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Chronic βcell depolarization impairs βcell identity by disrupting a network of Ca2+regulated

Jennifer S. Stancill1,2, JeanPhilippe 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 chronicallyelevated βcell [Ca ]i

*Corresponding author

9465 MRBIV 2213 Garland Avenue Nashville, TN 372320494 United States 6153227006 (p) 6153226645 (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 βcell KATPchannel, to analyze the

2+ 2+ effects of a sustained elevation in the intracellular Ca concentration ([Ca ]i) on βcell identity and expression. Lineage tracing analysis revealed the conversion of βcells lacking Abcc8 into PPcells, but not to α or δcells. RNASeq analysis of FACSpurified Abcc8-/- βcells

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 βcell identity, and cell

adhesion. The expression of S100a6 and S100a4, two highly upregulated 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 βcells. Interestingly, among the upregulated genes is Aldh1a3, a putative marker of βcell dedifferentiation, and other genes associated with βcell failure. Taken

2+ -/- together, our results suggest that chronicallyelevated βcell [Ca ]i in Abcc8 islets contributes to the alteration of βcell 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 βcells 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 (13) impair βcell

function are not understood. While metabolic stress is usually considered to be exogenous to the

βcell, chronic stimulation leads to changes within the βcell, impairing function. One such factor

2+ is chronic elevation in [Ca ]i, sometimes called excitotoxicity (4), which may be triggered by

sustained βcell depolarization due to chronic stimulation.

Ca2+ is a ubiquitous second messenger that is central to regulating cellular dynamics of

many cell types, including βcells. Genetic and pharmacological perturbations that either

stimulate or impair Ca2+signaling have dramatic effects on βcell function. For instance, the

disruption of calcineurin, a Ca2+dependent phosphatase, or either CaMKII or CamKIV, two

Ca2+dependent kinases, profoundly impairs βcell function, likely by modulating the activity of

Ca2+responsive transcription factors such as NFAT, CREB, and TORC2 (59). Conversely, the

constitutive activation of calcineurin or calmodulin, a Ca2+binding , also causes marked

βcell dysfunction (3; 10; 11).

Acutely, glucose metabolism induces ATPsensitive potassium (KATP) channel closure,

2+ 2+ membrane depolarization, opening of voltagegated Ca channels, a rise in [Ca ]i, and insulin

2+ secretion. However, sustained elevation in [Ca ]i has multiple effects on βcell function that can

either be adaptive or maladaptive. βcell 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 βcell death (13). In either case, mice lacking KATPchannels

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exhibit disrupted islet morphology, characterized by αcells being located in the islet core (14;

15), suggesting either loss of βcell identity or impairments in cell adhesion.

Here, we show that βcells 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 βcell identity.

We also report that Abcc8-/- mice exhibit βcell to PPcell transdifferentiation and have increased expression of Aldh1a3, a gene recently suggested as a marker of dedifferentiating β cells. Additionally, we show that S100a6 and S100a4, two EFhand Ca2+binding , are acutely regulated in βcells by membrane depolarization agents, suggesting that they may be markers for βcell 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 βcells.

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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 (1618). MIP-GFP mice (Tg(Ins1-

EGFP/GH1)14Hara, MGI: 3583654) were congenic CD1 and genotyped as previously described

(19).

Glucose tolerance testing. Following 16hour fast, male Abcc8+/+ and Abcc8-/- C57BL/6

mice were given intraperitoneal injection of Dglucose (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 8m. Immunofluorescence staining was performed as previously

described (20). Antibodies are listed in the Online Supplemental Material. Images were

acquired using an Olympus FV1000 confocal microscope, pseudocolored 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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Histopaque1077 (Sigma, 10771) followed by handpicking of islets. For fluorescenceactivated cell sorting (FACS) and RNAsequencing, islets from 47 mice were pooled per sample. For quantitative reverse transcription PCR (qRTPCR), islets from a single mouse were used per sample.

