and
are representative of the phenotype observed in at least three animals. Cell death was determined
using In Situ Cell Death Detection Kit (Roche, 11684795910).
Islet isolation. Pancreata were injected with 0.6mg/mL Collagenase P (Roche,
11213865001) into the pancreatic bile duct. Dissociated tissue was fractionated using
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Histopaque 1077 (Sigma, 10771) followed by hand picking of islets. For fluorescence activated cell sorting (FACS) and RNA sequencing, islets from 4 7 mice were pooled per sample. For quantitative reverse transcription PCR (qRT PCR), islets from a single mouse were used per sample.
Resting membrane potential. Islets were isolated from pancreata of 7 to 10 week old
Abcc8+/+; MIP-GFP and Abcc8-/-; MIP-GFP mice, and electrophysiological recordings were performed as previously described (21).
Ca2+ imaging. Islets were isolated from pancreata of 9 to 11 week old Abcc8+/+and
Abcc8-/- mice, and imaging of cytoplasmic calcium was performed as previously described (22).
Islet culture. Wildtype islets were incubated for 24 hours in DMEM (Gibco, 11966 025) containing 5.6mM glucose, 10% FBS (Gibco, 16140 071), and 1% penicillin streptomycin
(Gibco, 15140 122). Experimental media contained 100 M tolbutamide (Sigma, T0891) or
20mM KCl (Sigma, P5405), with or without 50 M verapamil.
Cell isolation. Islets were dissociated in Accumax (Sigma, A7089) containing 10U/mL
DNase (Invitrogen, AM2222). Following filtration (35 M strainer) and centrifugation, cells were resuspended in Flow Cytometry Buffer (R&D systems, FC001) containing 2U/mL DNase,
0.5M EDTA, and 7AAD (1:1000, ThermoFisher, A1310). GFP+/7AAD cells were analyzed and isolated using an Aria II (BD Biosciences) and collected in Homogenization Solution (Promega,
TM351, containing 1 thioglycerol).
RNA purification and quality control. RNA was isolated from FACS purified β cells and whole islets using Maxwell 16 LEV simplyRNA Tissue Kit (Promega, TM351). RNA samples
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were analyzed using the Agilent 2100 Bioanalyzer. Only samples with RNA integrity number >7
were used.
Library assembly, sequencing, and analysis. RNA samples from FACS purified β cells
were amplified using SMART Seq v4 Ultra Low Input RNA Kit for Sequencing (Clontech,
634888, 8 PCR cycles). cDNA libraries were constructed using Low Input Library Prep Kit
(Clontech, 634947). Paired end sequencing of four replicates each of Abcc8+/+; MIP-GFP and
Abcc8-/-; MIP-GFP samples was performed on an Illumina NextSeq 500 (75 nucleotide reads).
Approximately 900 million raw reads were processed utilizing TrimGalore 0.4.0. STAR (23)
was used to align sequences to mm10 (GRCm38) and GENCODE comprehensive gene
annotations (Release M8). HTSeq was used for counting reads mapped to genomic features (24),
and DESeq2 was employed for differential gene expression analysis (25).
Upstream regulator prediction. iRegulon (26) was used to predict gene regulatory
networks. Default search parameters were used (20kb centered around the transcription start site,
7 species conservation). Enrichment score threshold was 3.0.
qRT PCR. High Capacity cDNA Reverse Transcription Kit (ThermoFisher, 4368814)
was used to convert whole islet RNA to cDNA. qRT PCR was performed on an Applied
Biosystems 7900HT using 2X SyBR Green PCR Master Mix (ThermoFisher, 4309155). Samples
were analyzed in triplicate and normalized to Hprt expression. Primer sequences are listed in the
Online Supplemental Material.
Statistical Analysis. Statistical significance was determined using two tailed Student’s t
test. Data is represented as mean ± s.e.m. A threshold of p<0.05 was used to declare significance.
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Results
-/- 2+ Abcc8 β cells exhibit persistent membrane depolarization and elevated [Ca ]i. Previous studies have shown that single β cells from mice lacking KATP channels, in contrast to normal
2+ mice, exhibit chronically elevated [Ca ]i and continuous action potential firing (16; 27; 28) whereas intact islets exhibit electrical bursting and Ca2+ oscillations (29; 30). To definitively
-/- 2+ establish Abcc8 mice as a model for chronically elevated β cell [Ca ]i, we measured membrane potential at high (11mM) and low (2mM) glucose concentrations (Figure 1A, B).
Abcc8-/- β cells exhibit action potentials in high glucose, but fail to undergo membrane potential polarization in low glucose (Figure 1B). Quantification of the changes in Abcc8-/- β cell membrane potentials confirms that Abcc8-/- β cells show no difference in membrane potential between high and low glucose, contrary to Abcc8+/+ β cells (Figure 1C, D). However, Abcc8-/-
2+ 2+ β cells exhibit a chronic elevation in [Ca ]i, as shown by Ca imaging at both low and high glucose (Figure 1E). Quantification of area under the curve shows that Abcc8-/- β cells have
2+ +/+ significantly higher [Ca ]i than Abcc8 β cells at each time interval measured (Figure 1F).
Additionally, by examining individual traces rather than averaged data, and imaging over a longer time period, we observe Ca2+ oscillations in Abcc8-/- islets under low glucose conditions, as previously reported (29; 30), while Abcc8+/+ islets exhibit consistently low Ca2+ levels
(Supplemental Figure 1). This indicates that, while Abcc8-/- β cells exhibit variable and
2+ 2+ oscillating [Ca ]i under euglycemic conditions, their mean [Ca ]i is elevated compared to
Abcc8+/+ β cells.
2+ -/- Interestingly, despite having chronically elevated β cell [Ca ]i, Abcc8 mice have long been known to have surprisingly small disturbances in their plasma glucose concentrations (16).
First, and as we previously reported (31), they exhibit outright hypoglycemia in the fasted state
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(Supplemental Figure 3A). Second, they exhibit a trend toward mild hyperglycemia in the fed
state (Supplemental Figure 3B).
β cell identity becomes compromised in Abcc8-/- mice. During prolonged metabolic
stress, β cells can lose expression of functional markers and convert to other endocrine cell types
(32). However, β cell de differentiation has not been studied in the context of chronically
2+ -/- elevated [Ca ]i. Thus, we performed β cell lineage tracing using Abcc8 ; RIP-Cre;
Rosa26LSL.YFP/+ mice. While there was no evidence for either β to α cell or β to δ cell trans
differentiation (Supplemental Figure 2A, B), we observed an increase in YFP/PP co expression
(Figure 2C). Most YFP/PP co expressing cells are poly hormonal, expressing both PP and
insulin (Figure 2A), but a few cells (0.24% of all YFP expressing cells and 10% of YFP/PP co
expressing cells, Supplemental Figure 2C) no longer express insulin (Figure 2B).
Administration of a Ca2+ channel blocker to Abcc8-/- mice resulted in a lower number of
Insulin/PP co expressing cells, but the difference was not significant (Supplemental Figure
2D). The loss of β cell identity correlates with impaired glucose tolerance not attributable to β
cell death (Supplemental Figure 3A, C). Complete dedifferentiation, e.g. YFP expression
without hormone immunostaining, was only observed at a very low rate and was similar in both
wild type and knock out animals (0.19% and 0.21%, respectively, Supplemental Figure 2E).
2+ RNA expression profiling. To determine how chronically elevated β cell [Ca ]i affects
gene expression, we performed RNA sequencing using FACS purified β cells from Abcc8-/-;
MIP-GFP mice at 8 9 weeks of age. Since the hGH mini gene within the MIP-GFP allele causes
both hGH expression and activation of STAT5 signaling (33), we used MIP-GFP expressing
mice as controls. Principal component and gene clustering analyses (Supplemental Figure 4B,
C), performed on RNA Seq data from FACS purified cells (Supplemental Figure 4A),
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indicates that most of the top 500 differentially expressed genes cluster as expected. Differential expression analysis (Figure 3B, Supplemental Table 1) revealed 4,208 differentially expressed genes (2,152 downregulated and 2,056 upregulated) in Abcc8-/- β cells (adjusted p value < 0.05).
