# The MafA-target gene PPP1R1A regulates GLP1R-mediated amplification of glucose-stimulated insulin secretion in β-cells

Luis Rodrigo Cataldo, Neelanjan Vishnu, Tania Singh, Ludivine

Bertonnier-Brouty, Sara Bsharat, Cheng Luan, Erik Renström, Rashmi B

Prasad, Malin Fex, Hindrik Mulder, et al.

► To cite this version:

Luis Rodrigo Cataldo, Neelanjan Vishnu, Tania Singh, Ludivine Bertonnier-Brouty, Sara Bsharat, et al.. The MafA-target gene PPP1R1A regulates GLP1R-mediated amplification of glucose-stimulated insulin secretion in β-cells. Metabolism, 2021, 118, pp.154734. 10.1016/j.metabol.2021.154734. hal-04973822

HAL Id: hal-04973822

https://hal.science/hal-04973822v1

Submitted on 3 Mar 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

# The MafA-target gene PPP1R1A regulates GLP1R-mediated amplification of glucose-stimulated insulin secretion in β-cells

<figure><img src="image_3.png" /></figure>

Check for
updates

Luis Rodrigo Cataldo<sup>a,b,*†</sup>, Neelanjan Vishnu<sup>b,‡</sup>, Tania Singh<sup>a,b</sup>, Ludivine Bertonnier-Brouty<sup>a,b</sup>, Sara Bsharat<sup>a,b</sup>,
Cheng Luan<sup>b</sup>, Erik Renström<sup>b</sup>, Rashmi B. Prasad<sup>b,c</sup>, Malin Fex<sup>b,‡</sup>, Hindrik Mulder<sup>b,‡</sup>, Isabella Artner<sup>a,b,*</sup>

## ARTICLE INFO

Article history:

Received 29 October 2020

Accepted 15 February 2021

Keywords:

β-cells

GLP1R

Mitochondrial function

Insulin secretion

Type 2 diabetes

MafA

PPP1R1A

INS1 (832/13) β-cells

incretins

## ABSTRACT

The amplification of glucose-stimulated insulin secretion (GSIS) through incretin signaling is critical for maintaining physiological glucose levels. Intcretins, like glucagon-like peptide 1 (GLP1), are a target of type 2 diabetes drugs aiming to enhance insulin secretion.

Here we show that the protein phosphatase 1 inhibitor protein 1A (PPP1R1A), is expressed in β-cells and that its expression is reduced in dysfunctional β-cells lacking MafA and upon acute MafA knock down. MafA is a central regulator of GSIS and β-cell function. We observed a strong correlation of MAFA and PPP1R1A mRNA levels in human islets, moreover, PPP1R1A mRNA levels were reduced in type 2 diabetic islets and positively correlated with GLP1-mediated GSIS amplification. PPP1R1A silencing in INS1 (832/13) β-cells impaired GSIS amplification, PKA-target protein phosphorylation, mitochondrial coupling efficiency and also the expression of critical β-cell marker genes like MafA, Pdx1, NeuroD1 and Pax6. Our results demonstrate that the β-cell transcription factor MafA is required for PPP1R1A expression and that reduced β-cell PPP1R1A levels impaired β-cell function and contributed to β-cell dedifferentiation during type 2 diabetes. Loss of PPP1R1A in type 2 diabetic β-cells may explains the unresponsiveness of type 2 diabetic patients to GLP1R-based treatments.

© 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

## 1. Introduction

Diabetes mellitus results from a chronic imbalance in glucose homeostasis. This is caused by a decrease in functional pancreatic β-cell mass resulting in reduced physiological insulin secretion due to β-cell dysfunction and/or decline in β-cell number. Loss of β-cell function is

caused by reduced glucose sensing, insulin production and/or secretion. Recent reports show that β-cell dedifferentiation significantly contributes to the decline in β-cell function and mass [1].

β-cell function and identity is regulated by islet-enriched transcription factors like MafA and MafB which activate the transcription of genes involved in glucose sensing, insulin production and secretion as well as in β-cell development [2–4]. Type 2 diabetes and the accompanying chronic hyperglycemia result in limited MafA expression, and consequently, compromised β-cell function, insulin secretion, and ultimately β-cell dedifferentiation [1,5]. Recent studies have demonstrated that mutations in the MAFA gene are causing mature onset diabetes of the young [6] further highlighting the importance of MAFA in human β-cell function. MAFA expression is restricted to maturing β-cells in mice [7] and only detected from the juvenile period in humans [8], while the closely related MAFB transcription factor is present in developing and adult human β-cells [8]. Identification of MafA target genes provides an opportunity to better understand β-cell maturation and function.

Amplification of glucose-stimulated insulin secretion (GSIS) by incretins like GLP-1 is instrumental for maintaining glucose homeostasis in response to food intake. GLP-1 activates the G-protein coupled receptor GLP1R which results in Gαs/cAMP/PKA signaling [9,10] leading to sensitization of ATP-dependent K⁺ channels, activation of voltage-

**Abbreviations:** CREB, cAMP responsive element binding protein; FCCP, Carbonyl cyanide *p*-trifluoromethoxyphenylhydrazone; GIP, Glucose-dependent insulinotropic polypeptide; GLP1R, Glucagon-like peptide 1 receptor; GSIS, Glucose-stimulated insulin secretion; IBMX, 3-isobutyl-1-methylxanthine; MAFA, MAF BZIP Transcription Factor A; MAFB, MAF BZIP Transcription Factor B; PDX1, Pancreatic Duodenal transcription factor 1; MMP, Mitochondrial Membrane Potential; ND, non-diabetic; OCR, Oxygen Consumption Rate; PDL, Poly-α-lysine; PKA, Protein Kinase A; PP1, protein phosphatase 1; PPP1R1A, Protein Phosphatase 1 Regulatory Inhibitor Subunit 1A; ROI, Region of Interest; SI, Stimulatory Index.

* Corresponding authors at: CRC 91-12-020 (Floor 12), Jan Waldenströms gata 35, SE-21428 Malmö, Sweden.

**E-mail addresses:** rodrigo.cataldo@med.lu.se (L.R. Cataldo), isabella.artner@med.lu.se (I. Artner).

¹ Present address: The Novo Nordisk Foundation Centre for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, DK-2200 Denmark

² Present address: Division of Diabetes and Endocrinology, Children's Hospital of Philadelphia, University of Pennsylvania.

<footnote>ª Endocrine Cell Differentiation and Function group, Stem Cell Centre, Lund University, Sweden</footnote>

<footnote>ᵇ Lund University Diabetes Centre, Clinical Research Center, Sweden</footnote>

<footnote>ᶜ Department of Clinical Sciences in Malmö, Sweden</footnote>
dependent Ca²⁺ channels, and enhanced glucose-stimulated mitochondrial ATP production [11,12]. These mechanisms are critical for β-cell function and the target of several type 2 diabetes drugs that aim to improve β-cell function [13,14]. Unfortunately, up to 60% of patients are unresponsive to these treatments for not completely understood reasons resulting in an urgent need to better understand the intracellular signaling pathways used by this receptor [15-18].