Resting membrane potential. Islets were isolated from pancreata of 7 to 10week 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 11week 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, 11966025) containing 5.6mM glucose, 10% FBS (Gibco, 16140071), and 1% penicillinstreptomycin

(Gibco, 15140122). Experimental media contained 100M tolbutamide (Sigma, T0891) or

20mM KCl (Sigma, P5405), with or without 50M verapamil.

Cell isolation. Islets were dissociated in Accumax (Sigma, A7089) containing 10U/mL

DNase (Invitrogen, AM2222). Following filtration (35M 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 1thioglycerol).

RNA purification and quality control. RNA was isolated from FACSpurified βcells 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 FACSpurified βcells

were amplified using SMARTSeq 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). Pairedend sequencing of four replicates each of Abcc8+/+; MIP-GFP and

Abcc8-/-; MIP-GFP samples was performed on an Illumina NextSeq 500 (75nucleotide 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.

qRTPCR. High Capacity cDNA Reverse Transcription Kit (ThermoFisher, 4368814)

was used to convert whole islet RNA to cDNA. qRTPCR 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 twotailed 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 βcells exhibit persistent membrane depolarization and elevated [Ca ]i. Previous studies have shown that single βcells from mice lacking KATPchannels, 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 βcell [Ca ]i, we measured membrane potential at high (11mM) and low (2mM) glucose concentrations (Figure 1A, B).

Abcc8-/- βcells exhibit action potentials in high glucose, but fail to undergo membrane potential polarization in low glucose (Figure 1B). Quantification of the changes in Abcc8-/- βcell membrane potentials confirms that Abcc8-/- βcells show no difference in membrane potential between high and low glucose, contrary to Abcc8+/+ βcells (Figure 1C, D). However, Abcc8-/-

2+ 2+ βcells 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-/- βcells have

2+ +/+ significantly higher [Ca ]i than Abcc8 βcells 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-/- βcells exhibit variable and

2+ 2+ oscillating [Ca ]i under euglycemic conditions, their mean [Ca ]i is elevated compared to

Abcc8+/+ βcells.

2+ -/- Interestingly, despite having chronically elevated βcell [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).

βcell identity becomes compromised in Abcc8-/- mice. During prolonged metabolic

stress, βcells can lose expression of functional markers and convert to other endocrine cell types

(32). However, βcell dedifferentiation has not been studied in the context of chronically

2+ -/- elevated [Ca ]i. Thus, we performed βcell lineage tracing using Abcc8 ; RIP-Cre;

Rosa26LSL.YFP/+ mice. While there was no evidence for either β to αcell or β to δcell trans

differentiation (Supplemental Figure 2A, B), we observed an increase in YFP/PP coexpression

(Figure 2C). Most YFP/PP coexpressing cells are polyhormonal, expressing both PP and

insulin (Figure 2A), but a few cells (0.24% of all YFPexpressing 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 coexpressing cells, but the difference was not significant (Supplemental Figure

2D). The loss of βcell 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

wildtype and knockout animals (0.19% and 0.21%, respectively, Supplemental Figure 2E).

2+ RNA expression profiling. To determine how chronically elevated βcell [Ca ]i affects

gene expression, we performed RNAsequencing using FACSpurified βcells from Abcc8-/-;

MIP-GFP mice at 89 weeks of age. Since the hGH minigene within the MIP-GFP allele causes

both hGH expression and activation of STAT5 signaling (33), we used MIP-GFPexpressing

mice as controls. Principal component and gene clustering analyses (Supplemental Figure 4B,

C), performed on RNASeq data from FACSpurified cells (Supplemental Figure 4A),

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indicates that most of the top 500 differentiallyexpressed genes cluster as expected. Differential expression analysis (Figure 3B, Supplemental Table 1) revealed 4,208 differentiallyexpressed genes (2,152 downregulated and 2,056 upregulated) in Abcc8-/- βcells (adjusted pvalue < 0.05).