Approximately 90% are protein coding, 3% are non coding RNAs, 2% are pseudogenes, and 3% are other types of processed transcripts (Figure 3A).
Abcc8-/- β cells exhibit changes in expression of genes involved in β cell maturation,
Ca2+ signaling, cell adhesion, and de differentiation. To correlate gene expression with the functional abnormalities of Abcc8-/- islets, we examined genes known to be highly enriched in mature β cells and observed that Ins1, Slc2a2, Neurod1, Gck, Glp1r, Npy, several synaptotagmins, Tph1, Tph2, and Egfr are all down regulated (Figure 3C). Conversely, Ppy is upregulated in Abcc8-/- β cells, consistent with our observation of poly hormonal cells.
-/- 2+ Since Abcc8 β cells have a persistent increase in [Ca ]i, we examined genes with well defined roles in Ca2+ binding or signaling such as Myo7a, a Ca2+/Calmodulin binding myosin motor protein, Pcp4, a calmodulin binding protein known to protect neurons from Ca2+ induced toxicity (34), and Cacng3, a subunit of a voltage dependent Ca2+ channel, and found their expression to be elevated. Similarly, we observed that Nfatc1, Mef2c, and Mef2d, three calcium regulated transcription factors; Camk1d, Camkk1, and Camkk2, three kinases involved in calcium signaling; and S100a1, S100a3, S100a4, S100a6, and S100a13, five EF hand calcium binding proteins; were also up regulated (Figure 3C).
Quantitation of islet cell types in Abcc8-/- mice revealed fewer β cells, more α , δ , and
PP cells, and a progressive redistribution of non β endocrine cells to the islet core
(Supplemental Figure 5). To correlate gene expression with this disrupted islet architecture, we
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examined expression of cell adhesion molecules, hypothesizing that a reduction in such genes
could result in loss of islet structure. Consistently, we observed reduction in multiple cell
adhesion molecules, including Cldn1, Cldn3, Cldn8, Cldn23, and Ocln, genes involved in tight
junctions; Cdh1, Cdh7, Cdh8, Cdh13, and Cdh18, encoding cadherins; Cdhr1, a cadherin related
protein; Pcdhb15 and Pcdhb22, encoding protocadherins; and Vcam1, a vascular cell adhesion
molecule (Figure 3C).
Aldh1a3, a retinaldehyde dehydrogenase recently suggested to be a marker for β cell
dedifferentiation (35), is 27 fold upregulated in Abcc8-/- β cells by RNA seq (Figure 3C). In
addition, six other genes (Serpina7, Aass, Asb11, Penk, Fabp3, and Tcea1) enriched in
dedifferentiated β cells (35) are upregulated in Abcc8-/- β cells (Figure 3C). Co immunostaining
with insulin indicates that while ALDH1A3 is expressed in only 0.4% of Abcc8+/+ β cells, it is
present in 29.1% of Abcc8-/- β cells (Figure 4A, B). However, this fraction was reduced to
11.4% in Abcc8-/- mice administered the Ca2+ channel blocker verapamil (Figure 4A, B), further
2+ suggesting that a chronic increase in [Ca ]i impairs the maintenance of cell identity.
S100a6 and S100a4 are markers of excitotoxicity in β cells. To identify genes that could
serve as markers of β cell excitotoxicity, we analyzed S100a6 and S100a4. Both genes are
appealing targets due to their functions as EF hand Ca2+ binding proteins, the association of
S100a6 with insulin secretion (36), and the increased expression of members of the S100 gene
family in islets from humans with hyperglycemia (37). Moreover, they are among the most
highly upregulated genes in Abcc8-/- β cells, with S100a6 and S100a4 increasing 37 and 5 fold,
respectively. While S100A6 is only expressed in 2.8% of Abcc8+/+ β cells, it is expressed in
38.4% of Abcc8-/- β cells (Figure 4C, D). Additionally, qRT PCR using whole islet RNA
confirms the upregulation of S100a6 and S1004 in Abcc8-/- islets (Figure 5A).
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To determine if the observed changes in S100a6 and S100a4 expression in Abcc8-/- β
2+ cells are due to chronically elevated [Ca ]i, and not some other mechanism, we treated wildtype islets with either KCl or tolbutamide and found that membrane depolarization is associated with an increase in both S100a6 and S100a4 expression (Figure 5B E), mirroring the expression pattern in Abcc8-/- β cells. These changes were reversed when islets were treated with both a depolarizing agent and the Ca2+ channel inhibitor verapamil (Figure 5B E). Moreover, the
expression of S100a6 and S100a4 was decreased when Ca2+ influx is pharmacologically
inhibited in Abcc8-/- mice (Figure 5F, G). These results suggest that S100a6 and S100a4
-/- 2+ expression in Abcc8 β cells is tightly correlated with [Ca ]i. Finally, co immunostaining with
S100A6 and ALDH1A3 revealed that 15.4 ± 2.1% of insulin expressing cells in Abcc8-/- mice express both S100A6 and ALDH1A3 (Figure 4E).
Prediction of upstream regulators. To determine if differentially expressed genes in
Abcc8-/- β cells might share common upstream regulators, we utilized iRegulon, a program that identifies common DNA binding motifs in co expressed genes (26). Analysis of the top 500 upregulated genes revealed binding sites for ASCL1, CEBPG, and RARG in many genes, with some genes, including Aldh1a3, containing binding sites for all three of these transcriptional regulators (Figure 6A, Supplemental Table 2, Supplemental Figure 6). Interestingly, all three
of these predicted regulators are upregulated in Abcc8-/- β cells (Figure 6C). Conversely, analysis of the top 500 down regulated genes predicts binding sites for TEAD1, HNF1A, and
ZFP647 (Figure 6B, Supplemental Table 3, Supplemental Figure 7). However, the expression of these regulators is unchanged in Abcc8-/- β cells (Figure 6C).
2+ -/- Ascl1 is regulated by [Ca ]i in β cells. Since Ascl1 is 22 fold upregulated in Abcc8 ;
MIP-GFP β cells (Figure 3B) and 24 fold upregulated in Abcc8-/- islets (Figure 6D), and has
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been shown by ChIP Seq or PCR to bind near 51% of the predicted targets (38 40), we studied
2+ its responsiveness to changes in [Ca ]i in isolated islets. Consistent with Ascl1 being regulated
2+ by [Ca ]i, its expression increases in response to membrane depolarization, an effect that is
reversed when Ca2+ influx is inhibited by verapamil, both in isolated islets (Figure 6E) and in
mice (Figure 6F). These results support the idea that ASCL1 could play a central role in
2+ regulating gene expression in β cells with chronically elevated [Ca ]i.
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Discussion
-/- 2+ -/- Abcc8 β cells exhibit elevated basal [Ca ]i. Abcc8 β cells have been previously shown to have altered intracellular Ca2+ homeostasis, as would be expected in the absence of
-/- KATP channels (16; 27 30). We similarly observed that Abcc8 β cells exhibit both persistent
2+ +/+ depolarization and an elevated mean [Ca ]i compared to Abcc8 islets (Figure 1).
Interestingly, while Abcc8-/- β cells exhibit Ca2+ oscillations in sub stimulatory glucose
(Supplemental Figure 1), as has been previously reported (29; 30), we did not consistently observe oscillations in membrane potential, as has been observed in β cells lacking KATP channels. This may be due to the short duration of the recordings, or to our use of patch clamp technique rather than intracellular microelectrodes which limits the detection of oscillations in membrane potential (29). Regardless, Abcc8-/- β cells experience more persistent membrane
2+ depolarization and elevated mean [Ca ]i compared to wild type β cells, and the downstream
2+ effects on gene expression are likely to be the same. We also observed a transient drop in [Ca ]i in Abcc8-/- islets following glucose stimulation (Figure 1E) that was not seen in Abcc8+/+ islets.