Here we show that PPP1R1A, a protein regulating PKA signaling pathways, is lost in mouse *MafA* knockout β cells and upon *MafA* knock down in INS1 (832/13) β-cells. Acute PPP1R1A knockdown in INS 832/13 β-cells reduced GLP1-mediated GSIS and impaired mitochondrial metabolism, demonstrating that PPP1R1A is contributing to β-cell function. A prolonged PPP1R1A knock down in INS 832/13 β-cells had a profound impact on both GLP1-mediated and glucose-stimulated insulin secretion, and also impaired expression of islet transcription factors (e.g. MafA, Pdx1, NeuroD1, and Pax6) and β-cell function genes. Moreover, PPP1R1A expression was reduced in INS 832/13 β-cells subjected to hyperglycemia, as well as in human type 2 diabetic islets suggesting that reduced PPP1R1A expression in type 2 diabetic islets is contributing to loss of β-cell function and identity.

## 2. Research design and methods

### 2.1. Cell culture

INS1 (832/13) β-cells were cultured as previously described [19] and frequently tested for mycoplasma contamination. For Glucotoxic experiments; cells were transfected with NC or *PPP1R1A* siRNA (10 nM) and 48 h later treated with normal glucose (NG, 11.2 mM) or high glucose (HG, 30 mM) RPMI medium for another 48 h.

### 2.2. Insulin secretion

INS1 (832/13) β-cells were starved in SAB buffer (0.2% BSA, pH 7.2.) with low glucose (LG, 2.8 mM). Cells were stimulated for 1 h with SAB buffer with LG, high glucose (HG, 16.7 mM) or HG + IBMX (100 µM). Insulin concentration in supernatants was measured using insulin ELISA.

### 2.3. Viability/apoptosis assays

Cell viability, cytotoxicity and apoptosis were measured using ApoTox-Glo triple assay kit (Promega. code (c): G6320) according to manufacturer's instructions.

### 2.4. Lentiviral transduction and GSIS of human islets

Human pancreatic islets from non-diabetic donors (n = 4, OSM Table 1) were obtained through the EXODIAB network via the Nordic Network for Islet Transplantation and cultured as previously described [20]. All procedures were approved by Swedish authorities.

pLKO-PPP1R1A-shRNA (TRC, c: 367479) was obtained from the Broad Institute shRNA library [21]. Islets were transduced with pLKO-PPP1R1A-shRNA or mock lentiviral particles to reach an MOI of 2 (1000 cells/islets were considered for MOI calculation). Islets were incubated for 72 h prior to RNA extraction/GSIS assays. After transduction, islets (10 islets/well/ condition, 6 replicates) were starved for 1 h in SAB buffer, LG (1 mM) and stimulated for 1 h with SAB buffer LG (2.8 mM), HG (16.7 mM), HG + Exendin-4 (100 nM). Insulin concentration was measured by ELISA.

### 2.5. Mitochondrial oxygen consumption measurements

Mitochondrial oxygen consumption rate (OCR) was evaluated with an XF24 extracellular flux analyzer. INS1 (832/13) β-cells were transfected with scramble (negative control, NC) or PPP1R1A siRNA (10 nM, c: s133051, ThermoScientific) with RNAi-Max Lipofectamine and cultured for 72 h. Cells were starved for 2 h and OCR was measured

every 3 min for 90 min. OCR was measured in LG (2.8 mM glucose) and HG (16.7 mM) with DMSO (vehicle) or IBMX (100 µM), and subsequently in 4 µM oligomycin, 4 µM Carbonyl cyanide *p*-trifluoromethoxyphenylhydrazone (FCCP), and 1 µM Rotenone/ Antimycin A. Wave Seahorse Software was used to analyze data. Non-mitochondrial respiration was subtracted and OCR data normalized to basal OCR.

### 2.6. Animals

*MafA* floxed (*MafA*<sup>fl/fl</sup>) mice were crossed with Sox2-Cre or RIP-Cre mice to obtain total *MafA* [22] or β-cell-specific [23] *MafA* deletion. Mice were maintained on C57BL/6 background and housed in colony cages (3-5/cage) in a 12 h light/dark cycle with controlled humidity and temperature and free access to standard diet and water. Animal procedures were approved by the Swedish authorities.

### 2.7. Islets isolation

Pancreatic islets were isolated from 16 to 20 weeks old *MafA*<sup>fl/fl</sup> and *MafA*<sup>RIP</sup> mice (24-30 g) [24]. Protein was extracted with RIPA buffer (ratio islets/µl of 1/1), sonication and centrifugation.

### 2.8. mRNA analysis

Total RNA was extracted using an adapted protocol combining Trizol-Choloroform and RNeasy Mini Kit and cDNA was generated [25]. 10 ng cDNA/well (in duplicates) was used for qPCR (see primers details in OSM Table 2). qPCR assays were performed using StepOnePlus Real-Time PCR System. Relative gene abundance was calculated using the ΔΔCt method with β-ACTIN and *HPRT1* as housekeeping genes and expressed as FC to control.

### 2.9. RNA sequencing and data analysis

Islet RNA was processed for cDNA library preparation with TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat kit (Illumina) and sequenced using NextSeq® 500/550 High Output Kit v2 (150 cycles) (Illumina). Quality assessment was made pre- and post-sample preparation on a 2100 Bioanalyzer (Agilent). Output reads were aligned to the mouse reference genome (GRM38.75) using STAR v2.4.1 [26]. The dexseq_count python script was used by counting uniquely mapped reads in each exon [27]. Gene and exon expression normalizations were then performed using the TMM method, log-transformed and comparisons between groups were made using exactTest in edgeR [28]. Data were analyzed to yield Log-FC, FDR and *P* values.

### 2.10. Immunohistochemistry

Pancreata from 2- to 3-month-old wild-type and mutant mice, human non-diabetic (ND) and type 2 diabetic donors were processed for paraffin embedding. Immunohistochemical analysis was performed as described previously [29]. Primary antibodies: PPP1R1A (1:1000, Origene), Insulin (1:2000; Dako), Glucagon (1:2000; Sigma), MafA (1:1000, Bethyl laboratories). Secondary antibodies used were Cy2-, Cy3-, and Cy5- conjugated anti-guinea pig, goat, and rabbit (1:500; Jackson ImmunoResearch). Antibody dilutions for immunocytochemistry were: PPP1R1A 1:250; MafA 1:500; Pdx1 1:5000 (Abcam); with the following secondary antibodies Alexa 488 affinipure goat anti-rabbit IgG F(ab')2; Alexa 594 affinipure goat anti-rabbit IgG F(ab')2, and anti-goat Cy5 (1:500, Jackson Immunoresearch). Nuclear counterstaining was performed using DAPI (1:6000).
## 2.11. Mitochondrial Membrane Potential (MMP)

Single cell MMP was measured using the membrane potential sensitive Tetramethylrhodamine Methyl Ester (TMRM) dye in quench mode [30] with a fall in MMP resulting in a transient increase in whole-cell fluorescence [31]. Cells were transfected with NC or PPP1R1A siRNA (10 nM). Fluorescence emission in response to indicated stimuli was recorded for 20 min/well, scan time of 3.93 s (frequency 0.25 Hz).