Approximately 90% are proteincoding, 3% are noncoding RNAs, 2% are , and 3% are other types of processed transcripts (Figure 3A).

Abcc8-/- βcells exhibit changes in expression of genes involved in βcell maturation,

Ca2+signaling, cell adhesion, and dedifferentiation. To correlate gene expression with the functional abnormalities of Abcc8-/- islets, we examined genes known to be highly enriched in mature βcells and observed that Ins1, Slc2a2, Neurod1, Gck, Glp1r, Npy, several synaptotagmins, Tph1, Tph2, and Egfr are all downregulated (Figure 3C). Conversely, Ppy is upregulated in Abcc8-/- βcells, consistent with our observation of polyhormonal cells.

-/- 2+ Since Abcc8 βcells have a persistent increase in [Ca ]i, we examined genes with well defined roles in Ca2+binding or signaling such as Myo7a, a Ca2+/Calmodulinbinding myosin motor protein, Pcp4, a calmodulinbinding protein known to protect neurons from Ca2+induced toxicity (34), and Cacng3, a subunit of a voltagedependent 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 calciumsignaling; and S100a1, S100a3, S100a4, S100a6, and S100a13, five EFhand calcium binding proteins; were also upregulated (Figure 3C).

Quantitation of islet cell types in Abcc8-/- mice revealed fewer βcells, more α, δ, and

PPcells, and a progressive redistribution of nonβ 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 cadherinrelated

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 βcell

dedifferentiation (35), is 27fold upregulated in Abcc8-/- βcells by RNAseq (Figure 3C). In

addition, six other genes (Serpina7, Aass, Asb11, Penk, Fabp3, and Tcea1) enriched in

dedifferentiated βcells (35) are upregulated in Abcc8-/- βcells (Figure 3C). Coimmunostaining

with insulin indicates that while ALDH1A3 is expressed in only 0.4% of Abcc8+/+ βcells, it is

present in 29.1% of Abcc8-/- βcells (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 βcells. To identify genes that could

serve as markers of βcell excitotoxicity, we analyzed S100a6 and S100a4. Both genes are

appealing targets due to their functions as EFhand 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-/- βcells, with S100a6 and S100a4 increasing 37 and 5fold,

respectively. While S100A6 is only expressed in 2.8% of Abcc8+/+ βcells, it is expressed in

38.4% of Abcc8-/- βcells (Figure 4C, D). Additionally, qRTPCR 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 5BE), mirroring the expression pattern in Abcc8-/- βcells. These changes were reversed when islets were treated with both a depolarizing agent and the Ca2+channel inhibitor verapamil (Figure 5BE). 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 βcells is tightly correlated with [Ca ]i. Finally, coimmunostaining with

S100A6 and ALDH1A3 revealed that 15.4 ± 2.1% of insulinexpressing cells in Abcc8-/- mice express both S100A6 and ALDH1A3 (Figure 4E).

Prediction of upstream regulators. To determine if differentiallyexpressed genes in

Abcc8-/- βcells might share common upstream regulators, we utilized iRegulon, a program that identifies common DNA binding motifs in coexpressed 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-/- βcells (Figure 6C). Conversely, analysis of the top 500 downregulated 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-/- βcells (Figure 6C).

2+ -/- Ascl1 is regulated by [Ca ]i in βcells. Since Ascl1 is 22fold upregulated in Abcc8 ;

MIP-GFP βcells (Figure 3B) and 24fold upregulated in Abcc8-/- islets (Figure 6D), and has

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been shown by ChIPSeq or PCR to bind near 51% of the predicted targets (3840), 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 βcells with chronically elevated [Ca ]i.

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Discussion

-/- 2+ -/- Abcc8 βcells exhibit elevated basal [Ca ]i. Abcc8 βcells have been previously shown to have altered intracellular Ca2+ homeostasis, as would be expected in the absence of

-/- KATPchannels (16; 2730). We similarly observed that Abcc8 βcells exhibit both persistent

2+ +/+ depolarization and an elevated mean [Ca ]i compared to Abcc8 islets (Figure 1).