This drop is due to brief membrane hyperpolarization caused by transient activation of the sodium potassium ATPase (29), and has been observed previously in islets treated with KATP channel inhibitors (41) as well as in other KATP channel deficient mice (29).
Abcc8-/- β cells exhibit dysregulated gene expression. By performing RNA Seq on purified pancreatic β cell populations from both Abcc8-/- and Abcc8+/+ mice, we found that the expression of 4,208 genes was perturbed. Some of these genes, including S100a6, Myo7a, Pcp4,
Cacng3, Mef2c, and Camk1d, are known to be involved in calcium binding and signaling
(Figure 3C). The S100 gene family, for instance, modulates the activity of other proteins upon calcium binding (42). Moreover, S100A6, specifically, promotes Ca2+ stimulated insulin release
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(36). Camk1d, Camkk1, and Camkk2, three protein kinases, Myo7a, a myosin motor protein, and
Mef2d and Mef2c, are involved in Ca2+/calmodulin dependent signaling, or are regulated by
2+ 2+ [Ca ]i (43; 44). However, the alteration of some Ca regulated genes does not imply that all of
2+ the gene expression changes we observed are caused by changes in [Ca ]i. Although we have
demonstrated that changes in S100a6, S100a4, and Ascl1 expression are tightly linked to
membrane potential (Figures 5B E and 6E), a similar analysis has not been performed for the
remaining genes. Thus, while it is likely that a substantial fraction of the dysregulated genes are
2+ due to altered [Ca ]i homeostasis, other mechanisms, such as paracrine and/or neuronal
signaling, may also be involved. Additional studies are necessary to determine which changes
2+ are directly attributable to chronically elevated [Ca ]i, and which are due to other signaling
mechanisms and/or compensatory adaptations.
Compromised β cell identity in Abcc8-/- mice. Recent studies have suggested that β cell
dedifferentiation contributes to the development of T2D (32; 35). Among the genes affected in
Abcc8-/- β cells are many known to be involved in maintaining β cell identity and/or function,
such as Ins1, Slc2a2, Neurod1, Gck, and Syt10 (Figure 3C). However, some of the transcription
factors previously associated with β cell dedifferentiation (32), including Mafa, Pdx1, Nkx6.1,
FoxO1, Ngn3, Oct4, and Nanog, are unchanged. This difference may explain the modest loss of
β cell identity observed in Abcc8-/- mice, with only 2.21% of β cells undergoing trans
differentiation to either INS/PP poly hormonal or PP mono hormonal cells (Figure 2C). While
treatment with a Ca2+ channel blocker did not statistically reverse the INS/PP poly hormonal
cells, its use resulted in a decrease in the percentage of Abcc8-/- β cells expressing the
dedifferentiation marker ALDH1A3 (Figure 4B), further suggesting that a chronic increase in
2+ [Ca ]i may contribute to loss of β cell identity. In this regard, it is important to distinguish our
Diabetes Page 16 of 48
results, which reflect the loss of KATP channels, from studies using KATP channel gain of
2+ function mutants (45; 46). The current study examines the effects of elevated [Ca ]i in a nearly
2+ euglycemic setting, while the latter reflects decreased [Ca ]i in a hyperglycemic setting.
2+ Two potential genetic markers for elevated [Ca ]i. Our studies identified two genes,
S100a6 and S100a4, which were highly up regulated in Abcc8-/- β cells and were also acutely regulated by treatment with depolarizing agents and a Ca2+ channel blocker in isolated islets
(Figure 5B E). While administration of a Ca2+ channel blocker to Abcc8-/- mice only partially rescued the expression of S100a6 or S100a4 (Figure 5F, G), this may be due to inadequate dosing or a treatment duration that was too short to overcome the effects of the Abcc8 gene knockout. However, it is also possible that these genes are only partially regulated by Ca2+ influx in vivo. Regardless, our data strongly suggest that S100a6 and S100a4 are regulated by Ca2+ in the β cell, and that they may serve as markers for β cell excitotoxicity. In support of this, members of the S100 gene family, including S100A3, S100A6, S100A10, S100A11, and
S100A16, have been associated, in human islets, with hyperglycemia (37), and S100A6, specifically, was shown to be positively correlated with body mass index in β cells from type 2 diabetic donors (47). While neither gene was altered in two recent single cell sequencing studies of people with T2D (47; 48), the sequencing depth was very shallow.
2+ 2+ Effects of a sustained increase in [Ca ]i on islet morphology. Perturbations in Ca signaling also provide a compelling explanation for the disrupted islet morphology observed in
2+ KATP channel knockout mice (Supplemental Figure 5). [Ca ]i is required for maintenance of tight junctions and adherens junctions, and focal adhesion disassembly occurs in response to
2+ elevated [Ca ]i (49). Accordingly, among the down regulated genes are many that encode cell adhesion molecules, such as Ocln, Tln1, and Cdh1 (Figure 3C), suggesting that a Ca2+
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dependent gradual breakdown of cell to cell contacts may be responsible for the altered islet
morphology.
Identification of putative upstream regulators. Bioinformatics analysis of genes whose
expression was increased in the Abcc8 / mice identified ASCL1, CEBPG, and RARG as possible
upstream regulators (Figure 6A). ASCL1, also known as MASH1, is important for neuronal
commitment and differentiation (50). Retinoic acid receptors, including RARG, play a role in
both endocrine cell development and maintenance of proper insulin secretion and β cell mass
(51). Finally, CEBPB, a closely related protein to CEBPG, represses the insulin promoter under
conditions of chronically elevated glucose, and its accumulation in β cells increases vulnerability
to ER stress (52; 53). Although our computational analysis is purely predictive, it is partially
validated by the fact that 51% of the ASCL1 target genes and 60% of the RARG binding sites
were established by ChIP Seq or PCR (38 40; 54). Importantly, S100a4 is among the ASCL1
targets that have been experimentally validated (38 40), and our in depth analysis of Ascl1
2+ strongly supports its regulation by [Ca ]i, consistent with our model. Conversely, analysis of
2+ genes that are down regulated by [Ca ]i predicts binding sites for TEAD1, HNF1A, and ZFP647
(Figure 6B). Although Tead1 gene expression is unaffected in Abcc8-/- β cells, the activity of
TEAD1, a member of the Hippo pathway that interacts with YAP/TAZ to promote proliferation,
is directly inhibited by Ca2+ (55). Furthermore, since a gene knock out of Hnf1a results in β cell
failure and diabetes (56), a predicted decrease in its activity could explain the decrease in genes
involved in β cell function in Abcc8-/- β cells.
Does excitotoxicity contribute to β cell failure? Our studies, together with findings of
-/- others (15; 16; 27 30), indicate that the absence of functional KATP channels in Abcc8 mice
2+ causes a chronic elevation of β cell [Ca ]i, an impairment of β cell identity, alterations in islet
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cell numbers and morphology, and very significant perturbations in β cell gene expression.
2+ -/- While the elevation of [Ca ]i in Abcc8 β cells, due to the total absence of KATP channels, is
2+ persistent and severe, a less severe or persistent elevation in mean [Ca ]i may also occur in patients with pre diabetes or T2D, when hyperglycemia chronically stimulates insulin secretion, or when a sulfonylurea is given as therapy for T2D. Interestingly, although Abcc8-/- mice exhibit
impaired glucose tolerance at 12 weeks of age, they do not go on to develop T2D, at least in the
time frame studied here. This suggests that the impairments in β cell identity and islet
morphology are insufficient themselves to cause β cell failure. However, β cell excitotoxicity,
acting in combination with other metabolic stresses, may accelerate the loss of functional β cells, perhaps by dedifferentiation or glucolipotoxicity. Regardless, our findings provide new insights
into transcriptional responses that occur within β cells when they are subjected to chronically
2+ elevated [Ca ]i, and suggest a model (Figure 7) which involves the coordinated interactions of a
network of Ca2+ responsive genes and upstream transcriptional modulators. This network may
2+ exist to balance both the positive and negative effects that [Ca ]i is known to have on β cell function and mass.
