Loss of Slc12a2 specifically in pancreatic β-cells drives metabolic syndrome in mice

Abstract

The risk of type-2 diabetes and cardiovascular disease is higher in subjects with metabolic syndrome, a cluster of clinical conditions characterized by obesity, impaired glucose metabolism, hyperinsulinemia, hyperlipidemia and hypertension. Diuretics are frequently used to treat hypertension in these patients, however, their use has long been associated with poor metabolic outcomes which cannot be fully explained by their diuretic effects. Here, we show that mice lacking the diuretic-sensitive Na⁺K⁺2Cl⁻cotransporter-1 Nkcc1 (Slc12a2) in insulin-secreting β-cells of the pancreatic islet (Nkcc1^βKO) have reduced in vitro insulin responses to glucose. This is associated with islet hypoplasia at the expense of fewer and smaller β-cells. Remarkably, Nkcc1^βKO mice excessively gain weight and progressive metabolic syndrome when fed a standard chow diet ad libitum. This is characterized by impaired hepatic insulin receptor activation and altered lipid metabolism. Indeed, overweight Nkcc1^βKO but not lean mice had fasting and fed hyperglycemia, hypertriglyceridemia and non-alcoholic steatohepatitis. Notably, fasting hyperinsulinemia was detected earlier than hyperglycemia, insulin resistance, glucose intolerance and increased hepatic de novo gluconeogenesis. Therefore, our data provide evidence supporting the novel hypothesis that primary β-cell defects related to Nkcc1-regulated intracellular Cl⁻homeostasis and β-cell growth can result in the development of metabolic syndrome shedding light into additional potential mechanisms whereby chronic diuretic use may have adverse effects on metabolic homeostasis in susceptible individuals.

Introduction

Metabolic syndrome (MetS) is a common cluster of metabolic conditions reaching epidemic proportions. The main features include overweight/obesity, impaired glucose metabolism, hyperinsulinemia, hyperlipidemia and hypertension, which together strongly increase the risk for cardiovascular disease (CVD) and type-2 diabetes (T2D) [1–3]. In fact, the MetS is more frequent than T2D and its prevalence increases with age and overweight [4]. In addition, MetS together with obesity is considered the primary cause of non-alcoholic fatty liver disease (NAFLD) and its complications [5]. Therefore, preventing MetS constitutes a fundamental strategy to reduce CVD and T2D prevalence [1].

The etiology of the metabolic syndrome is complex. However, it is generally accepted that overeating calorie-dense diets rich in fats [6] and/or a sedentary life-style [7], is what eventually leads to increased adiposity, ectopic fat deposits, low-grade tissue inflammation, overweight/obesity and insulin resistance, the main drivers of the syndrome [8]. Current evidence suggests that insulin responses to feeding also play a role in the acute control of food intake [9] and that chronic hyperinsulinemia secondary to abnormal secretion/clearance is associated with a rise in fat mass accumulation [10]. It has been shown that lean individuals at risk of developing obesity have characteristically high and/or dynamically different insulin responses to nutrients, which persist or worsen during obesity [11, 12]. Moreover, obese individuals also show abnormal pulsatile insulin secretion [13, 14], all consistent with the notion that primary functional deficiencies in the islet secretory response to nutrients can contribute to the development of overweight and its complications including the MetS and T2D [15, 16].

It is well recognized that pancreatic β-cells release insulin in a pulsatile manner [17] and in synchrony with intracellular Ca²⁺ and/or metabolic oscillations [18, 19]. Particularly, some of the mechanisms proposed to underlie β-cell Ca²⁺/metabolic oscillations and electrical bursting [20] appear unrelated to the canonical K_ATP channel [21–25]. Indeed, a wide range of insulinotropic glucose concentrations promotes electrogenic Cl⁻fluxes while K_ATP channel activity remains inhibited [26, 27] whereas blocking these Cl⁻currents abolished membrane potential and Ca²⁺ oscillations [28–31]. Chloride fluxes do require Cl⁻channels and some of them were independently implicated in β-cell function. For instance, volume-regulated anion channels (VRAC) [32–34], anoctamine-1 (Ano1) [30, 31], the cystic fibrosis transmembrane conductance regulator (Cftr) [30, 35] or the ionotropic receptors for γ-aminobutyric acid (GABA) [36, 37] and glycine [38] all participate, to different extents, in β-cell excitability and insulin secretion. Independent of which Cl⁻channels are involved, secondary active Cl⁻loaders and extruders determine the non-equilibrium distribution of the anion and set the driving force for Cl⁻to flux through channels [39]. Inhibition of Cl⁻loaders such as Nkcc1 (Slc12a2) and others (Nkcc2, Slc12a1) with loop-diuretics bumetanide or furosemide impaired islet insulin secretion in vitro and resulted in glucose intolerance in different mouse models [40–44]. In addition, we have recently demonstrated that mice lacking a variant of the bumetanide-sensitive Nkcc2 (Nkcc2a, Slc12a1v1) exhibit abnormal insulin responses to glucose and develop hyperglycemia, glucose intolerance and insulin resistance [45]. In humans, diuretic treatment has been long associated with altered glucose homeostasis, insulin resistance [46–52] and worsening of the MetS [53]. Further, patients with functional deficiency of the thiazide-sensitive Cl⁻loader SLC12A3 are prone to overweight/obesity and the MetS [54–58]. At this point, it is important to keep in mind that the targets of diuretics, including Nkcc1, Nkcc2a and Slc12a3 are highly expressed in the kidney when compared to pancreatic β-cells [59, 60] and that diuretics can inhibit islet insulin secretion directly [61–63]. Therefore, the diuretic-dependent worsening of metabolic homeostasis may, at least in part be mediated by extra-renal effects of these drugs.

Here, we generated a new mouse model constitutively lacking the Nkcc1 in β-cells (Nkcc1^βKO) and present experimental evidence indicating spontaneous development of typical features of the metabolic syndrome in these mice. Indeed, by 30 weeks of age Nkcc1^βKO mice fed ad libitum a standard diet, are overweight, glucose intolerant, insulin resistant and develop non-alcoholic steatohepatitis (NASH). Therefore, our results provide a potential mechanistic explanation for the metabolic disturbances provoked by the chronic use of diuretics and a new pre-clinical mouse model to study the spontaneous development and progression of a syndrome considered a major risk factor of CVD and T2D.

Results

Effective and specific elimination of Nkcc1 in pancreatic β-cells

To ascertain β-cell specific Cre-mediated recombination, we determined immunoreactive red-fluorescent protein (RFP) and Nkcc1 expression in pancreatic islets and brain tissue dissected from Ins1^Cre:Nkcc1^lox/lox:Tomato reporter mice, using immunofluorescence microscopy. For these experiments, we used Nkcc1 antibodies validated against Nkcc1^KO tissues (S1A–S1H Fig). As expected, 15w old Ins1^Cre:Nkcc1^lox/lox:Tomato mice expressed RFP in insulin-positive cells (Fig 1A and 1E) but not in glucagon (Fig 1B and 1D) or somatostatin cells (Fig 1F and 1H) demonstrating β-cell-specific Cre-mediated recombination. In addition, 25w old Nkcc1^βKO mice did not show immunoreactivity for Nkcc1 in islet β-cells (Fig 1I–1L) but was present in glucagon-negative cells (arrowheads in Fig 1L). Consistent with previous data [64], Nkcc1 was barely detected in Nkcc1^βKO α-cells (Fig 1L) or control Ins1^Cre or Nkcc1^lox/lox (S1E–S1H and S2A–S2H Figs). Consistently, PCR and RT-PCR experiments demonstrate the expected genomic recombination event (Fig 1M and 1N) and undetectable Nkcc1 transcripts (Fig 1O and 1P) in islets from 25w old Nkcc1^βKO mice. Moreover, Nkcc1 protein expression was intact in the choroid plexus and in the brain of Ins1^Cre:Nkcc1^lox/lox:Tomato (S1I Fig) whereas Cre expression or "floxed" Slc12a2 alleles per se did not alter Nkcc1 expression patterns in the islet or tissues of 15w old Ins1^Cre and Nkcc1^lox/lox mice (S2 Fig). Therefore, these results suggest that Nkcc1^βKO mice lack Nkcc1 expression only in insulin-secreting β-cells.

[Figure omitted. See PDF.]

A-H. Representative pancreas sections of Ins1^Cre:Nkcc1^lox/lox:Tomato mice. Islets were coimmunolabeled against RFP (A and E), insulin (Ins, C and G), glucagon (Gcg, B) and somatostatin (Sst, F) to identify β-, α- or δ-cells, respectively. Overlay images of A-C and E-G are shown in D and H, respectively. I-L. Representative pancreas sections of Nkcc1^βKO mice coimmunolabeled against Nkcc1 (I), Gcg (J) and Ins (K) showing β-cell-specific Nkcc1 deletion in the overlay image (L). Arrowheads in L indicate Nkcc1 immunoreactivity in Ins- or Gcg-negative cells. M. Shown are exons 6–11 (filled boxes) of the mouse Slc12a2 gene and Lox sites (empty arrowheads). Filled arrowheads indicate PCR primers 106w/220f and 206w/320f designed to amplify 5’ Lox sites as 220bp and 320bp bands, respectively. The primer triplet 106w/220f/450r co-amplifies 220bp and 450bp fragments corresponding to the Nkcc1^lox/lox genotype of non-β cells and Cre/Lox-recombined alleles of β-cells, respectively. N. PCR of islet genomic DNA from Nkcc1^βKO mice showing amplicons of expected sizes by using the primers indicated in M. O. Represented are exons 1–5 (filled arrows) of Nkcc1 mRNAs and the RT-PCR primer pair 400s/400a used to produce Nkcc1 amplicons of 400bp. P. Representative RT-PCR experiments using total islet RNA from Nkcc1^lox/lox and Nkcc1^βKO mice. Nkcc1 mRNA expression detected as amplicons of expected sizes mainly in Nkcc1^lox/lox samples.