Interestingly, while Abcc8-/- βcells exhibit Ca2+ oscillations in substimulatory 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 βcells lacking KATP channels. This may be due to the short duration of the recordings, or to our use of patchclamp technique rather than intracellular microelectrodes which limits the detection of oscillations in membrane potential (29). Regardless, Abcc8-/- βcells experience more persistent membrane

2+ depolarization and elevated mean [Ca ]i compared to wildtype βcells, 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 KATPchanneldeficient mice (29).

Abcc8-/- βcells exhibit dysregulated gene expression. By performing RNASeq on purified pancreatic βcell 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+/calmodulindependent 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 5BE 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 chronicallyelevated [Ca ]i, and which are due to other signaling

mechanisms and/or compensatory adaptations.

Compromised βcell identity in Abcc8-/- mice. Recent studies have suggested that βcell

dedifferentiation contributes to the development of T2D (32; 35). Among the genes affected in

Abcc8-/- βcells are many known to be involved in maintaining βcell identity and/or function,

such as Ins1, Slc2a2, Neurod1, Gck, and Syt10 (Figure 3C). However, some of the transcription

factors previously associated with βcell dedifferentiation (32), including Mafa, Pdx1, Nkx6.1,

FoxO1, Ngn3, Oct4, and Nanog, are unchanged. This difference may explain the modest loss of

βcell identity observed in Abcc8-/- mice, with only 2.21% of βcells undergoing trans

differentiation to either INS/PP polyhormonal or PP monohormonal cells (Figure 2C). While

treatment with a Ca2+channel blocker did not statistically reverse the INS/PP polyhormonal

cells, its use resulted in a decrease in the percentage of Abcc8-/- βcells expressing the

dedifferentiation marker ALDH1A3 (Figure 4B), further suggesting that a chronic increase in

2+ [Ca ]i may contribute to loss of βcell identity. In this regard, it is important to distinguish our

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results, which reflect the loss of KATPchannels, from studies using KATPchannel gainof

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 upregulated in Abcc8-/- βcells and were also acutely regulated by treatment with depolarizing agents and a Ca2+channel blocker in isolated islets

(Figure 5BE). 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 βcell, and that they may serve as markers for βcell 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 βcells 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+ KATPchannel 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 downregulated 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 celltocell 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 βcell mass

(51). Finally, CEBPB, a closely related protein to CEBPG, represses the insulin promoter under

conditions of chronicallyelevated glucose, and its accumulation in βcells 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 ChIPSeq or PCR (3840; 54). Importantly, S100a4 is among the ASCL1

targets that have been experimentally validated (3840), and our indepth analysis of Ascl1

2+ strongly supports its regulation by [Ca ]i, consistent with our model. Conversely, analysis of

2+ genes that are downregulated by [Ca ]i predicts binding sites for TEAD1, HNF1A, and ZFP647

(Figure 6B). Although Tead1 gene expression is unaffected in Abcc8-/- βcells, 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 knockout of Hnf1a results in βcell

failure and diabetes (56), a predicted decrease in its activity could explain the decrease in genes

involved in βcell function in Abcc8-/- βcells.

Does excitotoxicity contribute to βcell failure? Our studies, together with findings of

-/- others (15; 16; 2730), indicate that the absence of functional KATPchannels in Abcc8 mice

2+ causes a chronic elevation of βcell [Ca ]i, an impairment of βcell identity, alterations in islet

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cell numbers and morphology, and very significant perturbations in βcell gene expression.