Page 19 of 48 Diabetes
Author Contributions
J.S.S. and M.A.M. designed the study and wrote the manuscript. J.S.S., H.W.C., and J.T.O.
performed experiments and analyzed data. J P.C. performed RNA Seq data processing,
alignment, differential gene expression analysis, and edited the manuscript. M.T.D., P.K.D., and
D.J. performed membrane potential measurements and calcium imaging, and analyzed the data.
A.B.O. contributed to study design and edited the manuscript. M.A.M. supervised and funded the
experiments. M.A.M. is the guarantor of this work and, as such, had full access to all the data in
the study and takes responsibility for the integrity of the data and the accuracy of the data
analysis.
RNA Seq data are available in ArrayExpress (www.ebi.ac.uk/arrayexpress) under accession
number E MTAB 4726.
Acknowledgments
These studies were supported in part by NIH grants DK72473 and DK89523 to M.A.M. We
thank the Vanderbilt Islet Procurement and Analysis Core (supported by DK020593) for
performing multiple islet isolations, Vanderbilt Technologies for Advanced Genomics
(VANTAGE) for performing cell sorting and RNA sequencing, the Vanderbilt Cell Imaging
Shared Resource (supported by DK020593 and CA68485) for helping to acquire images, the
Vanderbilt Tissue Pathology Shared Resource for processing and sectioning paraffin embedded
tissues, and the Vanderbilt Transgenic Mouse/ESC Shared Resource (supported by DK020593
Diabetes Page 20 of 48
and CA68485) for reconstituting mice with the Abcc8 null allele. We also thank Guoqiang Gu and Roland Stein of Vanderbilt University for reading the manuscript, and Jody Peters,
Katherine Boyer, and Lauren Stiehle, also of Vanderbilt University, for technical assistance. The authors declare no conflicts of interest.
Page 21 of 48 Diabetes
References
1. Muoio DM, Newgard CB: Mechanisms of disease:Molecular and metabolic mechanisms of insulin resistance and beta cell failure in type 2 diabetes. Nat Rev Mol Cell Biol 2008;9:193 205
2. Poitout V, Robertson RP: Glucolipotoxicity: fuel excess and beta cell dysfunction. Endocrine reviews 2008;29:351 366
3. Tornovsky Babeay S, Dadon D, Ziv O, Tzipilevich E, Kadosh T, Schyr Ben Haroush R, Hija A, Stolovich Rain M, Furth Lavi J, Granot Z, Porat S, Philipson LH, Herold KC, Bhatti TR, Stanley C, Ashcroft FM, In't Veld P, Saada A, Magnuson MA, Glaser B, Dor Y: Type 2 diabetes and congenital hyperinsulinism cause DNA double strand breaks and p53 activity in beta cells. Cell metabolism 2014;19:109 121
4. Arundine M, Tymianski M: Molecular mechanisms of calcium dependent neurodegeneration in excitotoxicity. Cell Calcium 2003;34:325 337
5. Heit JJ, Apelqvist AA, Gu X, Winslow MM, Neilson JR, Crabtree GR, Kim SK: Calcineurin/NFAT signalling regulates pancreatic beta cell growth and function. Nature 2006;443:345 349
6. Soleimanpour SA, Crutchlow MF, Ferrari AM, Raum JC, Groff DN, Rankin MM, Liu C, De Leon DD, Naji A, Kushner JA, Stoffers DA: Calcineurin signaling regulates human islet {beta} cell survival. J Biol Chem 2010;285:40050 40059
7. Dadi PK, Vierra NC, Ustione A, Piston DW, Colbran RJ, Jacobson DA: Inhibition of pancreatic beta cell Ca2+/calmodulin dependent protein kinase II reduces glucose stimulated calcium influx and insulin secretion, impairing glucose tolerance. J Biol Chem 2014;289:12435 12445
8. Screaton RA, Conkright MD, Katoh Y, Best JL, Canettieri G, Jeffries S, Guzman E, Niessen S, Yates JR, 3rd, Takemori H, Okamoto M, Montminy M: The CREB coactivator TORC2 functions as a calcium and cAMP sensitive coincidence detector. Cell 2004;119:61 74
9. Blanchet E, Van de Velde S, Matsumura S, Hao E, LeLay J, Kaestner K, Montminy M: Feedback Inhibition of CREB Signaling Promotes Beta Cell Dysfunction in Insulin Resistance. Cell reports 2015;10:1149 1157
10. Epstein PN, Overbeek PA, Means AR: Calmodulin induced early onset diabetes in transgenic mice. Cell 1989;58:1067 1073
11. Bernal Mizrachi E, Cras Meneur C, Ye BR, Johnson JD, Permutt MA: Transgenic overexpression of active calcineurin in beta cells results in decreased beta cell mass and hyperglycemia. PloS one 2010;5:e11969
12. Porat S, Weinberg Corem N, Tornovsky Babaey S, Schyr Ben Haroush R, Hija A, Stolovich Rain M, Dadon D, Granot Z, Ben Hur V, White P, Girard CA, Karni R, Kaestner KH,
Diabetes Page 22 of 48
Ashcroft FM, Magnuson MA, Saada A, Grimsby J, Glaser B, Dor Y: Control of pancreatic beta cell regeneration by glucose metabolism. Cell metabolism 2011;13:440 449
13. Xu G, Chen J, Jing G, Shalev A: Preventing beta cell loss and diabetes with calcium channel blockers. Diabetes 2012;61:848 856
14. Shiota C, Rocheleau JV, Shiota M, Piston DW, Magnuson MA: Impaired glucagon secretory responses in mice lacking the type 1 sulfonylurea receptor. Am J Physiol Endocrinol Metab 2005;289:E570 577
15. Winarto A, Miki T, Seino S, Iwanaga T: Morphological changes in pancreatic islets of KATP channel deficient mice: the involvement of KATP channels in the survival of insulin cells and the maintenance of islet architecture. Archives of histology and cytology 2001;64:59 67
16. Shiota C, Larsson O, Shelton KD, Shiota M, Efanov AM, Hoy M, Lindner J, Kooptiwut S, Juntti Berggren L, Gromada J, Berggren PO, Magnuson MA: Sulfonylurea receptor type 1 knock out mice have intact feeding stimulated insulin secretion despite marked impairment in their response to glucose. J Biol Chem 2002;277:37176 37183
17. Postic C, Shiota M, Niswender KD, Jetton TL, Chen Y, Moates JM, Shelton KD, Lindner J, Cherrington AD, Magnuson MA: Dual roles for glucokinase in glucose homeostasis as determined by liver and pancreatic beta cell specific gene knock outs using Cre recombinase. J Biol Chem 1999;274:305 315
18. Srinivas S, Watanabe T, Lin CS, William CM, Tanabe Y, Jessell TM, Costantini F: Cre reporter strains produced by targeted insertion of EYFP and ECFP into the ROSA26 locus. BMC Dev Biol 2001;1:4
19. Hara M, Wang X, Kawamura T, Bindokas VP, Dizon RF, Alcoser SY, Magnuson MA, Bell GI: Transgenic mice with green fluorescent protein labeled pancreatic beta cells. Am J Physiol Endocrinol Metab 2003;284:E177 183
20. Burlison JS, Long Q, Fujitani Y, Wright CV, Magnuson MA: Pdx 1 and Ptf1a concurrently determine fate specification of pancreatic multipotent progenitor cells. Developmental biology 2008;316:74 86
21. Vierra NC, Dadi PK, Jeong I, Dickerson M, Powell DR, Jacobson DA: Type 2 Diabetes Associated K+ Channel TALK 1 Modulates beta Cell Electrical Excitability, Second Phase Insulin Secretion, and Glucose Homeostasis. Diabetes 2015;64:3818 3828
22. Dadi PK, Vierra NC, Jacobson DA: Pancreatic beta cell specific ablation of TASK 1 channels augments glucose stimulated calcium entry and insulin secretion, improving glucose tolerance. Endocrinology 2014;155:3757 3768
23. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR: STAR: ultrafast universal RNA seq aligner. Bioinformatics 2013;29:15 21
Page 23 of 48 Diabetes
24. Anders S, Pyl PT, Huber W: HTSeq a Python framework to work with high throughput sequencing data. Bioinformatics 2015;31:166 169