Loss of Nkcc1 in β-cells reduces β-cell mass, insulin secretion and action

The results shown in Fig 2A demonstrate that islets from ~22w old Nkcc1^βKO mice are less responsive to glucose than control islets (Ins1^Cre). Importantly, bumetanide reduced the secretory response to glucose in control but not in Nkcc1^βKO islets, as expected for a highly specific inhibitor of Nkcc1 and Nkcc2. These data thus confirm functional elimination of the transporter in β-cells of Nkcc1^βKO islets. Note that the secretory response of islets from 8-10w old Nkcc1^βKO mice was reduced, albeit not significantly (S3A Fig). To determine if these findings relate to changes in islet β-cell number/size, a morphometric analysis was performed. The data demonstrates significantly reduced β-cell numbers (Fig 2B), volume (Fig 2C) and mass (Fig 2D) in 10w old Nkcc1^βKO relative to age-matched control mice (Nkcc1^lox/lox). Accordingly, the islet-to-pancreas area ratio was significantly reduced in 10w old Nkcc1^βKO (Fig 2E) as well as the total number of β-cell clusters throughout the Nkcc1^βKO pancreas (Fig 2F). As expected for normal mice, the β-cell morphometry parameters obtained in 10w old mice remained relatively unchanged in older mice. Since there were no significant differences found in α-cell count, volume, mass or area between mice of both genotypes (S3 Fig), together these data suggest that a combination of reduced β-cell volume and number contribute to the reduced Nkcc1^βKO islet secretory responses in vitro and overall reduction in pancreatic β-cell mass in Nkcc1^βKO mice.

[Figure omitted. See PDF.]

A. Insulin secretory responses to low (5.5mM) and high (12.5mM) glucose of islets from 22w old Nkcc1^βKO and control mice (Nkcc1^lox/lox) in the presence of vehicle (DMSO) or 10μM bumetanide (BTD), as indicated. Results are expressed as the mean ± SEM of insulin secreted relative to total islet insulin content (n = 7–8, *p<0.05). B-F. Morphometry analysis performed on pancreas sections from Nkcc1^βKO and control mice (Nkcc1^lox/lox) at the indicated ages and immunolabeled against insulin. Shown are the number of β-cells per islet (B), mean β-cell volume (C, pL), β-cell mass (D, mg), islet area (E, % pancreas section) and the number of β-cell clusters (representing ≤5 β-cells/cluster) per mm² of pancreas tissue section (F). The data in B-C represents the mean ± SEM corresponding to >700 individual islets identified in 19–21 tissue sections obtained from male mice (n = 3) of the indicated genotypes and ages. Each point in D-F represents the mean values per single tissue section (*p<0.05).

Since normal insulin secretion activates hepatic insulin signaling to reduce de novo gluconeogenesis [65], we evaluated age-dependent hepatic insulin receptor (Insr)-mediated Akt phosphorylation and G6Pc expression in fed and 16h fasted 10-30w old Nkcc1^βKO mice. Fed control mice (Ins1^Cre) showed the expected Insr-mediated increase in Akt phosphorylation (Fig 3A, left panel), which was barely detected in Nkcc1^βKO mice at all ages tested (Fig 3A, right panel). Thus, in Nkcc1^βKO mice the response of the liver to food intake appears blunted. When mice were fasted, Akt phosphorylation was neither detected in control mice, as expected, nor in Nkcc1^βKO (Fig 3B). These data indicate reduced post-prandial hepatic Insr signaling in Nkcc1^βKO mice. However, expression levels of Insr were found reduced only in younger (10-20w) Nkcc1^βKO relative to controls and did not differ at 30 weeks of age in Nkcc1^βKO mice (Fig 3C). Interestingly, G6Pc protein expression relative to β-actin remained unchanged in Nkcc1^βKO mice suggesting intact endogenous glucose production. However, as shown in Fig 3D, glucose responses to exogenous alanine increased in 30w old Nkcc1^βKO mice, thus suggesting age-dependent deterioration in the control of hepatic de novo gluconeogenesis.

[Figure omitted. See PDF.]

A, B. Expression pattern of insulin receptors (Insr, 95kDa), Akt (60kDa) and G6Pc (40kDa) and phospho-activation of Akt (pAkt) in liver extracts of 10w, 20w and 30w Nkcc1^βKO and control mice (Ins1^Cre) fed (A) or fasted 16h (B). Shown are representative immunoblots loaded to represent 2 mice (n = 3–4 per genotype, age and condition). As loading control, we used β-actin (45kDa). C. Semi-quantitative densitometry analysis of hepatic Insr expression levels relative to β-actin expressed in arbitrary units (au). Shown are the mean ± SEM of 3 independent blots corresponding to 3 male mice of the indicated genotypes, ages and condition (*p<0.05). D. Blood glucose excursions (mg/dl) during alanine tolerance tests (ATT) performed in 16h fasted Nkcc1^βKO and control mice (Ins1^Cre) at the indicated ages (mean ± SEM, n = 9–10, *p<0.05). The areas under each curve (mg/ml/min) are indicated as insets in D.

Excess weight, increased fat mass and adipocyte hypertrophy in Nkcc1^βKO mice

Ad libitum chow-fed Nkcc1^βKO male mice significantly increased their body weight (BW) as they became older (Fig 4A), and this was not attributed to increased daily food intake (S4A Fig). Notably, BW mass of Nkcc1^βKO did not significantly differ from that of control mice (Nkcc1^loxflox or Ins1^Cre) from weaning (p19-21) up to ~15w of age. Subsequently, Nkcc1^βKO were significantly heavier than control mice, without becoming overtly obese. As expected, weekly BW gain after weaning gradually declined with age in mice of both genotypes (Fig 4B). However, the initial reduction in post-weaning BW gain of Nkcc1^βKO was followed by an episodic burst of accelerated BW gain, which preceded the onset of BW mass increase. Indeed, BW decline was significantly faster in Nkcc1^βKO mice during the first 6w of age. After that, BW gain increased significantly during the 9^th-11^thw of age and remained hastened thereafter, but this significant difference disappeared over time relative to control mice. Notably, an increasing proportion of Nkcc1^βKO mice began to lose weight between 25w and 30w of age (Fig 4B) while their food intake also declined (S4A Fig). The results shown in Fig 4C and 4D confirm that Nkcc1^βKO BW accrual is due to a significant age-dependent increase in fat mass accumulation (Fig 4C) rather than lean mass (Fig 4D) or free/total body water content (S4B and S4C Fig). In a very consistent way, cross-sectional adipocyte areas and fat cell-size distribution in in white retroperitoneal fat tissue of 10w old Nkcc1^βKO mice were normal (Fig 4E and 4F, left panel). However, the mean adipocyte area and cell-size distribution were significantly expanded (Fig 4E), or shifted toward larger adipocytes, respectively, in 30w old Nkcc1^βKO mice (Fig 4F, right panel). In fact, 90–95% of the adipocytes were smaller than ~2000μm² in 10w and 30w old normal mice whereas ~50% of all adipocytes in 30w old Nkcc1^βKO mice were larger than 2000μm² (Fig 4F, left panel). Further, histological analysis of retroperitoneal white adipose tissue and pancreas of Nkcc1^βKO mice demonstrate infiltration of inflammatory cells (S4D and S4E Fig) and fat cell deposits (S4F and S4G Fig). Evidently, this increased local and ectopic fat mass accumulation and adipocyte hypertrophy account for the age-dependent increase in BW mass in Nkcc1^βKO mice.

[Figure omitted. See PDF.]

A. Growth of Nkcc1^βKO and control (Nkcc1^lox/lox) mice fed ad libitum a chow diet. Data recorded as net weekly BW mass (g) starting at weaning until mice reached 30w of age. Plotted are the mean ± SEM (n = 9–16, *p<0.01). B. Weekly BW gain (g/week) of Nkcc1^βKO and control (Nkcc1^lox/lox) mice computed by subtracting BW at a given week age to that of the previous week. Each point represents data from a single mouse (n = 9–16, *p<0.01). C, D. Indicated are the mean ± SEM values corresponding to net fat mass (C, g) and lean mass (D, g) of Nkcc1^βKO and control (Nkcc1^lox/lox) mice at the indicated ages (n = 9–16, *p<0.01). E. Mean cross sectional area (μm²) of adipocytes morphometrically determined by analyzing retroperitoneal white fat tissue sections from 10w and 30w old Nkcc1^βKO and control (Nkcc1^lox/lox) mice (n = 3). Each point represents the mean adipocyte area found in a single non-overlapping digital image randomly taken from tissue sections (n = 6–9) of the indicated genotypes and ages (*p<0.001). F. Relative mean adipocyte size distribution computed from the data in E.