## 2.12. Cytosolic ATP:ADP ratio

Single cell cytosolic ATP/ADP ratio measurements were performed using the genetically encoded biosensor PercevalHR [32] and pHrodo Red AM, intracellular pH indicator (c: p35372, Life Technologies). Cells were co-transfected with NC or PPP1R1A siRNA (10 nM) and 1 µg PercevalHR plasmid (c:49083, Addgene). Cells were starved for 2 h in SAB low glucose and preincubated for 1 h with pHrodo Red AM (diluted 1/1000). PercevalHR fluorescence was recorded by laser ex./em. at 490/ 530 nm and normalized to the pHrodo Red AM fluorescence emission (560/585 nm) on a Zeiss LSM510 confocal microscope for 30 min/well (scan time of 7.86 s).

## 2.13. Western blot analysis

Western blot analysis with cells/islets was performed as previously described [24] with the following antibodies (OSM Table 3). Band density for target proteins was normalized against total protein load and analyzed using Image Lab software.

## 2.14. Statistical analysis

Data are shown as mean ± SEM of at least 4 independent experiments. Student's t-test or one-way ANOVA were used for single or multiple comparisons, respectively. Statistical significance was set at *p* < 0.05. Prism 8.0 (Graph Pad) was used for statistical analysis and graph generation.

# 3. Results

## 3.1. MAFA is required for PPP1R1A expression in β-cells

Previous studies have demonstrated that loss of MafA impairs GSIS [2]. RNAseq analysis of wild type and total MafA knock out mouse islets was first performed to identify MafA target genes regulating β-cell function. MafA mutant islets had reduced expression of several known [3,4], but also not previously identified MafA target genes (Pcsk1-2, Slc2a1, Slc14a2, Tac1, PPP1R1A; Fig. 1A, B). Among these, PPP1R1A has been previously found to be down regulated in human type 2 diabetic islets [20,33]. PPP1R1A mRNA levels were significantly reduced in MafA<sup>−/−</sup> mice islets (Fig. 1B, *p* = 6.15 × 10<sup>−11</sup>) suggesting that MAFA regulates PPP1R1A expression.

To determine if loss of MafA in β-cells affects PPP1R1A expression, PPP1R1A expression levels were analyzed in β-cell-specific MafA mutant (MafA<sup>RIP</sup>) pancreatic sections [23]. Immunohistochemical analysis showed that PPP1R1A was expressed in wild type, but not MafA<sup>RIP</sup> β-cells (Fig. 1C). Downregulation of PPP1R1A protein levels in MafA<sup>RIP</sup> islets was confirmed by Western blot (OSM Fig. 1A).

To assess if the reduction in PPP1R1A expression in MafA mutant islets was a direct effect of MafA loss, MafA was acutely silenced in INS1

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Regulation of PPP1R1A expression in MafA mutant β-cells. (A) Expression of β-cell genes in 8 months old wild type (WT) and MafA<sup>−/−</sup> islets. Heat maps were generated using Log-CPM values. Color gradient (bottom) represents expression of each gene/sample (red = highest expression (Max); deep blue = lowest expression (Min); white = intermediate expression). Last row in heatmap shows MafA expression. (B) Box plot of PPP1R1A expression in WT and MafA<sup>−/−</sup> islets. N = 4 mice/genotype. (C) Immunostaining of PPP1R1A (red), Insulin (green) and Glucagon (blue) in MafA<sup>RIP</sup> and MafA<sup>RIP</sup> pancreatic sections (scale bar = 50 µm). (D) Immunoblot of PPP1R1A and MafA in INS1 (832/13) β-cells 72 h after transfection with scramble and MAFA siRNA (upper panel) and densitometric analysis for PPP1R1A protein levels in control and MAFA KD INS1 (832/13) β-cells (bottom panel). (E) Spearman's rank correlation analysis of PPP1R1A and MAFA (*r* = 0.38, *p* < 0.0001, *n* = 189) (F) or MAFB (*r* = 0.67, *p* < 0.0001, *n* = 190) mRNA levels in human islets. \* *p* < 0.05 by unpaired student's t-test.</figcaption></figure>
(832/13) β-cells and PPP1R1A protein levels were assessed. siRNA treatment reduced MafA expression by 42% (Fig. 1D and OSM Fig. 1B; *p* < 0.001). PPP1R1A protein levels were reduced by 28% in MafA siRNA-treated β-cells (Fig. 1D, *p* = 0.019) suggesting that reduced MafA expression directly affects PPP1R1A expression levels in β-cells. To evaluate if the relationship between MAFA and PPP1R1A gene expression was conserved in human β-cells, correlational analysis between MAFA, MAFB, and PPP1R1A levels was performed. A strong correlation between MAFA and PPP1R1A mRNA levels was observed (Fig. 1E). ChIPseq analysis showed binding of islet transcription factors MAFB, PDX1, NKX2.2, FOXA2 and NKX6.1 to the upstream region of the PPP1R1A gene in human islets [34] suggesting that PPP1R1A transcription is strongly promoted in islet cells. Unlike mouse, adult human β-cells also express the related MAFB transcription factor and we show that MAFB, as well as PDX1, NEUROD1 and PAX6 expression is highly correlated with PPP1R1A mRNA levels in human islets (Fig. 1F, OSM Fig. 1C-E). Moreover, siRNA knockdown of MAFA and MAFB in human islets resulted in a 27% decrease of PPP1R1A mRNA levels (OSM Fig. 1F). These results suggest that PPP1R1A expression is dependent on MafA/B expression levels in rodent and human β cells and contributes to MafA/B's regulation of GSIS and β-cell function.

## 3.2. PPP1R1A expression is reduced in type 2 diabetic human donor islets and positively correlated with GLP1-mediated GSIS

Our results showed that PPP1R1A expression is reduced in MafA deficient β-cells and its expression is highly correlated with MAFA and MAFB expression in human islets, next we investigated if PPP1R1A

expression was also altered in islets from type 2 diabetic donors and associated with GSIS in human islets.

Immunohistochemical analysis detected PPP1R1A expression in β-cells from ND donors, while protein and mRNA expression was severely reduced in islets from type 2 diabetic donors (Fig. 2A, B, *p* < 0.0001). To determine if PPP1R1A expression in pancreatic islets was associated with glycemic control and metabolic status (obese vs. lean), the correlation between islet PPP1R1A mRNA levels, HbA1c, and BMI was analyzed. Remarkably, we found a strong negative correlation between PPP1R1A mRNA levels, HbA1c (Fig. 2C. *p* < 0.0001), and BMI (Fig. 2D, E. *p* < 0.0080). A similar negative correlation was observed between MAFA/MAFB and HbA1c and BMI (Fig. 2 G-O), while the loss of MAFA, MAFB, and PPP1R1A expression with donor age was less pronounced (Fig. 2F, K, P).

To further evaluate if reduced PPP1R1A mRNA levels were associated with β-cell dysfunction in type 2 diabetes, we analyzed PPP1R1A mRNA levels in the ND donor group. Considering that overweight/obese people may be at higher risk to develop type 2 diabetes compared to leaner people, ND donors were separated into two subgroups; donors with BMI < 27 kg/m² (normal weight) and with BMI > 27 kg/m² (overweight/obese). We observed that PPP1R1A mRNA levels were lower in the overweight subgroup of ND donors (Fig. 2E, *p* = 0.0017). The negative correlation between islet PPP1R1A mRNA levels and donor BMI was preserved upon separating donors by diabetic status or sex (OSM Fig. 2A-D).