25. Love MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA seq data with DESeq2. Genome Biol 2014;15:550
26. Janky R, Verfaillie A, Imrichova H, Van de Sande B, Standaert L, Christiaens V, Hulselmans G, Herten K, Naval Sanchez M, Potier D, Svetlichnyy D, Kalender Atak Z, Fiers M, Marine JC, Aerts S: iRegulon: from a gene list to a gene regulatory network using large motif and track collections. PLoS Comput Biol 2014;10:e1003731
27. Miki T, Nagashima K, Tashiro F, Kotake K, Yoshitomi H, Tamamoto A, Gonoi T, Iwanaga T, Miyazaki J, Seino S: Defective insulin secretion and enhanced insulin action in KATP channel deficient mice. Proc Natl Acad Sci U S A 1998;95:10402 10406
28. Seghers V, Nakazaki M, DeMayo F, Aguilar Bryan L, Bryan J: Sur1 knockout mice. A model for K(ATP) channel independent regulation of insulin secretion. J Biol Chem 2000;275:9270 9277
29. Dufer M, Haspel D, Krippeit Drews P, Aguilar Bryan L, Bryan J, Drews G: Oscillations of membrane potential and cytosolic Ca(2+) concentration in SUR1( / ) beta cells. Diabetologia 2004;47:488 498
30. Nenquin M, Szollosi A, Aguilar Bryan L, Bryan J, Henquin JC: Both triggering and amplifying pathways contribute to fuel induced insulin secretion in the absence of sulfonylurea receptor 1 in pancreatic beta cells. J Biol Chem 2004;279:32316 32324
31. De Leon DD, Li C, Delson MI, Matschinsky FM, Stanley CA, Stoffers DA: Exendin (9 39) corrects fasting hypoglycemia in SUR 1 / mice by lowering cAMP in pancreatic beta cells and inhibiting insulin secretion. J Biol Chem 2008;283:25786 25793
32. Talchai C, Xuan S, Lin HV, Sussel L, Accili D: Pancreatic beta cell dedifferentiation as a mechanism of diabetic beta cell failure. Cell 2012;150:1223 1234
33. Brouwers B, de Faudeur G, Osipovich AB, Goyvaerts L, Lemaire K, Boesmans L, Cauwelier EJ, Granvik M, Pruniau VP, Van Lommel L, Van Schoors J, Stancill JS, Smolders I, Goffin V, Binart N, in't Veld P, Declercq J, Magnuson MA, Creemers JW, Schuit F, Schraenen A: Impaired islet function in commonly used transgenic mouse lines due to human growth hormone minigene expression. Cell metabolism 2014;20:979 990
34. Kanazawa Y, Makino M, Morishima Y, Yamada K, Nabeshima T, Shirasaki Y: Degradation of PEP 19, a calmodulin binding protein, by calpain is implicated in neuronal cell death induced by intracellular Ca2+ overload. Neuroscience 2008;154:473 481
35. Kim Muller JY, Fan J, Kim YJ, Lee SA, Ishida E, Blaner WS, Accili D: Aldehyde dehydrogenase 1a3 defines a subset of failing pancreatic beta cells in diabetic mice. Nature communications 2016;7:12631
Diabetes Page 24 of 48
36. Okazaki K, Niki I, Iino S, Kobayashi S, Hidaka H: A role of calcyclin, a Ca(2+) binding protein, on the Ca(2+) dependent insulin release from the pancreatic beta cell. J Biol Chem 1994;269:6149 6152
37. Fadista J, Vikman P, Laakso EO, Mollet IG, Esguerra JL, Taneera J, Storm P, Osmark P, Ladenvall C, Prasad RB, Hansson KB, Finotello F, Uvebrant K, Ofori JK, Di Camillo B, Krus U, Cilio CM, Hansson O, Eliasson L, Rosengren AH, Renstrom E, Wollheim CB, Groop L: Global genomic and transcriptomic analysis of human pancreatic islets reveals novel genes influencing glucose metabolism. Proc Natl Acad Sci U S A 2014;111:13924 13929
38. Castro DS, Martynoga B, Parras C, Ramesh V, Pacary E, Johnston C, Drechsel D, Lebel Potter M, Garcia LG, Hunt C, Dolle D, Bithell A, Ettwiller L, Buckley N, Guillemot F: A novel function of the proneural factor Ascl1 in progenitor proliferation identified by genome wide characterization of its targets. Genes Dev 2011;25:930 945
39. Webb AE, Pollina EA, Vierbuchen T, Urban N, Ucar D, Leeman DS, Martynoga B, Sewak M, Rando TA, Guillemot F, Wernig M, Brunet A: FOXO3 shares common targets with ASCL1 genome wide and inhibits ASCL1 dependent neurogenesis. Cell reports 2013;4:477 491
40. Raposo AA, Vasconcelos FF, Drechsel D, Marie C, Johnston C, Dolle D, Bithell A, Gillotin S, van den Berg DL, Ettwiller L, Flicek P, Crawford GE, Parras CM, Berninger B, Buckley NJ, Guillemot F, Castro DS: Ascl1 Coordinately Regulates Gene Expression and the Chromatin Landscape during Neurogenesis. Cell reports 2015;
41. Mourad NI, Nenquin M, Henquin JC: Metabolic amplification of insulin secretion by glucose is independent of beta cell microtubules. Am J Physiol Cell Physiol 2011;300:C697 706
42. Kligman D, Hilt DC: The S100 protein family. Trends in biochemical sciences 1988;13:437 443
43. Mellstrom B, Savignac M, Gomez Villafuertes R, Naranjo JR: Ca2+ operated transcriptional networks: molecular mechanisms and in vivo models. Physiol Rev 2008;88:421 449
44. Udovichenko IP, Gibbs D, Williams DS: Actin based motor properties of native myosin VIIa. J Cell Sci 2002;115:445 450
45. Wang Z, York NW, Nichols CG, Remedi MS: Pancreatic beta cell dedifferentiation in diabetes and redifferentiation following insulin therapy. Cell metabolism 2014;19:872 882
46. Brereton MF, Iberl M, Shimomura K, Zhang Q, Adriaenssens AE, Proks P, Spiliotis, II, Dace W, Mattis KK, Ramracheya R, Gribble FM, Reimann F, Clark A, Rorsman P, Ashcroft FM: Reversible changes in pancreatic islet structure and function produced by elevated blood glucose. Nature communications 2014;5:4639
47. Segerstolpe A, Palasantza A, Eliasson P, Andersson EM, Andreasson AC, Sun X, Picelli S, Sabirsh A, Clausen M, Bjursell MK, Smith DM, Kasper M, Ammala C, Sandberg R: Single Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes. Cell metabolism 2016;24:593 607
Page 25 of 48 Diabetes
48. Xin Y, Kim J, Okamoto H, Ni M, Wei Y, Adler C, Murphy AJ, Yancopoulos GD, Lin C, Gromada J: RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes. Cell metabolism 2016;24:608 615
49. Giannone G, Ronde P, Gaire M, Beaudouin J, Haiech J, Ellenberg J, Takeda K: Calcium rises locally trigger focal adhesion disassembly and enhance residency of focal adhesion kinase at focal adhesions. J Biol Chem 2004;279:28715 28723
50. Pang ZP, Yang N, Vierbuchen T, Ostermeier A, Fuentes DR, Yang TQ, Citri A, Sebastiano V, Marro S, Sudhof TC, Wernig M: Induction of human neuronal cells by defined transcription factors. Nature 2011;476:220 223
51. Brun PJ, Grijalva A, Rausch R, Watson E, Yuen JJ, Das BC, Shudo K, Kagechika H, Leibel RL, Blaner WS: Retinoic acid receptor signaling is required to maintain glucose stimulated insulin secretion and beta cell mass. FASEB J 2015;29:671 683
52. Lu M, Seufert J, Habener JF: Pancreatic beta cell specific repression of insulin gene transcription by CCAAT/enhancer binding protein beta. Inhibitory interactions with basic helix loop helix transcription factor E47. J Biol Chem 1997;272:28349 28359
53. Matsuda T, Kido Y, Asahara S, Kaisho T, Tanaka T, Hashimoto N, Shigeyama Y, Takeda A, Inoue T, Shibutani Y, Koyanagi M, Hosooka T, Matsumoto M, Inoue H, Uchida T, Koike M, Uchiyama Y, Akira S, Kasuga M: Ablation of C/EBPbeta alleviates ER stress and pancreatic beta cell failure through the GRP78 chaperone in mice. The Journal of clinical investigation 2010;120:115 126