Dyslipidemia and non-alcoholic fatty liver disease in Nkcc1^βKO mice

The results shown in Fig 5A demonstrate that plasma glycerol levels were significantly increased in 10w and 30w old Nkcc1^βKO, but hypertriglyceridemia only manifested later in 30w old Nkcc1^βKO mice (Fig 5B) suggesting age-related deterioration of lipid metabolism. Importantly, Nkcc1^βKO did not develop larger livers than control mice discarding hepatomegaly (Fig 5C). Within this context, total fat content was significantly elevated in the liver of 30w old Nkcc1^βKO relative to control (Fig 5D, ~9% and ~4% w/w, respectively, *p<0.001) but not in 10w old Nkcc1^βKO mice (~3% w/w). Histological analysis revealed minimal and isolated micro vesicular steatosis in 10w old Nkcc1^βKO mice (Fig 5E and 5F) consistent with a normal score of 1 in the Kleiner’s scale of NAFLD [66]. However, 30w old Nkcc1^βKO showed hepatocyte hypertrophy, micro/macro vesicular steatosis (Fig 5G and 5H) and clusters of inflammatory cells, hepatocyte fat degeneration, rare cell ballooning (S5A–S5F Fig) and variable loss of hepatocyte glycogen content (S5G and S5H Fig). Therefore, 30w old Nkcc1^βKO mice developed non-alcoholic steatohepatitis (NASH).

[Figure omitted. See PDF.]

A, B. Plasma glycerol (A, mg/L) and triglycerides (B, TG mg/dl) of 10w and 30w old Nkcc1^βKO and control (Ins1^Cre) mice fasted 16h. Results represent the mean ± SEM (n = 4–5, *p<0.01). C, D. Plotted are the hepatic index (C) calculated as wet liver mass (g) relative to total BW (g), and the net fat content (mg) per gram of liver tissue (D) of Nkcc1^βKO and control (Nkcc1^lox/lox) mice at the indicated ages. Results are expressed as the mean ± SEM (n = 5–6, *p<0.001). E-H. Shown are representative H&E-stained liver sections of 10w (E-F) or 30w old (G-H) control (Nkcc1^lox/lox, E and G) and Nkcc1^βKO (F and H) mice. The squares in E-H are shown magnified in the images below each one of them to depict histopathology changes including mild steatosis around a central vein (cv) in 10w old Nkcc1^βKO mice and hypertrophic hepatocytes (dashed-lined cells), micro- and macro-vesicular fat deposits in 30w Nkcc1^βKO mice, consistent with a more severe steatosis phenotype (see S4 Fig). Bars indicate 20μm.

Age-dependent worsening of glycemic control in Nkcc1^βKO mice

Because 30w old Nkcc1^βKO mice developed NASH, we further tested glycemic control in these mice. Plasma insulin and blood glucose were determined in 10-30w old Nkcc1^βKO mice after their nocturnal feeding or after preventing it. Ten-week old Nkcc1^βKO showed minimal changes in fed or fasted plasma insulin and blood glucose levels relative to control mice (Ins1^Cre, Fig 6A and 6B, left panels). However, fasting plasma insulin levels increased in 20w old Nkcc1^βKO mice and both, fed/fasted plasma insulin and blood glucose were significantly higher in Nkcc1^βKO mice at 30w of age (Fig 6A and 6B, center and right panels). Therefore, fasting hyperinsulinemia precedes the rise in blood glucose in Nkcc1^βKO mice whereas fed hyperinsulinemia and high blood glucose develop in older Nkcc1^βKO mice. Still, 30w old Nkcc1^βKO mice were not overtly hyperglycemic (e.g., >200 mg/dl) or hyperinsulinemic (e.g., >500 pmol/L) indicating that the secretory dysfunction/β-cell loss in islets lacking Nkcc1 is insufficient to trigger T2D in chow-fed Nkcc1^βKO mice younger than ~35w. Instead, it results in age-dependent worsening of glycemic control. In support of that conclusion, 10w and 20w old Nkcc1^βKO mice were normo-tolerant to exogenous glucose (Fig 6C, left and mid panel), whereas 30w Nkcc1^βKO mice were not (Fig 6C, right panel and Fig 6D). In addition, 30w old Nkcc1^βKO mice developed resistance to insulin-induced hypoglycemia (Fig 6E, right panel). Therefore, the excess weight goes in hand with increased fasting plasma insulin but appears before overt glucose intolerance and insulin resistance in Nkcc1^βKO mice.

[Figure omitted. See PDF.]

A, B. Plasma insulin (A, pmol/L) and whole blood glucose (B, mg/dl) of 10w, 20w and 30w old Nkcc1^βKO and control (Ins1^Cre) mice fed or fasted 16h. Results represent the mean ± SEM (n = 17–28, *p<0.05). C, D. Blood glucose excursions (mg/dl) during glucose tolerance tests (GTT, C) performed in 6h fasted Nkcc1^βKO and control (Ins1^Cre) mice of the indicated ages (mean ± SEM, n = 9–14, *p<0.05) and the areas under the curve (D, mg/ml/min) of those responses. E. Blood glucose responses to exogenous insulin during insulin tolerance tests (ITT) performed in 6h fasted Nkcc1^βKO and control (Ins1^Cre) mice at 10w, 20w and 30w of age. Each point represents the mean ± SEM (n = 9–16, *p<0.05).

Discussion

We present evidence indicating that Nkcc1^βKO mice develop a cluster of metabolic conditions compatible with the MetS. The metabolic features of Nkcc1^βKO mice are very similar to those found in the chow-fed Fatzo/Pco mouse model of MetS/NAFLD [67]. In fact, Fatzo/Pco mice became overweight/obese on a normal chow diet, independently of changes in energy intake [68] and had deficient insulin responses to oral glucose [67, 69]. Although the mechanisms responsible for the phenotypes of the Fatzo/Pco mouse model are complex and likely polygenic, the ones present in Nkcc1^βKO mice appear directly related to the functional loss of Nkcc1 in β-cells. Indeed, i) Cre-mediated recombination of "floxed" alleles was only detected in β-cells of Ins1^Cre:Nkcc1^lox/lox:Tomato (Fig 1A–1H) and Nkcc1^βKO mice (Fig 1I–1L), respectively; ii) Nkcc1^βKO islets exhibited expected recombination events and Nkcc1 transcript expression patterns (Fig 1M–1P); and iii) immunoreactive Cre was present only in β-cells of Ins1^Cre mice (S2I–S2P Fig). Importantly, the use of Nkcc1 antibodies validated against knockout tissues (S1A–S1H Fig) showed the expected expression pattern of Nkcc1 in tissues/cells of the normal Nkcc1^lox/lox mouse, including those in Sertoli and chromaffin cells (S2Q and S2R Fig) [70, 71], ductal/epithelial cells of the pancreas, intestine (S2S and S2T Fig) [72, 73] and brain in Ins1^Cre:Nkcc1^lox/lox:Tomato mouse model (S1E–S1I Fig) [74]. Along the same lines, Nkcc1 protein expression was intact in the choroid plexus (S1I Fig), a relevant finding because low levels of Ins1 gene activity were previously reported [75]. Moreover, since expression of Cre or "floxed" alleles did not alter Nkcc1 tissue expression patterns (S1 and S2 Figs), together these results support the conclusion that Nkcc1^βKO mice have lost Nkcc1 in β-cells, minimizing recent concerns related to the efficacy/efficiency of the Ins1^Cre line to eliminate target genes [76].

Consistent with the previous conclusion, the secretory function of 10w and 22w old Nkcc1^βKO islets is reduced by ~25% and ~50%, respectively (S2A and S3A Figs). Notably, disruption or chronic pharmacological inhibition of Nkcc1 does not eliminate insulin responses to glucose [35, 44, 45, 62]. This is attributed to the fact that β-cells express a wide range of Cl⁻transporters and channels with potential overlapping and/or compensatory function, at least to some extent [39]. Nevertheless, our results suggest that β-cell Nkcc2a [45, 77] is minimally involved in the reduced secretory response of Nkcc1^βKO islets, because bumetanide did not reduce insulin secretion (S2A and S3A Figs). Along those lines, the participation of VRAC (Lrrc8a-e) [33, 34, 78] in the secretory phenotype of Nkcc1^βKO islets is expected to be limited because inhibition of Nkcc1 impairs β-cell volume regulation and VRAC activation [33, 79]. Independent of the potential participation of the furosemide-sensitive Kcc2 (Slc12a5) [80] or that of other Cl⁻transporters or channels in the secretory response of Nkcc1^βKO islets, our data suggest that loss of Nkcc1 in β-cells results in a rather mild age-related secretory dysfunction. Further, the demonstration that 10w old Nkcc1^βKO islets were significantly smaller than control due to decreased β-cell number and volume (Fig 2B–2E) implies that the overall reduced in vitro secretory responses of these islets is also related, at least in part to their hypoplastic nature.

The mechanistic relationship between the loss of Nkcc1 in β-cells and reduced β-cell number/volume/size is intriguing but not surprising. It has been demonstrated that Nkcc1 participates in cell proliferation [81–87]. Actually, inhibition of Nkcc1 reduced the proliferative capacity of excitable neuronal progenitor cells by dampening the electrical activity of ionotropic GABA receptors [88], which are Cl⁻channels, whereas their activation increased mouse and human β-cell mass [89, 90]. Our results demonstrating reduced number of β-cell clusters in the pancreas of 10-30w old Nkcc1^βKO mice (Fig 2F) support a role for Nkcc1 as a potential regulator of progenitor cell proliferation, because these clusters are considered proto-islets [91]. In addition, our data demonstrating reduced cell volume in β-cells lacking Nkcc1 (Fig 2C) are consistent with its role as a key regulator of mammalian cell volume [92] and, in particular, with biophysical [64, 79], pharmacological [40, 93, 94] and molecular [44] data directly implicating Nkcc1 in the regulation of β-cell volume/size.