To gain insight into a potential role of PPP1R1A in human β-cell function and insulin secretion, we evaluated the association between islet PPP1R1A mRNA levels and *in vitro* functional parameters such as

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Correlation between PPP1R1A, MAFA and MAFB mRNA levels and metabolic parameters. (A) Immunostaining of PPP1R1A in pancreatic islets from type 2 diabetic and normoglycemic donors (bar = 20 µm). (B) PPP1R1A mRNA levels in type 2 diabetic (n = 31) and non-diabetic (ND, n = 160) donor islets, \*\*\*\* *p* < 0.0001. (C–D) Rank-Spearman correlation analysis of PPP1R1A mRNA levels with: (C) HbA1c (mmol/mol) (*r* = −0.43, *p* < 0.0001, n = 173), (D) BMI (*r* = −0.191, *p* = 0.008, n = 191). (E) PPP1R1A mRNA levels in islets from lean (BMI < 27, n = 107) and overweight/obese (BMI > 27, n = 51) ND donors. \*\*\* *p* = 0.0017. (F) PPP1R1A mRNA levels in human islets stratified by donor age, \* *p* < 0.05. (G) MAFA mRNA levels in islets from ND and T2D donors and in (H) lean (BMI < 27, n = 107) and overweight/obese (BMI > 27, n = 51) ND donors. (I-J) Rank-Spearman correlation analysis of MAFA mRNA levels with (I) BMI and (J) HbA1c. (K) MAFA mRNA levels in human islets stratified by donor age. (L) MAFB mRNA levels in islets from ND and T2D donors and in (M) lean (BMI < 27, n = 107) and overweight/obese (BMI > 27, n = 51) ND donors. (N–O) Rank-Spearman correlation analysis of MAFB mRNA levels with (N) BMI and (O) HbA1c. (P) MAFB mRNA levels in human islets stratified by donor age. \* *p* < 0.05, \*\*\* *p* < 0.01. Data are mean ± SEM. (B, F, G, H, K, L, M, P) Student's t-test followed by a Mann-Whitney post hoc test. (F, K, P) one-way ANOVA.</figcaption></figure>
stimulatory index values (insulin secretion in response to high vs. low glucose (SI)), GSIS and insulin secretion in response to glucose with glucose-dependent insulinotropic polypeptide (GIP) or GLP1. A significant positive correlation between PPP1R1A mRNA levels and SI (Fig. 3A), GSIS (Fig. 3B) and a stronger correlation with insulin secretion in response to glucose+GIP (Fig. 3C) and glucose+GLP1 (Fig. 3D) was found. GLP1 stimulated insulin secretion is not significantly affected by aging (OSM Fig. 2E).

To evaluate if reduced PPP1R1A expression directly affected GSIS and GLP1-mediated amplification of GSIS, PPP1R1A was knocked down in human islets. PPP1R1A mRNA levels were moderately, but significantly

reduced following PPP1R1A-shRNA lentiviral transduction (Fig. 3E) in human islets. Reduced PPP1R1A expression impaired GSIS and Exendin4-promoted GSIS (Fig. 3F).

Our results suggest that PPP1R1A is required for physiological insulin secretion in response to glucose and GLP1 signaling in human islets.

### 3.3. PPP1R1A contributes to IBMX-promoted insulin secretion and PKA-target phosphorylation in INS1 (832/13) β-cells

Activation of Gαs-protein-coupled receptors promotes increased cAMP accumulation/PKA activity, which results in PPP1R1A

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Correlations between PPP1R1A mRNA levels and insulin secretion. PPP1R1A mRNA levels correlated to (A) Stimulatory index ($r = 0.235, p = 0.0013, n = 191$); (B) insulin secretion in response to glucose ($r = 0.187, p = 0.022, n = 149$), (C) glucose+GIP ($r = 0.246, p = 0.003, n = 142$), and (D) glucose+GLP1 ($r = 0.255, p = 0.002, n = 138$). (E) PPP1R1A mRNA expression levels measured by qPCR in human islets transduced with mock or PPP1R1A shRNA5 lentivirus (MOI = 2). Graph bars represent mean ± SEM of $n = 3$ independent experiments. \*p < 0.05 with student's t-test. (F) Insulin secretion of human islets transduced with mock or PPP1R1A shRNA5 lentivirus was stimulated with low glucose (2.8 mM), high (16.7), high glucose+Exendin-4 (100 nM) or high glucose+Forskolin (10 µM), $n = 4$.</figcaption></figure>
phosphorylation by PKA in response to adrenergic stimulation of cardiomyocytes [35]. As a consequence, phosphorylated PPP1R1A inhibits the phosphatase PP1 which result in a prolongation of PKA-mediated phosphorylation of substrate proteins. To determine if PPP1R1A expression has a similar effect on Gαs-coupled GLP1R-mediated GSIS amplification in β-cells, PPP1R1A was knocked down in INS1 (832/13) β-cells and insulin secretion was assessed. INS1 (832/13) β-cells do not respond well to GLP1 receptor agonists GLP1 and Exendin-4 [19], thus we stimulated INS1 (832/13) β-cells with IBMX to elevate intracellular cAMP and mimic GLP1 signaling.

Silencing of PPP1R1A in INS1 (832/13) β-cells resulted in reduced basal and IBMX-promoted GSIS (Fig. 4A). Next, we evaluated if PPP1R1A contributed to PKA phosphorylation events downstream of GLP1R activation. Phosphorylation levels of all PKA-target proteins and the specific PKA target protein CREB, were assessed in PPP1R1A-KD and scramble control cells (Fig. 4B-D and OSM Fig. 3). PPP1R1A protein levels were significantly reduced in PPP1R1A-KD cells (Fig. 4B upper panel and 4C). The average phosphorylation levels of PKA-target proteins (Fig. 4B bottom) and CREB (p-CREB) (OSM Fig. 3) increased in response to glucose and were further enhanced in response to glucose + IBMX in control cells (Fig. 4B bottom and OSM Fig. 3A, B). These signals were partially blunted in the presence of H89, a selective PKA inhibitor (Fig. 4B bottom, 4D and OSM Fig. 3A, B). In PPP1R1A-KD cells, a similar pattern of PKA-target protein phosphorylation was observed, but the increase in phosphorylation of total PKA-target proteins in response to glucose+IBMX with or without H89 was reduced (Fig. 4D p = 0.05 and p < 0.01). In contrast, the increased phosphorylation of

the specific PKA target protein CREB in response to glucose+IBMX was not altered in PPP1R1A-KD compared to control cells (OSM Fig. 3A, B). An acute increase of PPP1R1A protein levels in response to glucose and glucose+IBMX was observed in control cells, with the response being much stronger upon stimulation with glucose+IBMX (Fig. 4B upper bands), suggesting that PKA-mediated PPP1R1A phosphorylation may increase PPP1R1A protein stability. These data indicate that PPP1R1A regulates phosphorylation levels of PKA/PP1 substrate proteins in β-cells and thereby contributes to the insulinotropic effects of GLP1 signaling.