54. Moutier E, Ye T, Choukrallah MA, Urban S, Osz J, Chatagnon A, Delacroix L, Langer D, Rochel N, Moras D, Benoit G, Davidson I: Retinoic acid receptors recognize the mouse genome through binding elements with diverse spacing and topology. J Biol Chem 2012;287:26328 26341
55. Thompson M, Andrade VA, Andrade SJ, Pusl T, Ortega JM, Goes AM, Leite MF: Inhibition of the TEF/TEAD transcription factor activity by nuclear calcium and distinct kinase pathways. Biochem Biophys Res Commun 2003;301:267 274
56. Pontoglio M, Sreenan S, Roe M, Pugh W, Ostrega D, Doyen A, Pick AJ, Baldwin A, Velho G, Froguel P, Levisetti M, Bonner Weir S, Bell GI, Yaniv M, Polonsky KS: Defective insulin secretion in hepatocyte nuclear factor 1alpha deficient mice. The Journal of clinical investigation 1998;101:2215 2222
Diabetes Page 26 of 48
Figure Legends
-/- 2+ Figure 1. Abcc8 β cells exhibit persistent membrane depolarization and elevated [Ca ]i. A perforated patch recording technique was employed to monitor the membrane potential of
Abcc8+/+ and Abcc8-/- β cells in whole islets. (A) Abcc8+/+ β cells display normal activity at
11mM glucose and become hyperpolarized in response to 2mM glucose (representative
recording). (B) Abcc8-/- β cells display activity similar to Abcc8+/+ β cells at 11mM glucose
(with a trend toward a depolarized plateau potential); however, their activity remains statistically unchanged in response to 2mM glucose (representative recording). (C) Quantification of the potentials of Abcc8+/+ and Abcc8-/- β cells at 11mM and 2mM glucose. Abcc8+/+ β cells become
significantly more polarized in response to 2mM glucose while there is no difference between
Abcc8-/- β cells at 11mM and 2mM glucose. (D) Quantification of the percent change in membrane potential between 11mM and 2mM glucose for Abcc8+/+ and Abcc8-/- β cells. The membrane potential of Abcc8+/+ β cells changes significantly more than Abcc8-/- β cells. (E)
Intracellular Ca2+ was monitored in Abcc8+/+ and Abcc8-/- islets with Fura 2 AM. Islets were
equilibrated in 2mM glucose, stimulated with 11mM glucose, and returned to 2mM glucose as
indicated by the bars above the traces (overall averages are shown). (F) Intracellular Ca2+ area
under the curve (AUC) was quantified at intervals representing low glucose conditions (0 2 min),
glucose stimulation (10 12 min), and a return to low glucose (20 22 min). Data are an average of
n ≥ 21 islets from three animals. **p<0.01, ***p<0.001.
Page 27 of 48 Diabetes
Figure 2. Loss of strict β cell identity in Abcc8-/- mice. We performed β cell lineage tracing
LSL.YFP/+ using Abcc8-/-; RIP-Cre; R26 animals and assessed β cell dedifferentiation at 12 weeks of
age. (A) Representative examples of polyhormonal cells co expressing YFP, PP, and insulin. (B)
Representative examples of YFP labeled cells that are expressing PP but not expressing insulin.
(C) Quantification of PP/YFP double+ cells shows an increase in their occurrence in Abcc8-/-;
LSL.YFP/+ LSL.YFP/+ RIP-Cre; R26 mice compared to Abcc8+/+; RIP-Cre; R26 mice at 12 weeks of
age. N=3 4 animals, 10 15 islets counted per animal. *p<0.05. Scale bar = 5 m.
Figure 3. RNA sequencing of Abcc8-/- β cells. We performed RNA sequencing of FACS
purified β cells from Abcc8-/-; MIP-GFP and Abcc8+/+; MIP-GFP animals at 8 9 weeks of age.
(A) Pie chart showing the percentage of differentially regulated genes that fall into biotype
categories of protein coding, non coding RNA, other RNA, pseudogene, other processed
transcripts, and other types of transcripts. (B) Volcano plot showing the most differentially
-/- expressed genes in Abcc8 ; MIP-GFP β cells based on the log10 (FDR adjusted P value) and
the log2 (fold change). Genes with a log2 (fold change) greater than 3 are labeled and grouped
into categories based on biotype characterization. (C) Selected differentially expressed genes in
Abcc8-/-; MIP-GFP β cells. Abcc8-/-; MIP-GFP β cells exhibit a decrease in expression of genes
associated with β cell maturation/function, an increase in expression of genes associated with
Ca2+ signaling, Ca2+ binding, or Ca2+ dependent gene expression, a decrease in expression of
genes associated with cell adhesion, and an increase in genes that are enriched in a population of
dedifferentiated β cells, as indicated by the fold change in selected genes from our RNA seq
dataset. All genes shown were manually selected and have FDR adjusted p values < 0.05.
Diabetes Page 28 of 48
Figure 4. Heterogeneous expression of S100A6 and ALDH1A3. (A) Co immunostaining of
ALDH1A3, a potent marker of dedifferentiated β cells, and insulin in pancreatic sections from
Abcc8+/+, Abcc8-/-, and Abcc8-/- mice given Verapamil. (B) Quantification of (A) showing the percentage of Insulin and ALDH1A3 co expressing cells in each group. Verapamil treatment partially rescues the percentage of ALDH1A3 expressing β cells in Abcc8-/- mice. (C) Co immunostaining of S100A6 and insulin in Abcc8+/+ and Abcc8-/- pancreatic sections. (D)
Quantification of (C) showing the percentage of Insulin expressing cells that co express S100A6 in Abcc8+/+ and Abcc8-/- mice. (E) Co immunostaining of ALDH1A3 and S100A6 shows that
there is not strict co localization of these two factors, again emphasizing the heterogeneous
nature of β cell failure. Arrows indicate cells that co express ALDH1A3 and S100A6. Scale bar
= 50 m. N=3 animals, 8 12 islets counted per animal. *p<0.05, **p<0.01, ***p<0.001.
Figure 5. S100a6 and S100a4 serve as markers of excitotoxicity in β cells. (A) qRT PCR using whole islet RNA confirms upregulation of S100a6 and S100a4 in Abcc8-/- islets compared
to Abcc8+/+ islets. (B E) qRT PCR using whole islet RNA from wild type islets treated with either 100 M tolbutamide or 20mM KCl with or without 50 M verapamil for 24 hours. S100a6
(B, C) and S100a4 (D, E) are significantly upregulated in response to membrane depolarization, but this effect is negated when Ca2+ influx is blocked. (F, G) qRT PCR using whole islet RNA
from animals administered verapamil (1mg/mL) in the drinking water for 3 weeks indicates that both S100a6 and S100a4 expression is significantly downregulated when Ca2+ influx is inhibited. n.s. = not significant, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
Page 29 of 48 Diabetes
Figure 6. Upstream regulator prediction using iRegulon. Using the top 500 up and down
regulated genes in Abcc8-/- β cells, we utilized iRegulon to predict common upstream regulators
based on enriched DNA binding motifs. (A, B) Tables summarizing the top 3 predicted
regulators of upregulated (A) and downregulated (B) genes, their enrichment scores, and the
number of predicted targets. (C) Expression of the predicted regulators in Abcc8-/- β cells, as
determined by RNA seq. (D) qRT PCR using whole islet RNA confirms upregulation of Ascl1 in
Abcc8-/- islets compared to Abcc8+/+ islets. (E) qRT PCR for Ascl1 using whole islet RNA from
wildtype islets treated with 20mM KCl with or without 50 M verapamil for 24 hours. (F) qRT
PCR using whole islet RNA from animals administered verapamil. n.s. = not significant,
*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.