Therefore, the physiological metabolic consequences of losing Nkcc1 in β-cells are potentially related to reduced β-cell mass/volume/size due to dysregulated [Cl^–]_i, altered Cl⁻channel-mediated electrical activity or a combination of both. In fact, inhibition of β-cell Nkcc1 reduced glucose-induced β-cell electrical oscillations modulated by Cl⁻channels [29, 31] whereas isovolumetric circadian oscillations in [Cl^–]_i, determined by the activity of Nkcc1/Kcc, established the frequency of action potential firings in electrically excitable cells [95]. Regardless of the underlying mechanisms, the age-related metabolic consequences of altered pulsatile/circadian insulin release are multiple [16]. These include hepatic Insr down-regulation, reduced insulin signaling and development of insulin resistance [96], impaired glucose tolerance, BW gain, dyslipidemia, liver fat accumulation and increased risk of NAFLD/NASH [15, 97]. As we have shown, Nkcc1^βKO mice fed ad libitum a chow diet recapitulated most of the previous metabolic phenotypes in an age-dependent manner. At 10w of age, Nkcc1^βKO mice showed reduced hepatic Insr expression/signaling (Fig 3A and 3B), mild focal liver steatosis (Fig 5F) and reduced hepatic glycogen stores (S5G and S5H Fig) considered early metabolic manifestations of deficient insulin-mediated responses in vivo [98, 99]. Importantly, lean 10w old Nkcc1^βKO mice also showed increased plasma glycerol (Fig 5A), an early marker of lipolysis, altered triglyceride turnover [100, 101] and a predictor of glucose intolerance/T2D in humans [102]. Consistently, 30w old Nkcc1^βKO mice developed glucose intolerance (Fig 6C and 6D), systemic insulin resistance (Fig 6E) and had increased responses to alanine (Fig 3D), a substrate almost exclusively used by the liver for de novo gluconeogenesis [45]. Further, older Nkcc1^βKO mice had fasting/fed hyperinsulinemia (Fig 6A), hyperglycemia (Fig 6B) and developed overweight (Fig 4A–4C), severe dyslipidemia (Fig 5A and 5B) and NASH (Fig 5G and 5H and S5 Fig). Therefore, the age-dependent metabolic phenotype of ad libitum chow-fed Nkcc1^βKO mice resembles most of the natural history of metabolic syndrome. In a physiological setting, our data rises the possibility that β-cell Nkcc1 may play a role in the natural decline of metabolic health associated with aging. In a clinical setting, our results may also provide a potential mechanism whereby chronic use of loop diuretics may worsen glucose homeostasis in patients with metabolic syndrome or susceptible to develop T2D.

In summary, our results demonstrate that the mild metabolic dysfunction of 10w old Nkcc1^βKO mice represents early phenotypic manifestations linked to a primary defect in β-cell function/proliferation/differentiation consequence of losing a diuretic-sensitive Cl⁻cotransporter. In addition, given that these phenotypes are not related to increased food intake, but precede the onset of overweight, it seems reasonable to conclude that the cascade of age-related metabolic manifestations observed in these mice develop in parallel with BW gain, likely increasing the risk of developing T2D later in life.

Methods

Animals and housing

The Animal Care and Use Committee of Wright State University approved all methods involving mice, which were carried out in accordance to relevant guidelines and regulations. Mice were congenic on the C57BL/6J genetic background and crossed for ~10 generations. Mice harboring loxP sites flanking exon 8–10 of the Slc12a2 gene (Nkcc1^lox/lox, provided by Dr. Christian A. Hübner, Jena University, Germany) were mated to Ins1^Cre mice [Jackson Labs stock 026801, B6(Cg)-Ins1^{tm1.1(cre)Thor}/J] constitutively expressing Cre recombinase only in pancreatic β-cells [103] to generate Ins1^Cre:Nkcc1^lox/lox mice (Nkcc1^βKO). As control, we used the following homozygous mice: Ins1^Cre, Nkcc1^lox/lox, Nkcc1^WT (C57BL/6J) and the tdTomato reporter line [Jackson Labs stock 007909, B6.Cg-Gt(ROSA)26Sor^{tm9(CAG-tdTomato)Hze}/J] to verify β-cell recombination of target alleles. In our hands, homozygous Cre expression in β-cells or the presence of "floxed" alleles in mice (Ins1^Cre and Nkcc1^lox/lox) were not associated with changes in glucose homeostasis as determined by: basal/fed blood glucose, plasma insulin, and glucose and insulin tolerance, consistent with previous reports [103–105]. Mice had ad libitum access to water and a standard chow diet [Envigo, Teklad 22/5 Rodent Diet #8640 (3.0kCal/g, 54% carbohydrates, 29% proteins and 17% fats)], except when they were fasted. In that case, only water was provided. Housing conditions were set as 12:12h light (0630-1830h) and dark (1830-0630h) cycles with an ambient temperature of ~22ºC. Data presented here correspond to experiments performed using male mice from ~10 to ~35 weeks (w) of age housed in groups as recently described [106].

Genotyping and RT-PCR

Mice were genotyped by using conventional PCR (Phire Tissue Direct PCR Master Mix, ThermoFisher Sci., #F170L) and genomic DNA from tail-clips or isolated islets to assess Cre-mediated recombination of Nkcc1^lox alleles [107]. Three sets of amplifying primers were used (5’-3’). Set 1: GCA ATT AAG TTT GGA GGT TCC TT (Nkcc1-w106/f220s) and TGG TGT GAA GGA ACA GTT GG (Nkcc1-w106/f220a). Set 2: GCA ATT AAG TTT GGA GGT TCC TT (Nkcc1-w206/f320s) and TGG TGT GAA GGA ACA GTT GG (Nkcc1-w206/f320a). Set 3: Nkcc1-w106/f220s, Nkcc1-w106/f220a and CCA ACA GTA TGC AGA CTC TC (Nkcc1-450r). Sets 1 and 2 amplify 106bp/206bp or 220bp/320bp from tail genomic DNA when mice are WT or carry Nkcc1^lox alleles, respectively. Set 3 was designed to co-detect recombined and Nkcc1^lox alleles as bands of 450bp and 206bp, respectively. Total RNA for RT-PCR experiments was obtained from freshly isolated mouse islets by using the RNeasy mini kit (Qiagen, Valencia, CA) reverse transcribed into cDNA (SuperScript II reverse transcriptase, ThermoFisher Sci., #18064022) and DNAse I-treated (New England Biolabs Inc., Ipswich, MA #M0303). Islet Nkcc1 cDNAs were amplified by using the primer set 5’-ACA CCA CCA GCA GTA CTA CT-3’ (Nkcc1-400s) and 5’GGC CAT TGC TAT TAC GAC GA-3’ (Nkcc1-400) as previously done [80].

Plasma biochemical studies, blood glucose and tolerance tests

Plasma was obtained after a 6h or 16h fasting period (0730-1330h or 1600-0800h, respectively) or at 0800h from mice fed ad libitum, by using heparinized glass capillaries (Scientific Glass, Rockwood, TN) and processed essentially as described [45]. Plasma triglycerides (TGs) and glycerol concentrations were determined by using commercially available kits (Cayman, Ann Harbor MI #10010303 and #10010755, respectively) and following the manufacturer’s instructions. Plasma insulin was quantified by using an ultrasensitive ELISA (10-1247-01; Mercodia, Winston-Salem, NC). Whole blood glucose was determined with a glucometer (FreeStyle-Lite, Abbott, IL). Glucose and insulin tolerance tests (GTTs and ITTs, respectively) consisted in measuring 6h fasted glucose and serially 15, 30, 60 and 120 minutes after intraperitoneal administration of 2.0g/kg D-glucose or 0.75U/kg of human recombinant insulin (HumulinR Eli Lilly, Indianapolis, IN). Alanine tolerance tests (ATTs) were performed in 16h fasted mice as described [45].

Primary islets and insulin secretion

Mice were deeply and terminally anesthetized (Euthasol^®, ip 150mg/kg) and pancreas tissues processed to isolate islets by using the collagenase method as previously described [45]. Islets were handpicked into individual wells of 12-well plates with mesh inserts [15 islet equivalents (iEq)/well] containing KRBH (in mM: 118.5 NaCl, 2.5 CaCl₂, 1.2 KH₂PO₄, 4.7 KCl, 25 NaHCO₃, 1.2 MgSO₄, 10 HEPES and 0.1% BSA pH 7.4) plus 3.3mM glucose. The mesh inserts containing islets were transferred to new wells containing KRBH+3.3mM glucose and incubated at 37ºC (5% CO₂) for 30 minutes, a step repeated once more. The islets were then transferred into their respective experimental wells containing KRBH+5.5mM or +12.5mM glucose plus vehicle (DMSO) or bumetanide (#B3023, Sigma Chem Co. Saint Louis, MO) for 1h at 37ºC (5% CO₂). Islets were transferred into new wells containing KRBH+12.5mM glucose plus vehicle or drugs, incubated 1h at 37ºC (5% CO₂) and transferred to new wells containing acidified ethanol. The KRBH from experimental wells was frozen at –20ºC for further analysis. Insulin content or secreted into the media was estimated using ELISA (10-1247-01, Mercodia, Salem, NC). Results are expressed as the ratio between secreted insulin and the sum of secreted and islet insulin content.