### 3.4. PPP1R1A contributes to IBMX-promoted mitochondrial coupling efficiency

GLP1-mediated GSIS amplification in primary human and mouse β-cells [12] and in MIN6 cells [11] is accompanied by increased mitochondrial ATP production. To identify if the insulinotropic effect of PPP1R1A is caused by changes in mitochondrial metabolism, we examined how reduced PPP1R1A expression affected mitochondrial bioenergetic profiles in response to stimulation with glucose or glucose+IBMX in INS1 (832/13) β-cells. The mitochondrial oxygen consumption rate (OCR) was measured by an extracellular flux analyzer in PPP1R1A-KD and scramble control cells. In control cells, we observed an increase in OCR in response to glucose (50% over basal glucose, Fig. 5A). In agreement with previous studies [36], glucose+IBMX stimulation (Fig. 5A, B) did not further enhance acute OCR, but enhanced ATP-mediated OCR (Fig. 5A, C), reduced proton-leak OCR (Fig. 5A, D), and consequently

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** PPP1R1A contributes to IBMX-promoted insulin secretion and PKA-targets phosphorylation in INS1 (832/13) β-cells. INS1 (832/13) β-cells transfected with scramble or PPP1R1A siRNA. (A) Insulin secretion was stimulated for 1 h with low (2.8 mM), high (16.7) or high glucose+IBMX (100 µM). (B) In INS1 (832/13) β-cells under the same conditions as in (A) immunoblot of PPP1R1A (top) and PKA-phosphorylated proteins (bottom) after 30 min of stimulation with low (2.8 mM), high (16.7) and high glucose+IBMX (100 µM) w/wo PKA inhibitor H89, (C,D) Densitometric analysis for (C) PPP1R1A and (D) total PKA-phosphorylated proteins. Graph bars represent mean ± SEM of n = 11 (A), n = 5 (C), n = 7 (D) independent experiments. Within group comparison; \#p < 0.001. Between groups comparison (control vs. KD) \*p < 0.05; \*\*p < 0.01 using a Two-way ANOVA.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** PPP1R1A contributes to IBMX-promoted mitochondrial coupling efficiency in INS1 (832/13) β-cells. Mitochondrial Oxygen Consumption Rate (OCR) was measured by Seahorse (XF24) in INS1 (832/13) β-cells transfected with scramble or PPP1R1A siRNA (10 nM). (A) Average OCR traces in basal glucose (2.8 mM), glucose (16.7 mM) + IBMX (100 µM) or vehicle (DMSO), Oligomycin (4 µM), FCCP (4 µM) and Antimycin A + Rotenone (1 µM) conditions (traces represent average FC to basal OCR at 2.8 mM glucose). Mitochondrial activity parameters; (B) Acute Response OCR, (C) ATP-mediated OCR, (D) Proton-Leak OCR and, (E) Coupling-Efficiency. Data are mean ± SEM of *n* = 9 independent experiments. \*p < 0.05; \*\*p < 0.01; \*\*\*p < 0.001; \*\*\*\*p < 0.0001 with student t-test.</figcaption></figure>

increased the mitochondrial coupling efficiency (Fig. 5A, E, OSM Fig. 4A, E) in control cells. PPP1R1A-KD cells also showed increased ATP-mediated OCR in response to glucose+IBMX (Fig. 5A, C). However the reduction of proton leak OCR was blunted (Fig. 5A, D) and the IBMX-promoted mitochondrial coupling efficiency was less pronounced (Fig. 5A, E). This is consistent with the reduced IBMX-promoted GSIS amplification observed in PPP1R1A-KD cells (Fig. 4A).

The mitochondrial membrane potential (MMP) is the driving force pumping protons across the inner mitochondrial membrane [31]. MMP is fed by reducing equivalents (NADH and FADH₂) from pyruvate oxidation in the Krebs cycle and dissipated by either proton leak or ATP production [31]. MMP dynamics were measured in response to glucose or glucose+IBMX in single PPP1R1A-KD and control INS1 (832/13) β-cells using the MMP indicator TMRM. As expected, MMP increased (decreased TMRM emission) in response to glucose; the augmentation was accelerated in response to the ATP synthase inhibitor Oligomycin and decreased upon treatment with the mitochondrial uncoupling agent FCCP in control cells (OSM Fig. 5A). The MMP increase was reduced in response to glucose+IBMX vs. glucose stimulus in control cells (OSM Fig. 5A, C) while hyperpolarization levels (MMP increase) were unchanged in response to glucose+IBMX compared to glucose alone in PPP1R1A-KD cells (OSM Fig. 5B, C).

To further understand the effects of PPP1R1A on IBMX-induced changes in mitochondrial bioenergetics, we measured single cell cytosolic ATP:ADP ratios (corrected by cytosolic pH), using the genetically encoded PercevalHR probe [32] (OSM Fig. 5D–F). Consistent with the MMP results, the increase in ATP:ADP ratio was significantly higher in response to glucose than glucose+IBMX in control cells (OSM Figs. 5D–F and 6). PPP1R1A-KD cells showed no differences in cytosolic ATP:ADP ratios in response to glucose+IBMX compared to glucose stimulation (OSM Fig. 5E, F), suggesting that PPP1R1A is required to mediate the effects of IBMX on the cytosolic ATP:ADP ratio.

## 3.5. Reduced PPP1R1A expression causes β-cell dysfunction under normoglycemic and glucotoxic conditions

Reduction of PPP1R1A expression impaired GLP-1 mediated amplification of GSIS and mitochondrial function. Next, we evaluated if extended loss of PPP1R1A further impaired β-cell function and aggravated β-cell dysfunction under chronic hyperglycemic conditions. INS1 (832/13) β-cells were treated with PPP1R1A siRNA (96 h) and subjected to glucotoxic conditions during the last 48 h (Fig. 6). PPP1R1A

siRNA treatment reduced PPP1R1A mRNA and protein levels (Fig. 6A, N). Interestingly, a reduction of PPP1R1A transcript and protein levels was also observed in control INS1 (832/13) β-cells exposed to hyperglycemic conditions (Fig. 6A, N). PPP1R1A siRNA-treated cells had reduced basal and glucose or glucose+IBMX-stimulated insulin secretion under normoglycemic conditions (Fig. 6B) an effect that was even more pronounced under hyperglycemic conditions (Fig. 6C, D). Reduced PPP1R1A mRNA levels did not affect β-cell apoptosis and viability suggesting that loss of PPP1R1A predominantly affects β-cell function (Fig. 6E, data not shown).

To evaluate if loss of PPP1R1A expression mimics β-cell dysfunction associated with chronic hyperglycemia and diabetes, gene expression profiles of β-cell marker genes were analyzed in PPP1R1A-KD cells. Loss of PPP1R1A expression impaired transcription of genes associated with insulin secretion and metabolism, like; *Ins1*, *Slc2a2*, and *Gck* (Fig. 6F–H) while expression levels of MCT1 which is predominantly expressed by immature β-cells and during β-cell dedifferentiation [37] were unaffected (Fig. 6I). Moreover, transcript and protein levels of the β-cell identity genes MafA, Pdx1, Pax6 and NeuroD1 were reduced in PPP1R1A-KD cells (Fig. 6J–N). These changes of β cell gene expression in PPP1R1A-KD cells resemble the effects observed under glucotoxic conditions (Fig. 6F–N) further supporting that PPP1R1A is required for maintaining β-cell function/identity.