2+ -/- While the elevation of [Ca ]i in Abcc8 βcells, due to the total absence of KATPchannels, is

2+ persistent and severe, a less severe or persistent elevation in mean [Ca ]i may also occur in patients with prediabetes 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

timeframe studied here. This suggests that the impairments in βcell identity and islet

morphology are insufficient themselves to cause βcell failure. However, βcell excitotoxicity,

acting in combination with other metabolic stresses, may accelerate the loss of functional βcells, perhaps by dedifferentiation or glucolipotoxicity. Regardless, our findings provide new insights

into transcriptional responses that occur within βcells 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 βcell function and mass.

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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. JP.C. performed RNASeq 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.

RNASeq data are available in ArrayExpress (www.ebi.ac.uk/arrayexpress) under accession

number EMTAB4726.

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 RNAsequencing, 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 paraffinembedded

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

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Diabetes Page 26 of 48

Figure Legends

-/- 2+ Figure 1. Abcc8 βcells exhibit persistent membrane depolarization and elevated [Ca ]i. A perforated patch recording technique was employed to monitor the membrane potential of

Abcc8+/+ and Abcc8-/- βcells in whole islets. (A) Abcc8+/+ βcells display normal activity at

11mM glucose and become hyperpolarized in response to 2mM glucose (representative

recording). (B) Abcc8-/- βcells display activity similar to Abcc8+/+ βcells 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-/- βcells at 11mM and 2mM glucose. Abcc8+/+ βcells become

significantly more polarized in response to 2mM glucose while there is no difference between

Abcc8-/- βcells at 11mM and 2mM glucose. (D) Quantification of the percent change in membrane potential between 11mM and 2mM glucose for Abcc8+/+ and Abcc8-/- βcells. The membrane potential of Abcc8+/+ βcells changes significantly more than Abcc8-/- βcells. (E)

Intracellular Ca2+ was monitored in Abcc8+/+ and Abcc8-/- islets with Fura2 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 (02 min),

glucosestimulation (1012 min), and a return to low glucose (2022 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 βcell identity in Abcc8-/- mice. We performed βcell lineage tracing

LSL.YFP/+ using Abcc8-/-; RIP-Cre; R26 animals and assessed βcell dedifferentiation at 12 weeks of

age. (A) Representative examples of polyhormonal cells coexpressing YFP, PP, and insulin. (B)

Representative examples of YFPlabeled 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=34 animals, 1015 islets counted per animal. *p<0.05. Scale bar = 5m.

Figure 3. RNAsequencing of Abcc8-/- βcells. We performed RNAsequencing of FACS

purified βcells from Abcc8-/-; MIP-GFP and Abcc8+/+; MIP-GFP animals at 89 weeks of age.

(A) Pie chart showing the percentage of differentiallyregulated genes that fall into biotype

categories of proteincoding, noncoding RNA, other RNA, , other processed

transcripts, and other types of transcripts. (B) Volcano plot showing the most differentially

-/- expressed genes in Abcc8 ; MIP-GFP βcells based on the log10 (FDRadjusted Pvalue) 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 differentiallyexpressed genes in

Abcc8-/-; MIP-GFP βcells. Abcc8-/-; MIP-GFP βcells exhibit a decrease in expression of genes

associated with βcell 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 βcells, as indicated by the fold change in selected genes from our RNAseq

dataset. All genes shown were manually selected and have FDRadjusted pvalues < 0.05.

Diabetes Page 28 of 48

Figure 4. Heterogeneous expression of S100A6 and ALDH1A3. (A) Coimmunostaining of

ALDH1A3, a potent marker of dedifferentiated βcells, and insulin in pancreatic sections from

Abcc8+/+, Abcc8-/-, and Abcc8-/- mice given Verapamil. (B) Quantification of (A) showing the percentage of Insulin and ALDH1A3 coexpressing cells in each group. Verapamil treatment partially rescues the percentage of ALDH1A3expressing βcells in Abcc8-/- mice. (C) Co immunostaining of S100A6 and insulin in Abcc8+/+ and Abcc8-/- pancreatic sections. (D)

Quantification of (C) showing the percentage of Insulinexpressing cells that coexpress S100A6 in Abcc8+/+ and Abcc8-/- mice. (E) Coimmunostaining of ALDH1A3 and S100A6 shows that

there is not strict colocalization of these two factors, again emphasizing the heterogeneous

nature of βcell failure. Arrows indicate cells that coexpress ALDH1A3 and S100A6. Scale bar

= 50m. N=3 animals, 812 islets counted per animal. *p<0.05, **p<0.01, ***p<0.001.