Tissue processing and immunofluorescence microscopy

Mice were deeply anesthetized (Euthasol^®, ip 150mg/kg), transcardially perfused with ice-cold PBS/heparin (0.1mM/1000U/ml, pH7.4) and then with ice-cold 4% paraformaldehyde (PFA) fixative to sacrifice them and collect tissues essentially as described [35]. Tissue embedding, sectioning and staining [(hematoxylin-eosin (H&E) and periodic acid-Schiff (PAS)] were done at AML Laboratories (Saint Augustine, FL). Additional tissue sections were processed for immunolabeling or H&E-staining (Sigma-Aldrich #HHS16 and 1% Phloxine B #19350 Certified Generon plus eosin Y #SE23-500D Fisher Chemical) and mounted (Permount SP15-100, Fisher Sci., Waltham MA) to capture digital images. To that end, we used a digital camera mounted on a Nikon Eclipse 600 microscope (Nikon Corp., Japan). Immunofluorescence microscopy experiments were performed as described [35] and the primary antibodies used were: RFP (rabbit, Rockland #35634), Cre (mouse, Millipore #MAB3120), insulin (guinea pig, Cell Marque #273A-15), glucagon (mouse, Abcam #K79bB10) and somatostatin (rat, Abcam #30788). We also used two KO-validated Nkcc1 antibodies [rabbit, Abcam #59791 [108] and Aviva #OABB01332, S1 Fig]. Species-specific DyLight405/Cy3/AlexaFluor488-conjugated secondary antibodies were purchased from Jackson Immunoresearch Inc. (PA, USA). Note that DyLight405-conjugated secondary antibodies were used to visualize insulin-positive β-cells and that images were converted to gray-scale to increase contrast against Cy3/AlexaFluor488-conjugated antibody signals.

Body composition and liver fat content analysis

Total body fat, lean mass and body water were determined in live mice by using the whole body quantitative magnetic resonance imaging (QMRI) analyzer EchoMRI-500^™ system (EchoMRI LLC, Echo Medical Systems, Houston TX) as described [109]. Mice were then sacrificed by decapitation to determine hepatic fat content (w/w) by using the gravimetric method of Bligh and Dyer [110]. Briefly, liver samples were homogenized in chloroform:methanol:water (2:2:1.8) using a manual glass/glass homogenizer on ice. The homogenate was centrifuged at 625×g and the organic phase collected and washed once with double distilled water to help with phase separation. The chloroform phase containing extracted fat was vacuum-dried in a rotary evaporator (SC110A SpeedVac Plus) at high drying rate. The residue was then analytically weighed (Mettler Toledo, AE100).

Tissue morphometry and histopathology analysis

Weighed pancreas tissues from mice were post-fixed, sectioned every 100μm and immunostained to assess endocrine cell areas (μm²), relative density (islet area/section area), endocrine cell number (counts/islet, only cells with a clear nucleus were counted), volume (pL, assuming spherical shape of cells) and mass [cell area per tissue section area × pancreas weight (g)]. We used NIH Fiji (ImageJ v2.3.0/1.53f, https://imagej.net/software/fiji/) [111] and digital images (1000dpi) taken at medium or high magnification (×400 to ×600, calibrated scale: 4.7–6.3 pixels/μm, respectively, corresponding to 0.045–0.024μm²/pixel²) using regular or oil immersion objectives (×60; Olympus Epi Fluorescence Spot Scope) attached to a color digital camera. Isolated, clusters of ≤5 β-cells or single β-cells within ductal epithelial cells were counted as identifiers of potential neogenic islets [91, 112]. Adipose tissue morphometry was performed by using the Adiposoft plug-in for Fiji (imagej.net/plugins/adiposoft) on H&E-stained retroperitoneal fat tissue sections at 100× and 200× magnification. Surface area data (pixels²) were manually transformed to μm² after calibration against a 10μm ruler [1pixel² = 0.754μm² (100×) and 0.189μm² (200×)]. The results were then confirmed by applying the automatic measuring function of the plug-in. Hepatic steatosis was blindly assessed by one of us (MDiF) and the preliminary diagnosis confirmed/extended by an experienced histopathologist (Dr. David Mirkin, Children’s Hospital, Dayton, OH). Images were subsequently analyzed to score steatosis severity by applying the criteria of Kleiner et al. [66]. These consist in the unweighted sum of three different scores: i) hepatocellular micro/macrovesicular steatosis (0, <5%; 1, >5–33%; 2, >33–66% and 3, >66% at 200×-400× magnification), ii) lobular inflammation as clusters of ≥5 inflammatory cells (0, no foci; 1, 1 foci/field; 2, 2 foci/field and 3, >2 foci/field at 100× magnification) and iii) cell ballooning (0, none; 1, few and 2, many cells with ballooning at 200×-400× magnification).

Western blotting

Tissues were weighed and immediately submerged in liquid nitrogen or immediately processed to extract proteins. Briefly, liver tissues were minced and quickly homogenized at 4ºC in a glass/glass homogenizer (Wheaton 15ml) containing Radioimmunoprecipitation assay (RIPA) lysis buffer (Sigma, Saint Louis, MO, #R3792) supplemented with phenylmethylsulfonyl fluoride (PMSF) and a protease/phosphatase inhibitor cocktail (Thermo Sci., Waltham, MA, #78443) to a proportion of 3ml RIPA per gm of tissue. Tissue lysates were transferred onto a 15ml conical tube (Fisher Scientific, Corning #430790) and re-homogenized by passing the lysate ~20 times through 18-gauge needles attached to a 5ml plastic syringe followed by ~20 more strokes through 21-gauge needles. Protein concentration in tissue extracts was determined by using the Coomassie-Bradford protein assay kit (Thermo Sci., Waltham, MA, #23200) following the instructions of the manufacturer. Up to 50μg of total proteins boiled 5min in denaturing loading buffer (Novex #2107345) were resolved in duplicates by polyacrylamide gel electrophoresis (PAGE) by using Bolt^™ 4–12%, Bis-Tris pre-casted gels (ThermoFisher Sci., #NW04120). Molecular weights were estimated by using pre-stained protein standards (SeeBlue Plus 2, ThermoFisher Sci., #LC5925). Gels were run at 130V for 35min in 2-(N-morpholino)-ethanesulfonic (MES) acid buffer (ThermoFisher Sci., #B000202), removed and soaked in 20% ethanol for 5 mins before transferring them onto pre-assembled transfer PVDF stacks (iBolt Transfer Stack, ThermoFisher Sci.). Proteins were electroblotted onto PDVF membranes by using a dry blotting system (Life Technologies, iBolt 2) and then incubated in blocking buffer (SuperBlock T20, ThermoFisher Sci. #37516) overnight at 4ºC. Membranes were washed three times for 10min in Tris-buffered saline (TBS) plus Tween 20 (TBST) and exposed to primary antibodies for 48h at 4ºC with gentle rocking. Membranes were then washed four times for 10min in TBST and exposed to relevant secondary antibodies for 1h at room temperature. After washing excess antibodies, antigen/antibody reactions were developed by chemiluminescence (Pierce West Pico Plus, ThermoFisher Sci., #34577). Images were taken using ChemiDoc Imaging System (Bio-Rad, Hercules, CA). Membranes were either stripped off the first antibody and reblotted, or new blots were produced when different antibodies were needed to detect proteins of similar molecular weight. The primary antibodies used were directed against: insulin receptor β-subunit (Insr), the S/T protein kinase Akt and its active version pAkt phosphorylated in S⁴⁷³ (rabbit, Cell Signaling #3025, #9272 and #9271, respectively), the catalytic subunit of glucose-6-phosphatase G6Pc (rabbit, Abcam ab83690) and β-actin (mouse, Developmental Studies Hybridoma Bank #528068). Secondary HRP-conjugated antibodies used were: anti-rabbit IgG and anti-mouse IgM (Jackson Immunoresearch, PA, #711-035-152 and #315-035-049, respectively).

Energy intake

Net 24h food intake was recorded in individually identifiable group-housed mice at 10w, 20w and 30w of age. Data was collected during 2 consecutive weeks after a week of acclimation in a metabolic cage equipped to record the feeding behavior of mice in real-time (Feed and Water intake activity monitor system HM-2, MBRose, Faaborg, Denmark). The overall settings, calibration and design of these experiments have been described in detail elsewhere [106]. The feeding microstructure/dynamics and ambulatory activity of Nkcc1^βKO and Ins1^Cre shall be reported in a forthcoming manuscript.

Statistics

Results are represented as mean values ± SEM, with the number of individual points (n) indicated. Statistical significance for a p value <0.05 between groups was obtained by applying one-way or two-way analyses of variance (ANOVA), as appropriate, followed by the Tukey-Kramer post-hoc test. Statistical analyses were conducted by using GraphPad Prism v7 (GraphPad Software Inc., San Diego, CA, USA). Normal distribution and homogeneity of data variance were tested using Shapiro-Wilk and F-tests, respectively.

Supporting information

S1 Fig. Validation of Nkcc1 antibodies and tissue expression pattern of the transporter.

A-H. Representative pancreas sections from 4w old male mouse lacking Nkcc1 in all tissues (Nkcc1^KO, A-D) and 20w old C57BL/6J WT mouse (Nkcc1^WT, E-H) co-immunolabeled against Nkcc1 (A and E), insulin (Ins, C and G) and glucagon (Gcg, B and F) to demonstrate specificity of Nkcc1 immunoreactivity in insulin-positive β-cells of normal Nkcc1^WT mice only. I. Representative sagittal brain section of a 15w old Ins1^Cre;Nkcc1^lox/lox;Tomato mouse immunolabeled against Nkcc1 to demonstrate specific immunoreactivity in six regions of the brain: the granule cell layer (gcl), corpus callosum (cc), anterior commissure (ac), third lobule of cerebellar vermis (cv3) and in the choroid plexus epithelium of the 3^rd (cp3) and 4^th (cp4) ventricle. Bar represents 25μm.

https://doi.org/10.1371/journal.pone.0279560.s001

(TIF)

S2 Fig. Expression pattern of immunoreactive Nkcc1 in the pancreas and tissues of normal Ins1^Cre and Nkcc1^lox/lox mice.