2+ Figure 7. Model showing the effects of chronically elevated [Ca ]i in the β cell. Our results
suggest that there is a putative gene regulatory network mediating the effects of chronically
2+ 2+ elevated [Ca ]i in the β cell. First, the effects of elevated [Ca ]i may be mediated, at least in
part, through the predicted regulator Ascl1, causing an elevation in Ca2+ dependent gene
2+ expression changes. Second, an elevated [Ca ]i may also contribute to the loss of β cell function
and stable β cell identity, as evidenced by elevation in Aldh1a3 expression as well as the
2+ presence of polyhormonal cells. These effects mediated by chronically elevated [Ca ]i combined
with other metabolic stresses may contribute to β cell failure in T2D.
Diabetes Page 30 of 48
A 11 mM Glucose 2 mM Glucose
-20
-40
-60 Membrane Potential (mV)
1 min -80 B
11 mM Glucose 2 mM Glucose
-20
-40 1 min Membrane Potential (mV) C D -80 60% Abcc8+/+ *** *** Abcc8-/- 50% -70 40% -60 p = 0.102 30% -50 20%
Membrane Potential Membrane 10%
-40 11 mM2 mM to Glucose) 4 4 Membrane Potential (mV) Potential Membrane N=15 N=11 N=10 N=7 0% -30 (% 11 mM Glucose 2 mM Glucose -10% Abcc8+/+ Abcc8-/- E F +/+ -/- 2 mM 11 mM 2 mM 225 Abcc8 Abcc8 1.8 *** ** *** 1.7 200 1.6
1.5 175
1.4 150 1.3
1.2 125 +/+ Area Under the Curve (AU) Areathe Under Curve Relative Calcium (340/380 nm) Calcium Relative Abcc8 1.1 Abcc8-/-
1.0 100 0-2 min 10-12 min 20-22 min 0 300 600 900 1200 1500 (2 mM Glucose) (11 mM Glucose) (2 mM Glucose) Time (sec) Page 31 of 48 Diabetes
Abcc8-/-; RIP-Cre; Rosa26LSL.YFP/+ A B C 3.5% PP 3.0% * YFP YFP 2.5%
DAPI 2.0% 1.5% 1.0% 0.5% total cells total YFP-expressing Insulin
% PP & YFP co-expressing &YFP co-expressing cells/ %PP 0.0% DAPI Diabetes Page 32 of 48 A C Differentially-Expressed Genes by Biotype Specific Categories of Dysregulated Genes
Tcea1Tcea1 Other RNA Pseudogene Other 0.05% 2.09% Fabp3Fabp3 1.21% PenkPenk Enriched in Asb11Asb11 Dedifferentiated ncRNA AassAass Serpina7 β-cells 2.76% Other processed transcripts Serpina7 Aldh1a3Aldh1a3 3.45% Vcam1Vcam1 Pcdhb22Pcdhb22 Pcdh15Pcdh15 Cdhr1Cdhr1 Cdh18Cdh18 Cdh13Cdh13 Cdh8Cdh8 Cdh7Cdh7 Cell Adhesion Cdh1Cdh1 OclnOcln Cldn23Cldn23 Cldn8Cldn8 Cldn3Cldn3 Cldn1Cldn1 Protein-coding Camkk2Camkk2 90.45% Camkk1Camkk1 Camk1dCamk1d Mef2dMef2d Mef2cMef2c B Nfatc1Nfatc1 S100a13S100a13 Ca2+-Binding/ S100a6S100a6 S100a4S100a4 Signaling S100a3S100a3 S100a1S100a1 Cacng3Cacng3 Pcp4Pcp4 Myo7aMyo7a EgfrEgfr Tph2Tph2 Tph1Tph1 Syt14Syt14 Syt13Syt13 Syt10Syt10 β-cell Maturation/ Syt4Syt4 NpyNpy Function Glp1rGlp1r GckGck Neurod1Neurod1 Slc2a2Slc2a2 PpyPpy Ins1Ins1 0.001 0.01 0.1 1 10 100 1000 Fold Change (Abcc8-/-/Abcc8+/+) Log Scale PageA 33 of 48 Diabetes B Abcc8-/- + Insulin/ALDH1A3 Abcc8+/+ Abcc8-/- Verapamil Co-Expressing Cells
40% *** ** * 35%
ALDH1A3 30%
25% expressing cells/ expressing Insulin Insulin - 20% expressing cells expressing - 15%
Total Total Ins 10%
% Ins & AlDH1A3 Co % & AlDH1A3 Ins 5% ALDH1A3 0% Wildtype Knockout Knockout + Verapamil
C Abcc8+/+ Abcc8-/- D Insulin/S100A6 Co-Expressing Cells 50% ** 45% / S100A6 40% cells
cells 35%
Insulin 30% expressing expressing - 25% expressing expressing -
Ins 20%
S100A6 Co S100A6 15% Total Total
Ins & Ins 10% % S100A6 5%
0% Wildtype Knockout E Abcc8-/- ALDH1A3 S100A6 DAPI DAPI Diabetes Page 34 of 48 A Fold Change in B S100a6 Expression in C S100a6 Expression in Abcc8-/- Islets Depolarized Islets Depolarized Islets
100 12 n.s. 5 n.s. 4.5 )
Ct 10 * * ΔΔ - 4 * *
(2 ****
+/+ 3.5 8 3 Abcc8 10 *** 6 2.5
Log Scale Log 2 Change over DMSO over Change Change over Control over Change 4 1.5 Fold Fold Fold Fold 1 2 Fold Change Over Change Fold 0.5 1 0 0 S100a6 S100a4 Control KCl KCl + DMSO Tolbutamide Tolbutamide + Verapamil Verapamil D S100a4 Expression in E S100a4 Expression in F S100a6 Expression in Depolarized Islets Depolarized Islets Verapamil-Treated Mice 60 8 18 ** **** * 7 16 50 ** *** * ** **** * 6 14 + + Splenda 40 12 5 +/+ 10
30 4 Abcc8 8 3 Change over DMSO over Change Change over Control over Change 20 6 2 Fold Fold
Fold Fold 4 10 over Change 1 2 Fold Fold 0 0 0 Control KCl KCl + DMSO Tolbutamide Tolbutamide + Abcc8+/+ + Abcc8-/- + Abcc8-/- + Verapamil Verapamil Splenda Splenda Verapamil G S100a4 Expression in Verapamil-Treated Mice 14 *** 12 **** **
+ + Splenda 10 +/+ 8 Abcc8 6
4
2 Fold Change over Change Fold 0 Abcc8+/+ + Abcc8-/- + Abcc8-/- + Splenda Splenda Verapamil Page 35 of 48 Diabetes A C Regulator Enrichment No. Expression in Abcc8-/- β-cells Score Predicted Targets 100 ASCL1 3.704 271 p=4.68 x 10-30
CEBPG 3.143 199 +/+ 10
RARG 3.062 155 Abcc8 B Regulator Enrichment No. p=0.0007 p=7.35 x 10-6 Score Predicted Log Scale 1 Targets
TEAD1 3.848 52 Change over Fold HNF1A 3.313 70 0.1 ZFP647 3.277 163 Ascl1 Rarg Cebpg Tead1 Hnf1a Zfp647
D Ascl1 Expression in E Ascl1 Expression in F Ascl1 Expression in Whole Islets Depolarized Islets Verapamil-treated Mice 30 6 30 n.s. **** *** 25 5 ** ** 25 +/+ *** * + Splenda + 20 4 20 +/+ Abcc8
15 3 Abcc8 15
10 Change Control over 2 10 Change over Fold Fold over Change Fold Fold 5 1 5 Fold Fold 0 0 0 Abcc8+/+ Abcc8-/- Control KCl KCl + Abcc8+/+ + Abcc8-/- + Abcc8-/- + Verapamil Splenda Splenda Verapamil Diabetes Page 36 of 48
2+ X[Ca ]i
Ascl1
X /2+-dependent X !oZíï Yt-cell function gene expression expression and identity
t-cell failure
Other metabolic stress Page 37 of 48 Diabetes
Online Supplemental Material
Primary antibodies used:
Antibody Species Company Dilution
Aldh1a3 Rabbit Novus Biologicals 1:500
GFP Chicken Invitrogen 1:2000
Glucagon Rabbit Linco 1:1000
Insulin Guinea pig Invitrogen 1:1000
Insulin Rabbit Cell Signaling 1:100
Pancreatic polypeptide Guinea pig Linco 1:1000
Somatostatin Rabbit ICN Biomedicals 1:1000
S100a6 Sheep R&D Systems 1:100
qRT PCR primer sequences:
Gene Forward Primer Reverse Primer
Aldh1a3 5’ GGGTCACACTGGAGCTAGGA 5’ CTGGCCTCTTCTTGGCGAA
Ascl1 5’ GACTTTGGAAGCAGGATGGCA 5’ CACCCCTGTTTGCTGAGAAC
Hprt 5’ TACGAGGAGTCCTGTTGATGTTGC 5’ GGGACGCAGCAACTGACATTTCTA