## 4. Discussion

MafA transcription factor activity is essential for insulin secretion and β-cell function [2,3]. Here we used RNAseq analysis of MafA deficient mouse islets to identify novel genes important to β-cell physiology. PPP1R1A was identified as a novel factor required for GSIS and GLP-1 mediated amplification of GSIS by modifying mitochondrial bioenergetics and intracellular Gαs-coupled receptor signaling in β-cells.

The expression pattern and dynamics of MAFA and MAFB transcription factors and PPP1R1A in β-cells are remarkably similar, with strong expression correlation in human islets. Moreover, PPP1R1A mRNA levels were reduced in mouse MafA knock out islets and upon acute KD of MafA in INS1 (832/13) β-cells and human islets. Chronic hyperglycemia, elevated BMI, and type 2 diabetes reduced PPP1R1A, as well as MAFA and/or MAFB expression in β-cells [5]. Interestingly, RNAseq analysis using highly purified human pancreatic islet cells showed low MAFA and PPP1R1A mRNA levels in fetal but a strong increase in expression of both genes in adult mature β-cells [38] which supports that PPP1R1A,
<figure><img src="image_9.png" /><figcaption>**Fig. 6.** Reduced PPP1R1A expression causes β-cell dysfunction under normoglycemic and glucotoxic conditions. (A) PPP1R1A expression levels in INS1 (832/13) β-cells transfected with scramble or PPP1R1A siRNA and cultured under normoglycemic (NG) or hyperglycemic (HG) conditions. (B-D) Insulin secretion of NG (B) and HG (C) cells after 1 h incubation with low (2.8 mM), high (16.7) or high glucose+IBMX (100 µM). (D) Comparison of insulin secretion of PPP1R1A-KD cells cultured in NG and HG conditions. (E) Cell viability of PPP1R1A-KD cells in NG and HG. (F-M) qPCR expression analysis of glucose sensing (F-I) and β-cell transcription factors (J-M) of PPP1R1A-KD cells in NG and HG. (N) Immunostaining for PPP1R1A, MafA and Pdx1 protein of PPP1R1A-KD cells in NG and HG. Graph bars represent mean ± SEM of n = 3-6 independent experiments. \*p < 0.05; \*\*p < 0.01 with student's t-test.</figcaption></figure>

along with MAFA expression, should be used as a marker protein for β-cell differentiation protocols. Our observations further suggest that PPP1R1A expression is dependent on MAFA transcriptional activity and mediates some of the effects attributed to MAFA/B function in β-cells.

Recent publications suggest that β-cell dedifferentiation contributes to the loss of β-cell function observed in type 2 diabetes [39]. MAFA transcriptional activity is essential for insulin transcription and lost in hyperglycemic and diabetic islets contributing to pathological β-cell dedifferentiation. Here, we show that loss of MafA impairs PPP1R1A expression which could enhance metabolic stress during the progression to type 2 diabetes. Moreover, we observed that extended PPP1R1A-KD impaired mRNA and protein expression of β-cell transcription factors like MafA, Pdx1, NeuroD1, and Pax6 and reduced GSIS mimicking β-cell dedifferentiation. These findings suggest that loss of PPP1R1A as observed in type 2 diabetic β-cells either directly or through loss of MafA contributes to dedifferentiation during type 2 diabetes progression.

Analysis of RNAseq and insulin secretion data from pancreatic islets from a large number of ND and type 2 diabetic donors showed a positive correlation between PPP1R1A expression levels and incretin-promoted GSIS. Follow up *in vitro* experiments demonstrated that PPP1R1A contributed to IBMX-promoted amplification of GSIS, PKA-mediated phosphorylation and mitochondrial coupling efficiency in 832/13 β-cells. Moreover, glucose homeostasis was altered in PPP1R1A KO mice which had an altered initial response in an intraperitoneal glucose tolerance test (nominal *p*-value = 0.0068, [40]) supporting a role for PPP1R1A in *in vivo* GSIS and incretin-promoted GSIS. cAMP/PKA signaling is a common pathway enhancing GSIS upon incretin signaling, as well as after stimulation of other Gαs-coupled receptors, making this signaling pathway an attractive pharmacological target for development of type 2 diabetes therapies (1). Here we presented evidence that PPP1R1A is participating in extending cAMP/PKA signaling downstream of the GLP1R in β-cells. We have observed that IBMX- and Exendin-4-promoted GSIS amplification is reduced in INS1 (832/13) β-cells and human islets upon PPP1R1A knock down. The experiments with human islets were performed with a low number of donors (n = 4) and human islets are known to exhibit a high metabolic variability between donors, thus potentially explaining the non-significant result in response to PPP1R1A knock down observed.

We also showed that IBMX-promoted global phosphorylation of PKA-target proteins was reduced in PPP1R1A-KD cells. The differences in phosphorylation levels between control and PPP1R1A-KD cells were significant in the presence of H89, a selective PKA inhibitor drug. In this condition, PKA activation of the remaining PPP1R1A is likely poor, rendering the phosphorylated proteins more sensitive to the fully active PP1, hence resulting in a more rapid dephosphorylation.

Recent studies show that PPP1R1A is contributing to extending cAMP/PKA-phosphorylation cascades in response to activation of Gαs-coupled receptors such as β-adrenergic receptors in cardiomyocytes [41] and A2α adenosine receptors in MIN6 cells [42], further supporting a role of PPP1R1A in GLP1R signaling.

Phosphorylation levels of PKA-target proteins, but not the specific PKA-target protein CREB, appeared to be reduced in PPP1R1A-KD cells, suggesting that p-CREB does not belong to the subgroup of common PKA and PP1 substrate proteins being regulated by PPP1R1A. This implies that PPP1R1A is an inhibitory PP1 regulatory subunit that fine tunes PP1 activity only in a subgroup of common PKA/PP1 substrate proteins, converging in a protein complex with PPP1R1A and PP1 [43,44].

We have examined the effects of PPP1R1A-KD in GLP1R-mediated alterations of mitochondrial bioenergetics in β-cells. While glucose +IBMX stimulation resulted in increased respiration rate for ATP production, reduced proton-leak and consequently increased mitochondrial coupling efficiency in control INS1 (832/13) β-cells, these effects were attenuated in PPP1R1A-KD cells; glucose+IBMX treatment did not reduce proton leak respiration nor improve mitochondrial coupling efficiency. Moreover, mitochondrial membrane hyperpolarization and cytoplasmic ATP:ADP ratios in response to glucose+IBMX treatment were blunted
in PPP1R1A-KD cells further supporting a role for PPP1R1A in extending the signaling effects of cAMP/PKA and thereby positively affecting mitochondrial bioenergetics.

Our analysis showed a robust negative correlation between PPP1R1A mRNA levels in human islets and donor HbA1c, BMI, and age (to a lesser extend) suggesting that an impairment of glycemic and metabolic control is associated with a progressive loss of PPP1R1A expression in β-cells which parallels loss of β-cell glucose sensitivity during type 2 diabetes development. Previous studies have shown that *in vitro* hyperglycemia [45], as well as prediabetes in humans, is associated with reduced efficiency of GLP1R-mediated GSIS amplification and that type 2 diabetic patients are less responsive to GLP1-based therapies [15,16,46,47]. Moreover, a negative correlation between donor BMI and GLP1 responsiveness of human islets has been observed in *vitro* [12], suggesting that reduced PPP1R1A expression and desensitization to GLP1 represent a common pathophysiological phenomenon with lower PPP1R1A protein levels contributing to reduced GLP1R-induced cAMP/PKA signaling extension and GSIS amplification in β-cells from obese/prediabetic subjects progressing to type 2 diabetes. Thus, reduced PPP1R1A levels in β-cells may contribute to unresponsiveness of type 2 diabetic patients to GLP1-based treatments. A hypothesis further supported by previous findings demonstrating that PPP1R1A knock down in cardiomyocytes contributes to desensitization of G<sub>α5</sub>-coupled β-adrenergic receptors [35].