Representative pancreas sections from a 15w old male mouse expressing both Cre alleles in β-cells (Ins1^Cre, A-D and I, J) or homozygous for Lox alleles (Nkcc1^lox/lox, E-H and M-P) co-immunolabeled against Nkcc1 (A, E and Q-T), Cre (i and M), glucagon (Gcg, B, F, J and N) and insulin (Ins, C, G, K and O) to demonstrate conserved expression patterns of Nkcc1 immunoreactivity in insulin-positive β-cells of the islets and in the indicated tissues. Bar represents 25μm. Representative sections of the indicated tissues (Q-T) dissected from 20-25w old Nkcc1^βKO mice immunolabeled against Nkcc1 by using a KO-validated primary antibody (OABB01332). Nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI).

https://doi.org/10.1371/journal.pone.0279560.s002

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S3 Fig. Secretory response of 10w old islets and α-cell morphometry analysis.

A. Insulin secretory responses to low (5.5mM) and high (12.5mM) glucose of islets from 10w old Nkcc1^βKO and control mice (Ins1^Cre) in the presence of vehicle (DMSO) or 10μM bumetanide (BTD), as indicated. Results are expressed as the mean ± SEM of insulin secreted relative to total islet insulin content (n = 3, *p<0.05). B-F. Shown are α-cell number (B, counts per islet), volume (C, pL), area (D, μm²; and E, % of pancreas section) and α-cell mass (F, g) corresponding to 10w and 30w old Nkcc1^βKO and control (Nkcc1^lox/lox) mice. The results in B-D represent the mean ± SEM of data corresponding to >700 individual glucagon-stained islets found in 19–21 pancreas tissue sections obtained from male mice (n = 3) of the indicated genotypes. Each point in E, F represents mean values per tissue section. G. Shown is the mean islet α/β-cell ratio of Nkcc1^βKO and control mice at the indicated ages (*p<0.05). Results were obtained by dividing the data in B and that of Fig 2B.

https://doi.org/10.1371/journal.pone.0279560.s003

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S4 Fig. Energy intake, body water content, white adipose tissue inflammation and ectopic fat accumulation.

A. Normalized 24h food intake (kCal/gBW/day) of Nkcc1^βKO and control (Ins1^Cre) mice recorded for 14 days. Data represents the mean ± SEM (n = 9–10, *p<0.05 vs. genotype, ^■p<0.05 vs. age). B, C. Free water mass (B, g) representing bladder content and water in stomach/intestines of mice of the indicated genotypes/ages and total water mass (C, g): total water − free water / lean mass of mice (n = 9–10). D, E and F, G. Shown are H&E-stained retroperitoneal white adipose tissue (D, E) and pancreas (F, G) sections of 10w (D and F) and 30w old mice (E and G) of the indicated genotypes. The squares are shown at higher magnification in the images below. Bars indicate 50μm.

https://doi.org/10.1371/journal.pone.0279560.s004

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S5 Fig. Histopathology confirmation of steatohepatitis in 30w old Nkcc1^βKO mice.

A, B. Mild (A) and severe (B) inflammatory cell infiltration foci in relatively healthy liver tissue. C, D. Fat-degeneration of hepatocytes (arrowheads). E, F. Macrovesicular/balooning steatosis (arrowheads) consistent with a score of 3 in Kleiner’s scale. G, H. PAS-stained liver sections of control (Nkcc1^lox/lox) and Nkcc1^βKO mice at 10w (G) and 30w of age (H) to demonstrate glycogen stores in hepatocytes. Scale bar represents 20μm.

https://doi.org/10.1371/journal.pone.0279560.s005

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S1 Raw images. Original full-size PCR and RT-PCR gels.

The red rectangles on top of gels A and B represent the cropped areas used to build Fig 1N and 1P (B), respectively, in the main text. A. Original gel of genomic PCR experiments using DNA (+DNA) or not (–DNA) as templates. Shown are amplified DNA fragments of expected sizes obtained by using the primer sets indicated in Fig 1M. Also shown are additional control reactions performed by using primers designed to amplify 123bp of genomic sequences corresponding to the Slc12a5 gene. B. Original full-size RT-PCR gel showing bands of expected sizes corresponding to Cre (390bp) and Nkcc1 transcripts (400bp) amplified from total RNA purified from Nkcc1^βKO (lanes a and b) or from Nkcc1^lox/lox islets (lane c). As negative control, water was used instead of total WT RNA (lane d).

https://doi.org/10.1371/journal.pone.0279560.s006

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S2 Raw images. Original full-size Western blots.

The red rectangles on top of each blot correspond to the cropped areas used to build Fig 3A and 3B in the main text.

https://doi.org/10.1371/journal.pone.0279560.s007

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S1 Datasets.

https://doi.org/10.1371/journal.pone.0279560.s008

(XLSX)

Acknowledgments

We are most grateful to the members of Laboratory Animal Resource (WSU) who helped facilitate our research and to Chris Rapp (Department of Pharmacology and Toxicology), who helped establish histochemistry protocols in our laboratory. The authors are thankful to Dr. Christian A. Hübner for providing Nkcc1^lox mice and Dr. David Mirkin (Dayton’s Children Hospital) for his expertise in assessment of histopathology images. We are grateful to Drs. Khalid Elased and Courtney Sulentic (WSU) for their valuable comments during the development of this project. Part of the results presented here constitutes RA’s and MA’s Master of Science Theses [2021 and 2022, respectively].

Citation: Abdelgawad R, Rathod YD, Alshammari M, Kelly L, Hübner CA, Aguilar-Bryan L, et al. (2022) Loss of Slc12a2 specifically in pancreatic β-cells drives metabolic syndrome in mice. PLoS ONE 17(12): e0279560. https://doi.org/10.1371/journal.pone.0279560

About the Authors:

Rana Abdelgawad

Contributed equally to this work with: Rana Abdelgawad, Yakshkumar Dilipbhai Rathod

Roles: Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – review & editing

Affiliation: Department of Pharmacology and Toxicology, Wright State University, School of Medicine Dayton, Fairborn, Ohio, United States of America

ORICD: https://orcid.org/0000-0002-2430-3458

Yakshkumar Dilipbhai Rathod

Contributed equally to this work with: Rana Abdelgawad, Yakshkumar Dilipbhai Rathod

Roles: Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – review & editing

Affiliation: Department of Pharmacology and Toxicology, Wright State University, School of Medicine Dayton, Fairborn, Ohio, United States of America

Modhi Alshammari

Roles: Data curation, Investigation, Methodology, Visualization

Affiliation: Department of Pharmacology and Toxicology, Wright State University, School of Medicine Dayton, Fairborn, Ohio, United States of America

Lisa Kelly

Roles: Data curation, Investigation, Writing – review & editing

Affiliation: Department of Pharmacology and Toxicology, Wright State University, School of Medicine Dayton, Fairborn, Ohio, United States of America

Christian A. Hübner

Roles: Methodology, Resources, Validation, Writing – review & editing

Affiliation: Institut für Humangenetik, Universitätsklinikum Jena, Jena, Germany

Lydia Aguilar-Bryan

Roles: Resources, Writing – original draft, Writing – review & editing

Affiliation: Pacific Northwest Diabetes Research Institute, Seattle, Washington, United States of America

Mauricio Di Fulvio

Roles: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

E-mail: [email protected]

Affiliation: Department of Pharmacology and Toxicology, Wright State University, School of Medicine Dayton, Fairborn, Ohio, United States of America

ORICD: https://orcid.org/0000-0003-4046-7425

References

1. Samson SL, Garber AJ. Metabolic syndrome. Endocrinol Metab Clin North Am. 2014;43(1):1–23. pmid:24582089.

2. Khan SS, Ning H, Wilkins JT, Allen N, Carnethon M, et al. Association of Body Mass Index With Lifetime Risk of Cardiovascular Disease and Compression of Morbidity. JAMA Cardiol. 2018;3(4):280–7. pmid:29490333.

3. Ninomiya JK, L’Italien G, Criqui MH, Whyte JL, Gamst A, Chen RS. Association of the metabolic syndrome with history of myocardial infarction and stroke in the Third National Health and Nutrition Examination Survey. Circulation. 2004;109(1):42–6. pmid:14676144.

4. Moore JX, Chaudhary N, Akinyemiju T. Metabolic Syndrome Prevalence by Race/Ethnicity and Sex in the United States, National Health and Nutrition Examination Survey, 1988–2012. Prev Chronic Dis. 2017;14:E24. pmid:28301314.

5. Godoy-Matos AF, Silva WS Junior, Valerio CM. NAFLD as a continuum: from obesity to metabolic syndrome and diabetes. Diabetol Metab Syndr. 2020;12:60. pmid:32684985.

6. Dhurandhar NV, Petersen KS, Webster C. Key Causes and Contributors of Obesity: A Perspective. Nurs Clin North Am. 2021;56(4):449–64. pmid:34749887.

7. Church T, Martin CK. The Obesity Epidemic: A Consequence of Reduced Energy Expenditure and the Uncoupling of Energy Intake? Obesity (Silver Spring). 2018;26(1):14–6. pmid:29265774.