S100a4 5’ AGCACTTCCTCTCTCTTGGTC 5’ TCATCTGTCCTTTTCCCCAGG
S100a6 5’ CACATTCCATCCCCTCGACC 5’ GTGGAAGATGGCCACGAGAA
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Supplemental Figure 1. Abcc8-/- β cells exhibit oscillations in intracellular Ca2+ at sub stimulatory glucose. (A B) Intracellular Ca2+ was monitored in Abcc8-/- (A) and Abcc8+/+ (B) intact islets with Fura 2 AM at 2mM glucose for 20 minutes. Traces from three representative islets are shown for each genotype. Abcc8-/- islets exhibit oscillations of variable frequency and 2+ +/+ 2+ elevated [Ca ]i, while Abcc8 islets show no oscillatory behavior and low [Ca ]i. Page 39 of 48 Diabetes
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Supplemental Figure 2. Abcc8-/- β cells don’t transdifferentiate to α or δ cells. (A, B) We performed β cell lineage tracing using Abcc8-/-; RIP-Cre; R26LSL.YFP animals and assessed β cell + dedifferentiation at 12 weeks of age. Quantification of YFP/Glucagon double cells (A) or YFP/Somatostatin double+ cells (B) shows no difference in the prevalence of these cells in wild type and knockout mice, suggesting that Abcc8-/- β cells do not transdifferentiate to α or δ cells. N=3 4 animals, 10 15 islets counted per animal. (C) Summary of the total number of YFP and PP double positive, but insulin negative, cells observed in Abcc8+/+; RIP-Cre; R26LSL.YFP and -/- LSL.YFP Abcc8 ; RIP-Cre; R26 animals at 12 weeks of age. (D) Quantification of PP/Insulin double+ cells in frozen pancreatic sections shows a trend towards a decrease in polyhormonal cells in 8 9 week old Abcc8-/- mice after 3 weeks of verapamil administration (p=0.26). However, the difference is not statistically significant. (E) Quantification of the number of YFP positive, hormone negative cells observed in Abcc8+/+; RIP-Cre; R26LSL.YFP and Abcc8-/-; RIP- Cre; R26LSL.YFP animals at 12 weeks of age. N=3 animals per group. *p<0.05, ***p<0.001, n.s. = Not Significant. Page 41 of 48 Diabetes
Supplemental Figure 3. Blood glucose control in Abcc8-/- mice. (A) Results of intraperitoneal glucose tolerance tests on male Abcc8+/+ and Abcc8-/- mice at 12 weeks of age. n=4 10 animals per genotype. Error bars represent standard error. *p<0.05, **p<0.01. (B) Fed blood glucose concentration in a cohort of Abcc8+/+ and Abcc8-/- mice between from 4 to 8 weeks of age showing no statistically significant difference between the groups. n=5 animals per genotype. (C) TUNEL was used to assess β cell death at 12 weeks of age. In Abcc8+/+ islets, no insulin and TUNEL co expressing cells were observed. In Abcc8-/- islets, one insulin and TUNEL co expressing cell was observed. Diabetes Page 42 of 48
Supplemental Figure 4. Principal Component Analysis and Gene Clustering Analysis. (A) FACS profiles of sorted populations from Abcc8+/+; MIP-GFP and Abcc8-/-; MIP-GFP mice indicating that β cells from both genotypes can be purified similarly. (B) Principal component analysis shows that the eight samples used for RNA sequencing cluster by genotype, with some variation in the second principal component. (C) Heat map depicting gene clustering analysis using the top 500 differentially expressed genes. “WT” = Abcc8+/+. “KO” = Abcc8-/-.
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Supplemental Figure 5. Abcc8-/- islets have disrupted islet morphology. (A) Abcc8+/+ islets maintain a clear mantle of α cells while (B) Abcc8-/- islets progressively lose the boundary between mantle and core between 4 and 28 weeks of age. (C I) Cell counting at 4, 12, 20, and 28 weeks of age shows that Abcc8-/- islets have fewer β cells (C), a greater percentage of α cells (D), PP cells (F), and δ cells (H), and an increasing percentage of core α cells (E), core PP cells Diabetes Page 44 of 48
(G) and core δ cells (I). Core cells were defined as being located greater than 2 cell diameters interior from the islet boundary. Green lines represent Abcc8+/+ islets. Blue lines represent Abcc8-/- islets. n=3 4 animals per genotype, 10 15 islets counted per animal. Error bars represent standard error. *p<0.05, **p<0.01, ***p<0.001. Scale bar = 50 m.
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Supplemental Figure 6. iRegulon predicted network of regulators of the top 500 upregulated genes in Abcc8-/- β cells. Map depicting the top 3 predicted regulators (green octagons) and their predicted target genes (magenta circles). A majority of the genes are predicted to be co regulated by two or more regulators. Genes of interest (S100a6, S100a4, and Aldh1a3) are highlighted yellow.
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Supplemental Figure 7. iRegulon predicted network of regulators of the top 500 downregulated genes in Abcc8-/- β cells. Map depicting the top 3 predicted regulators (green octagons) and their predicted target genes (magenta circles).
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Supplemental Table Legends
Supplemental Table 1. Differential expression analysis. Results of differential expression analysis using 4 Abcc8-/-; MIP-GFP and 4 Abcc8+/+; MIP-GFP samples. Genes are identified by MGI Symbol, Ensembl ID, and Entrez gene ID, and are categorized by MGI biotype. Log2[Fold Change (KO vs. WT)], p value (Wald test), and padj (p value adjusted for Benjamini and Hochberg’s False Discovery Rate), and the raw counts for each of the 8 samples are included for each gene.
Supplemental Table 2. Predicted regulators and targets of the top 500 most upregulated genes in Abcc8-/-β cells. Complete list of iRegulon predicted target genes for each of the top 3 regulators (ASCL1, RARG, and CEBPG).
Supplemental Table 3. Predicted regulators and targets of the top 500 most downregulated genes in Abcc8-/-β cells. Complete list of iRegulon predicted target genes for each of the top 3 regulators (TEAD1, HNF1A, and ZFP647).
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Link to Online Supplemental Tables
https://www.dropbox.com/sh/xxe96rmld086gyf/AADUd7WfCsQFTaI5EZvu1hSYa?dl=0