The current study aims to identify PPP1R1A's function in β-cells. Our experiments rely on MafA-deficient islets, a validated β-cell model (INS1 832/13), and observational correlation studies from a large cohort of human islets to show that PPP1R1A is participating in amplification of insulin secretion via GLP-1 signaling. To assess if these effects are significant and specific to GLP1 signaling *in vivo*, it would be necessary to study PPP1R1A loss of function animal models and/or human islet/β-cells with efficient PPP1R1A knock down and robust responsiveness to GLP1R stimulation which is missing in INS1 (832/13) β-cells [19]. Moreover, mass spectrometry-based global phosphoproteomics analysis would be extremely interesting to identify specific PKA phosphorylation target proteins that are affected by reduced PPP1R1A activity, as this would give an insight on how GLP1/PKA signaling is impaired in type 2 diabetic islets that lack PPP1R1A expression.

## 5. Conclusion

Our data suggest that PPP1R1A is a novel MAFA/MAFB target gene involved in GLP1R/PKA signaling, increasing mitochondrial coupling efficiency and amplifying GSIS in β-cells. Reduced PPP1R1A expression in β-cells may increase the risk of progressing from glucose intolerance to type 2 diabetes by reducing responsiveness to GLP1 and thereby attenuating GSIS amplification.

## CRediT authorship contribution statement

**Luis Rodrigo Cataldo:** Conceptualization, Methodology, Investigation, Writing – original draft, Writing – review & editing, Visualization, Funding acquisition.
**Neelanjan Vishnu:** Methodology, Investigation.
**Tania Singh:** Methodology, Investigation.
**Ludivine Bertonnier-Brouty:** Investigation.
**Sara Bsharat:** Investigation.
**Cheng Luan:** Methodology, Investigation.
**Erik Renström:** Methodology, Resources.
**Rashmi B. Prasad:** Methodology, Data curation, Writing – review & editing.
**Malin Fex:** Resources, Writing – review & editing.
**Hindrik Mulder:** Resources, Writing – review & editing.
**Supervision, Funding acquisition.**
**Isabella Arnter:** Conceptualization, Methodology, Resources, Writing – original draft, Writing – review & editing, Supervision, Funding acquisition.

## Declaration of competing interest

None.

## Acknowledgements

We want to thank Drs. Claes Wollheim (Geneva University/Lund University) and Roland Stein (Vanderbilt University) for scientific discussions.

## Funding

This project was funded by the following research grants: Albert Pålsson Foundation (FB2018-0251-FB2019-0318), Royal Physiographic Society of Lund (2018-2019), Diabetes Wellness Sverige Junior Grant (2018). Our laboratory as part of the LUDC-IRC was supported by the Swedish Foundation for Strategic Research Dnr IRC15-0067. LRC and IA were supported by an individual fellowship-Marie Skłodowska-Curie Action (H2020-MSCA-IF-2017. NACHO-795912) and LRC by a postdoctoral fellowship CONICYT 74180010.

## Prior presentation

Preliminary results of this study were previously presented at the 55th Annual Meeting of the EASD (poster #435), Barcelona, Spain, September 2019.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.metabol.2021.154734.

## References

[1] Hunter CS, Stein RW. Evidence for loss in identity, de-differentiation, and trans-differentiation of islet beta-cells in type 2 diabetes. Front Genet. 2017;8:35.

[2] Zhang C, Moriguchi T, Kajihara M, Esaki R, Harada A, Shimohata H, et al. MafA is a key regulator of glucose-stimulated insulin secretion. Mol Cell Biol. 2005;25:4969-76.

[3] Artner I, Hang Y, Mazur M, Yamamoto T, Guo M, Lindner J, et al. MafA and MafB regulate genes critical to beta-cells in a unique temporal manner. Diabetes. 2010;59:2530-9.

[4] Hang Y, Yamamoto T, Benninger RK, Brissova M, Guo M, Bush W, et al. The MafA transcription factor becomes essential to islet beta-cells soon after birth. Diabetes. 2014;63:1994-2005.

[5] Guo S, Dai C, Guo M, Taylor B, Harmon JS, Sander M, et al. Inactivation of specific beta cell transcription factors in type 2 diabetes. J Clin Invest. 2013;123:3305-16.

[6] Iacovazzo D, Flanagan SE, Walker E, Quezado R, de Sousa Barros FA, Caswell R, et al. MAFA missense mutation causes familial insulinomatosis and diabetes mellitus. Proc Natl Acad Sci U S A. 2018;115:1027-32.

[7] Matsuoka TA, Artner I, Henderson E, Means A, Sander M, Stein R. The MafA transcription factor appears to be responsible for tissue-specific expression of insulin. Proc Natl Acad Sci U S A. 2004;101:2930-3.

[8] Cyphert HA, Walker EM, Hang Y, Dhawan S, Haliyur R, Bonataki L, et al. Examining how the MAFB transcription factor affects islet beta-cell function postnatally. Diabetes. 2019;68:337-48.

[9] Baggio LL, Drucker DJ. Biology of incretins: GLP-1 and GIP. Gastroenterology. 2007;132:2131-57.

[10] Doyle ME, Egan JM. Mechanisms of action of glucagon-like peptide 1 in the pancreas. Pharmacol Ther. 2007;113:546-93.

[11] Tsuboi T, da Silva Xavier G, Holz GG, Jouaville LS, Thomas AP, Rutter GA. Glucagon-like peptide-1 mobilizes intracellular Ca2+ and stimulates mitochondrial ATP synthesis in pancreatic MIN6 beta-cells. Biochem J. 2003;369:287-99.

[12] Hodson DJ, Tarasov AI, Gimeno Brias S, Mitchell RK, Johnston NR, Haghollahi S, et al. Incretin-modulated beta cell energetics in intact islets of Langerhans. Mol Endocrinol. 2014;28:860-71.

[13] Thomas MK, Nikooienejad A, Bray R, Cui X, Wilson J, Duffin K, et al. Dual GIP and GLP-1 receptor agonist tirzepatide improves beta-cell function and insulin sensitivity in Type 2 diabetes. J Clin Endocrinol Metab. 2020;106(2):388-96. https://doi.org/10.1210/clinem/dgaa863

[14] Matarese A, Gambardella J, Lombardi A, Wang X, Santulli G. miR-7 regulates GLP-1-mediated insulin release by targeting beta-Arrestin 1. Cells. 2020;9.

[15] Anderson SL, Trujillo JM, McDermott M, Saseen JJ. Determining predictors of response to exenatide in type 2 diabetes. J Am Pharm Assoc (2003). 2012;52:466-71.

[16] Preumont V, Hermans MP, Bergman M, Buysschaert M. Predictive factors associated with primary failure to exenatide and non goal attainment in patients with type 2 diabetes. Acta Clin Belg. 2012;67:411-5.