8. Grundy SM. Metabolic syndrome update. Trends Cardiovasc Med. 2016;26(4):364–73. pmid:26654259.

9. Dodd GT, Kim SJ, Mequinion M, Xirouchaki CE, Bruning JC, et al. Insulin signaling in AgRP neurons regulates meal size to limit glucose excursions and insulin resistance. Sci Adv. 2021;7(9). pmid:33637536.

10. Corkey BE. Banting lecture 2011: hyperinsulinemia: cause or consequence? Diabetes. 2012;61(1):4–13. pmid:22187369.

11. Goedecke JH, Dave JA, Faulenbach MV, Utzschneider KM, Lambert EV, et al. Insulin response in relation to insulin sensitivity: an appropriate beta-cell response in black South African women. Diabetes Care. 2009;32(5):860–5. pmid:19196884.

12. Stefan N, Stumvoll M, Weyer C, Bogardus C, Tataranni PA, Pratley RE. Exaggerated insulin secretion in Pima Indians and African-Americans but higher insulin resistance in Pima Indians compared to African-Americans and Caucasians. Diabet Med. 2004;21(10):1090–5. pmid:15384955.

13. Gumbiner B, Van Cauter E, Beltz WF, Ditzler TM, Griver K, et al. Abnormalities of insulin pulsatility and glucose oscillations during meals in obese noninsulin-dependent diabetic patients: effects of weight reduction. J Clin Endocrinol Metab. 1996;81(6):2061–8. pmid:8964829.

14. Polonsky KS, Given BD, Van Cauter E. Twenty-four-hour profiles and pulsatile patterns of insulin secretion in normal and obese subjects. J Clin Invest. 1988;81(2):442–8. pmid:3276730.

15. Hudish LI, Reusch JE, Sussel L. beta Cell dysfunction during progression of metabolic syndrome to type 2 diabetes. J Clin Invest. 2019;129(10):4001–8. pmid:31424428.

16. Satin LS, Butler PC, Ha J, Sherman AS. Pulsatile insulin secretion, impaired glucose tolerance and type 2 diabetes. Mol Aspects Med. 2015;42:61–77. pmid:25637831.

17. Porksen N. The in vivo regulation of pulsatile insulin secretion. Diabetologia. 2002;45(1):3–20. pmid:11845219.

18. Nunemaker CS, Zhang M, Wasserman DH, McGuinness OP, Powers AC, et al. Individual mice can be distinguished by the period of their islet calcium oscillations: is there an intrinsic islet period that is imprinted in vivo? Diabetes. 2005;54(12):3517–22. pmid:16306370.

19. Merrins MJ, Fendler B, Zhang M, Sherman A, Bertram R, Satin LS. Metabolic oscillations in pancreatic islets depend on the intracellular Ca2+ level but not Ca2+ oscillations. Biophys J. 2010;99(1):76–84. pmid:20655835.

20. Benninger RKP, Kravets V. The physiological role of beta-cell heterogeneity in pancreatic islet function. Nat Rev Endocrinol. 2022;18(1):9–22. pmid:34667280.

21. Yildirim V, Vadrevu S, Thompson B, Satin LS, Bertram R. Upregulation of an inward rectifying K+ channel can rescue slow Ca2+ oscillations in K(ATP) channel deficient pancreatic islets. PLoS Comput Biol. 2017;13(7):e1005686. pmid:28749940.

22. Dufer M, Haspel D, Krippeit-Drews P, Aguilar-Bryan L, Bryan J, Drews G. Oscillations of membrane potential and cytosolic Ca(2+) concentration in SUR1(-/-) beta cells. Diabetologia. 2004;47(3):488–98. pmid:14872319.

23. Seghers V, Nakazaki M, DeMayo F, Aguilar-Bryan L, Bryan J. Sur1 knockout mice. A model for K(ATP) channel-independent regulation of insulin secretion. J Biol Chem. 2000;275(13):9270–7. pmid:10734066.

24. Ravier MA, Nenquin M, Miki T, Seino S, Henquin JC. Glucose controls cytosolic Ca2+ and insulin secretion in mouse islets lacking adenosine triphosphate-sensitive K+ channels owing to a knockout of the pore-forming subunit Kir6.2. Endocrinology. 2009;150(1):33–45. pmid:18787024.

25. Szollosi A, Nenquin M, Aguilar-Bryan L, Bryan J, Henquin JC. Glucose stimulates Ca2+ influx and insulin secretion in 2-week-old beta-cells lacking ATP-sensitive K+ channels. J Biol Chem. 2007;282(3):1747–56. pmid:17138557.

26. Malaisse WJ, Zhang Y, Louchami K, Jijakli H. Stimulation by D-glucose of 36Cl- efflux from prelabeled rat pancreatic islets. Endocrine. 2004;25(1):23–5. pmid:15545702.

27. Best L. Glucose-induced electrical activity in rat pancreatic β-cells: dependence on intracellular chloride concentration. J Physiol. 2005;568(Pt 1):137–44. pmid:16024506.

28. Sehlin J, Meissner HP. Effects of Cl- deficiency on the membrane potential in mouse pancreatic beta-cells. Biochim Biophys Acta. 1988;937(2):309–18. pmid:3276351.

29. Eberhardson M, Patterson S, Grapengiesser E. Microfluorometric analysis of Cl- permeability and its relation to oscillatory Ca2+ signaling in glucose-stimulated pancreatic β-cells. Cell Signal. 2000;12(11–12):781–6. pmid:11152964.

30. Edlund A, Esguerra JL, Wendt A, Flodstrom-Tullberg M, Eliasson L. CFTR and Anoctamin 1 (ANO1) contribute to cAMP amplified exocytosis and insulin secretion in human and murine pancreatic beta-cells. BMC Med. 2014;12:87. pmid:24885604.

31. Crutzen R, Virreira M, Markadieu N, Shlyonsky V, Sener A, et al. Anoctamin 1 (Ano1) is required for glucose-induced membrane potential oscillations and insulin secretion by murine beta-cells. Pflugers Arch. 2016;468(4):573–91. pmid:26582426.

32. Best L, Brown PD, Sener A, Malaisse WJ. Electrical activity in pancreatic islet cells: The VRAC hypothesis. Islets. 2010;2(2):59–64. pmid:21099297.

33. Kang C, Xie L, Gunasekar SK, Mishra A, Zhang Y, et al. SWELL1 is a glucose sensor regulating beta-cell excitability and systemic glycaemia. Nat Commun. 2018;9(1):367. pmid:29371604.

34. Stuhlmann T, Planells-Cases R, Jentsch TJ. LRRC8/VRAC anion channels enhance beta-cell glucose sensing and insulin secretion. Nat Commun. 2018;9(1):1974. pmid:29773801.

35. Di Fulvio M, Bogdani M, Velasco M, McMillen TS, Ridaura C, et al. Heterogeneous expression of CFTR in insulin-secreting beta-cells of the normal human islet. PLoS One. 2020;15(12):e0242749. pmid:33264332.

36. Braun M, Ramracheya R, Bengtsson M, Clark A, Walker JN, et al. Gamma-aminobutyric acid (GABA) is an autocrine excitatory transmitter in human pancreatic beta-cells. Diabetes. 2010;59(7):1694–701. pmid:20413510.

37. Menegaz D, Hagan DW, Almaca J, Cianciaruso C, Rodriguez-Diaz R, et al. Mechanism and effects of pulsatile GABA secretion from cytosolic pools in the human beta cell. Nat Metab. 2019;1(11):1110–26. pmid:32432213.

38. Yan-Do R, Duong E, Manning Fox JE, Dai X, Suzuki K, et al. A Glycine-Insulin Autocrine Feedback Loop Enhances Insulin Secretion From Human beta-Cells and Is Impaired in Type 2 Diabetes. Diabetes. 2016;65(8):2311–21. pmid:27207556.

39. Di Fulvio M, Aguilar-Bryan L. Chloride transporters and channels in beta-cell physiology: revisiting a 40-year-old model. Biochem Soc Trans. 2019;47(6):1843–55. pmid:31697318.

40. Hermansen K, Schmitz O, Arnfred J, Mogensen CE. Effects of furosemide and indapamide upon pancreatic insulin and somatostatin secretion in vitro. Diabetes Res. 1986;3(4):221–3. pmid:2874909.

41. Sandstrom PE. Evidence for diabetogenic action of bumetanide in mice. Eur J Pharmacol. 1988;150(1–2):35–41. pmid:3042432.

42. Sandstrom PE, Sehlin J. Furosemide-induced glucose intolerance in mice is associated with reduced insulin secretion. Eur J Pharmacol. 1988;147(3):403–9. pmid:3288480.

43. Sandstrom PE, Sehlin J. Furosemide causes acute and long-term hyperglycaemia and reduces glucose tolerance in mice. Acta Physiol Scand. 1988;132(1):75–81. pmid:3066121.

44. Alshahrani S, Di Fulvio M. Enhanced insulin secretion and improved glucose tolerance in mice with homozygous inactivation of the Na+K+2Cl- co-transporter 1. J Endocrinol. 2012;215(1):59–70. pmid:22872759.

45. Kelly L, Almutairi MM, Kursan S, Pacheco R, Dias-Junior E, et al. Impaired glucose tolerance, glucagon, and insulin responses in mice lacking the loop diuretic-sensitive Nkcc2a transporter. Am J Physiol Cell Physiol. 2019;317(4):C843–C56. pmid:31365295.

46. Giugliano D, Varricchio M, Cerciello T, Varano R, Saccomanno F, Giannetti G. Bumetanide and glucose tolerance in man. Farmaco Prat. 1980;35(8):403–8. pmid:7449959.