Figure 5. S100a6 and S100a4 serve as markers of excitotoxicity in βcells. (A) qRTPCR using whole islet RNA confirms upregulation of S100a6 and S100a4 in Abcc8-/- islets compared

to Abcc8+/+ islets. (BE) qRTPCR using whole islet RNA from wild type islets treated with either 100M tolbutamide or 20mM KCl with or without 50M 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) qRTPCR 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-/- βcells, 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-/- βcells, as

determined by RNAseq. (D) qRTPCR using whole islet RNA confirms upregulation of Ascl1 in

Abcc8-/- islets compared to Abcc8+/+ islets. (E) qRTPCR for Ascl1 using whole islet RNA from

wildtype islets treated with 20mM KCl with or without 50M 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 βcell. Our results

suggest that there is a putative gene regulatory network mediating the effects of chronically

2+ 2+ elevated [Ca ]i in the βcell. 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 βcell function

and stable βcell identity, as evidenced by elevation in Aldh1a3 expression as well as the

2+ presence of polyhormonal cells. These effects mediated by chronicallyelevated [Ca ]i combined

with other metabolic stresses may contribute to βcell 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

qRTPCR 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-/- βcells exhibit oscillations in intracellular Ca2+ at sub stimulatory glucose. (AB) Intracellular Ca2+ was monitored in Abcc8-/- (A) and Abcc8+/+ (B) intact islets with Fura2 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

Diabetes Page 40 of 48

Supplemental Figure 2. Abcc8-/- βcells don’t transdifferentiate to α or δcells. (A, B) We performed βcell lineage tracing using Abcc8-/-; RIP-Cre; R26LSL.YFP animals and assessed βcell + 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-/- βcells do not transdifferentiate to α or δcells. N=34 animals, 1015 islets counted per animal. (C) Summary of the total number of YFP and PP doublepositive, but insulinnegative, 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 89weekold 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, hormonenegative 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=410 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 βcell death at 12 weeks of age. In Abcc8+/+ islets, no insulin and TUNEL coexpressing 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 βcells from both genotypes can be purified similarly. (B) Principal component analysis shows that the eight samples used for RNAsequencing cluster by genotype, with some variation in the second principal component. (C) Heat map depicting gene clustering analysis using the top 500 differentiallyexpressed 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 αcells while (B) Abcc8-/- islets progressively lose the boundary between mantle and core between 4 and 28 weeks of age. (CI) Cell counting at 4, 12, 20, and 28 weeks of age shows that Abcc8-/- islets have fewer βcells (C), a greater percentage of αcells (D), PPcells (F), and δcells (H), and an increasing percentage of core αcells (E), core PPcells Diabetes Page 44 of 48

(G) and core δcells (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=34 animals per genotype, 1015 islets counted per animal. Error bars represent standard error. *p<0.05, **p<0.01, ***p<0.001. Scale bar = 50m.

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Supplemental Figure 6. iRegulonpredicted network of regulators of the top 500 upregulated genes in Abcc8-/- βcells. 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 coregulated by two or more regulators. Genes of interest (S100a6, S100a4, and Aldh1a3) are highlighted yellow.

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Supplemental Figure 7. iRegulonpredicted network of regulators of the top 500 downregulated genes in Abcc8-/- βcells. 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 gene ID, and are categorized by MGI biotype. Log2[Fold Change (KO vs. WT)], pvalue (Wald test), and padj (pvalue 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-/-βcells. Complete list of iRegulonpredicted 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-/-βcells. Complete list of iRegulonpredicted 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