[17] Oduori OS, Murao N, Shimomura K, Takahashi H, Zhang Q, Dou H, et al. Gs/Gq signaling switch in beta cells defines incretin effectiveness in diabetes. J Clin Invest. 2020;130:6639-55.
[18] Fang Z, Chen S, Manchanda Y, Bitsi S, Pickford P, David A, et al. Ligand-specific factors influencing GLP-1 receptor post-endocytic trafficking and degradation in pancreatic beta cells. Int J Mol Sci. 2020;21.

[19] Hohmeier HE, Mulder H, Chen G, Henkel-Rieger R, Prentki M, Newgard CB. Isolation of INS-1-derived cell lines with robust ATP-sensitive K+ channel-dependent and -independent glucose-stimulated insulin secretion. Diabetes. 2000;49:424-30.

[20] Taneera J, Fadista J, Ahlqvist E, Atac D, Ottosson-Laakso E, Wollheim CB, et al. Identification of novel genes for glucose metabolism based upon expression pattern in human islets and effect on insulin secretion and glycemia. Hum Mol Genet. 2015; 24:1945-55.

[21] Yang X, Boehm JS, Yang X, Salehi-Ashtiani K, Hao T, Shen Y, et al. A public genome-scale lentiviral expression library of human ORFs. Nat Methods. 2011;8:659-61.

[22] Singh T, Colberg JK, Sarmiento L, Chaves P, Hansen L, Bsharat S, et al. Loss of MafA and MafB expression promotes islet inflammation. Sci Rep. 2019;9:9074.

[23] Ganic E, Singh T, Luan C, Fadista J, Johansson JK, Cyphert HA, et al. MafA-controlled nicotinic receptor expression is essential for insulin secretion and is impaired in patients with Type 2 diabetes. Cell Rep. 2016;14:1991-2002.

[24] Johansson JK, Voss U, Kesavan G, Kostetskii I, Wierup N, Radice GL, et al. N-cadherin is dispensable for pancreas development but required for beta-cell granule turnover. Genesis. 2010;48:374-81.

[25] Mazur MA, Winkler M, Ganic E, Colberg JK, Johansson JK, Bennet H, et al. Microphthalmia transcription factor regulates pancreatic beta-cell function. Diabetes. 2013;62:2834-42.

[26] Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15-21.

[27] Anders S, Reyes A, Huber W. Detecting differential usage of exons from RNA-seq data. Genome Res. 2012;22:2008-17.

[28] Robinson MD, McCarthy DJ, Smyth GK. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26: 139-40.

[29] Matsuoka TA, Zhao L, Artner I, Jarrett HW, Friedman D, Means A, et al. Members of the large Maf transcription family regulate insulin gene transcription in islet beta cells. Mol Cell Biol. 2003;23:6049-62.

[30] Goehring I, Gerencser AA, Schmidt S, Brand MD, Mulder H, Nicholls DG. Plasma membrane potential oscillations in insulin secreting Ins-1 832/13 cells do not require glycolysis and are not initiated by fluctuations in mitochondrial bioenergetics. J Biol Chem. 2012;287:15706-17.

[31] Brand MD, Nicholls DG. Assessing mitochondrial dysfunction in cells. Biochem J. 2011;435:297-312.

[32] Tantama M, Martinez-Francois JR, Mongeon R, Yellen G. Imaging energy status in live cells with a fluorescent biosensor of the intracellular ATP-to-ADP ratio. Nat Commun. 2013;4:2550.

[33] Solimena M, Schulte AM, Marselli L, Ehehalt F, Richter D, Kleeberg M, et al. Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients

defines a novel transcriptomic signature of islets from individuals with type 2 diabetes. Diabetologia. 2018;61:641-57.

[34] Mularoni L, Ramos-Rodriguez M, Pasquali L. The pancreatic islet regulome browser. Front Genet. 2017;8:13.

[35] El-Armouche A, Rau T, Zolk O, Ditz D, Pamminger T, Zimmermann WH, et al. Evidence for protein phosphatase inhibitor-1 playing an amplifier role in beta-adrenergic signaling in cardiac myocytes. FASEB J. 2003;17:437-9.

[36] Peyot ML, Gray JP, Lamontagne J, Smith PJ, Holz GG, Madiraju SR, et al. Glucagon-like peptide-1 induced signaling and insulin secretion do not drive fuel and energy metabolism in primary rodent pancreatic beta-cells. PLoS One. 2009;4:e6221.

[37] Bensellam M, Jonas JC, Laybutt DR. Mechanisms of beta-cell dedifferentiation in diabetes: recent findings and future research directions. J Endocrinol. 2018;236:R109-R43.

[38] Blodgett DM, Nowosielska A, Afik S, Pechhold S, Cura AJ, Kennedy NJ, et al. Novel observations from next-generation RNA sequencing of highly purified human adult and fetal islet cell subsets. Diabetes. 2015;64:3172-81.

[39] Accili D, Talchai SC, Kim-Muller JY, Cinti F, Ishida E, Ordelheide AM, et al. When beta-cells fail: lessons from dedifferentiation. Diabetes Obes Metab. 2016;18(Suppl. 1): 117-22.

[40] (IMPC) TIMPC. The international mouse phenotyping consortium. https://wwwmousephenotype.org/; 2012.

[41] Chen G, Zhou X, Nicolaou P, Rodriguez P, Song G, Mitton B, et al. A human polymorphism of protein phosphatase-1 inhibitor-1 is associated with attenuated contractile response of cardiomyocytes to beta-adrenergic stimulation. FASEB J. 2008;22: 1790-6.

[42] Shahrestanaki MK, Arasi FP, Aghaei M. IPP-1 controls Akt/CREB phosphorylation extension in A2a adenosine receptor signaling cascade in MIN6 pancreatic beta-cell line. Eur J Pharmacol. 2019;850:88-96.

[43] Connor JH, Weiser DC, Li S, Hallenbeck JM, Shenolikar S. Growth arrest and DNA damage-inducible protein GADD34 assembles a novel signaling complex containing protein phosphatase 1 and inhibitor 1. Mol Cell Biol. 2001;21:6841-50.

[44] Vander Mierde D, Scheuner D, Quintens R, Patel R, Song B, Tsukamoto K, et al. Glucose activates a protein phosphatase-1-mediated signaling pathway to enhance overall translation in pancreatic beta-cells. Endocrinology. 2007;148:609-17.

[45] Rajan S, Dickson LM, Mathew E, Orr CM, Ellenbroek JH, Philipson LH, et al. Chronic hyperglycemia downregulates GLP-1 receptor signaling in pancreatic beta-cells via protein kinase A. Mol Metab. 2015;4:265-76.

[46] Kjems LL, Holst JJ, Volund A, Madsbad S. The influence of GLP-1 on glucose-stimulated insulin secretion: effects on beta-cell sensitivity in type 2 and nondiabetic subjects. Diabetes. 2003;52:380-6.

[47] Anichini R, Cosimi S, Di Carlo A, Orsini P, De Bellis A, Seghieri G, et al. Gender difference in response predictors after 1-year exenatide therapy twice daily in type 2 diabetic patients: a real world experience. Diabetes Metab Syndr Obes. 2013;6:123-9.