47. Gries FA, Kleophas W. Effects of diuretics on insulin secretion and glucose disposal. Horm Metab Res Suppl. 1990;22:33–8. pmid:2202626.

48. Robinson DS, Nilsson CM, Leonard RF, Horton ES. Effects of loop diuretics on carbohydrate metabolism and electrolyte excretion. J Clin Pharmacol. 1981;21(11–12 Pt 2):637–46. pmid:7040494.

49. Kubik MM, Bowers E, Underwood PN. Longterm experience of the routine use of bumetanide. Br J Clin Pract. 1976;30(1):11–4. pmid:764842.

50. Furman BL. Impairment of glucose tolerance produced by diuretics and other drugs. Pharmacol Ther. 1981;12(3):613–49. pmid:6116241.

51. Fonseca V, Phear DN. Hyperosmolar non-ketotic diabetic syndrome precipitated by treatment with diuretics. Br Med J (Clin Res Ed). 1982;284(6308):36–7. pmid:6797633.

52. Ramsay LE, Yeo WW, Jackson PR. Metabolic effects of diuretics. Cardiology. 1994;84 Suppl 2:48–56. pmid:7954546.

53. Buscemi S, Nicolucci A, Lucisano G, Galvano F, Grosso G, et al. Impact of chronic diuretic treatment on glucose homeostasis. Diabetol Metab Syndr. 2013;5(1):80. pmid:24330854.

54. Blanchard A, Vallet M, Dubourg L, Hureaux M, Allard J, et al. Resistance to Insulin in Patients with Gitelman Syndrome and a Subtle Intermediate Phenotype in Heterozygous Carriers: A Cross-Sectional Study. J Am Soc Nephrol. 2019;30(8):1534–45. pmid:31285285.

55. Yuan T, Jiang L, Chen C, Peng X, Nie M, et al. Glucose tolerance and insulin responsiveness in Gitelman syndrome patients. Endocrine connections. 2017;6(4):243–52. pmid:28432081.

56. Liu T, Wang C, Lu J, Zhao X, Lang Y, Shao L. Genotype/Phenotype Analysis in 67 Chinese Patients with Gitelman’s Syndrome. Am J Nephrol. 2016;44(2):159–68. pmid:27529443.

57. Eriksson JW, Jansson PA, Carlberg B, Hagg A, Kurland L, et al. Hydrochlorothiazide, but not Candesartan, aggravates insulin resistance and causes visceral and hepatic fat accumulation: the mechanisms for the diabetes preventing effect of Candesartan (MEDICA) Study. Hypertension. 2008;52(6):1030–7. pmid:18981327.

58. Reungjui S, Roncal CA, Mu W, Srinivas TR, Sirivongs D, et al. Thiazide diuretics exacerbate fructose-induced metabolic syndrome. J Am Soc Nephrol. 2007;18(10):2724–31. pmid:17855639.

59. Alshahrani S, Alvarez-Leefmans F, Di Fulvio M. Expression of the Slc12a1 Gene in Pancreatic β-cells: Molecular Characterization and in silico Analysis. Cell Physiol Biochem. 2012;30(1):95–112. pmid:22759959.

60. Di Fulvio M, Brown PD, Aguilar-Bryan L. Chloride channels and transporters in β-cell physiology. In: Islam MS, editor. The islets of Langerhans. 1. 2nd ed: Springer-Verlag; 2014. p. 401–51.

61. Sandstrom PE, Sehlin J. Furosemide reduces insulin release by inhibition of Cl- and Ca2+ fluxes in beta-cells. Am J Physiol. 1988;255(5 Pt 1):E591–6. pmid:3056030.

62. Sandstrom PE. Bumetanide reduces insulin release by a direct effect on the pancreatic beta-cells. Eur J Pharmacol. 1990;187(3):377–83. pmid:1963593.

63. Sandstrom PE. Inhibition by hydrochlorothiazide of insulin release and calcium influx in mouse pancreatic beta-cells. Br J Pharmacol. 1993;110(4):1359–62. pmid:8306076.

64. Majid A, Speake T, Best L, Brown PD. Expression of the Na+K+-2CI- cotransporter in α and β cells isolated from the rat pancreas. Pflugers Arch. 2001;442(4):570–6. pmid:11510890.

65. Hatting M, Tavares CDJ, Sharabi K, Rines AK, Puigserver P. Insulin regulation of gluconeogenesis. Ann N Y Acad Sci. 2018;1411(1):21–35. pmid:28868790.

66. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313–21. pmid:15915461.

67. Droz BA, Sneed BL, Jackson CV, Zimmerman KM, Michael MD, et al. Correlation of disease severity with body weight and high fat diet in the FATZO/Pco mouse. PLoS One. 2017;12(6):e0179808. pmid:28640904.

68. Peterson RG, Jackson CV, Zimmerman KM, Alsina-Fernandez J, Michael MD, et al. Glucose dysregulation and response to common anti-diabetic agents in the FATZO/Pco mouse. PLoS One. 2017;12(6):e0179856. pmid:28640857.

69. Sun G, Jackson CV, Zimmerman K, Zhang LK, Finnearty CM, et al. The FATZO mouse, a next generation model of type 2 diabetes, develops NAFLD and NASH when fed a Western diet supplemented with fructose. BMC Gastroenterol. 2019;19(1):41. pmid:30885145.

70. Liu YL, Yang SS, Chen SJ, Lin YC, Chu CC, et al. OSR1 and SPAK cooperatively modulate Sertoli cell support of mouse spermatogenesis. Sci Rep. 2016;6:37205. pmid:27853306.

71. Xie Z, Currie KP, Cahill AL, Fox AP. Role of Cl- co-transporters in the excitation produced by GABAA receptors in juvenile bovine adrenal chromaffin cells. J Neurophysiol. 2003;90(6):3828–37. pmid:12968012.

72. Jakab RL, Collaco AM, Ameen NA. Physiological relevance of cell-specific distribution patterns of CFTR, NKCC1, NBCe1, and NHE3 along the crypt-villus axis in the intestine. Am J Physiol Gastrointest Liver Physiol. 2011;300(1):G82–98. pmid:21030607.

73. Shumaker H, Soleimani M. CFTR upregulates the expression of the basolateral Na(+)-K(+)-2Cl(-) cotransporter in cultured pancreatic duct cells. Am J Physiol. 1999;277(6 Pt 1):C1100–10. pmid:10600761.

74. Virtanen MA, Uvarov P, Hubner CA, Kaila K. NKCC1, an Elusive Molecular Target in Brain Development: Making Sense of the Existing Data. Cells. 2020;9(12). pmid:33291778.

75. Mazucanti CH, Liu QR, Lang D, Huang N, O’Connell JF, et al. Release of insulin produced by the choroid plexis is regulated by serotonergic signaling. JCI Insight. 2019;4(23). pmid:31647782.

76. Mosleh E, Ou K, Haemmerle MW, Tembo T, Yuhas A, et al. Ins1-Cre and Ins1-CreER Gene Replacement Alleles Are Susceptible To Silencing By DNA Hypermethylation. Endocrinology. 2020;161(8). pmid:32267917.

77. Alshahrani S, Almutairi MM, Kursan S, Dias-Junior E, Almiahuob MM, et al. Increased Slc12a1 expression in β-cells and improved glucose disposal in Slc12a2 heterozygous mice. J Endocrinol. 2015;227(3):153–65. pmid:26400961.

78. Qiu Z, Dubin AE, Mathur J, Tu B, Reddy K, et al. SWELL1, a plasma membrane protein, is an essential component of volume-regulated anion channel. Cell. 2014;157(2):447–58. pmid:24725410.

79. Miley HE, Holden D, Grint R, Best L, Brown PD. Regulatory volume increase in rat pancreatic beta-cells. Pflugers Arch. 1998;435(2):227–30. pmid:9382935.

80. Kursan S, McMillen TS, Beesetty P, Dias-Junior E, Almutairi MM, et al. The neuronal K+Cl- co-transporter 2 (Slc12a5) modulates insulin secretion. Sci Rep. 2017;7(1):1732. pmid:28496181.

81. Panet R, Markus M, Atlan H. Bumetanide and furosemide inhibited vascular endothelial cell proliferation. J Cell Physiol. 1994;158(1):121–7. pmid:8263019.

82. Panet R, Atlan H. Stimulation of bumetanide-sensitive Na+/K+/Cl- cotransport by different mitogens in synchronized human skin fibroblasts is essential for cell proliferation. J Cell Biol. 1991;114(2):337–42. pmid:2071675.

83. Panet R, Eliash M, Atlan H. Na+/K+/Cl- cotransporter activates MAP-kinase cascade downstream to protein kinase C, and upstream to MEK. J Cell Physiol. 2006;206(3):578–85. pmid:16222701.

84. Panet R, Marcus M, Atlan H. Overexpression of the Na(+)/K(+)/Cl(-) cotransporter gene induces cell proliferation and phenotypic transformation in mouse fibroblasts. J Cell Physiol. 2000;182(1):109–18. pmid:10567922

85. Capo-Aponte JE, Wang Z, Akinci MA, Wolosin JM, Pokorny KS, et al. Potassium-chloride cotransporter mediates cell cycle progression and proliferation of human corneal epithelial cells. Cell Cycle. 2007;6(21):2709–18. pmid:17912038.

86. Wang JF, Zhao K, Chen YY, Qiu Y, Zhu JH, et al. NKCC1 promotes proliferation, invasion and migration in human gastric cancer cells via activation of the MAPK-JNK/EMT signaling pathway. J Cancer. 2021;12(1):253–63. pmid:33391422.

87. Bush PG, Pritchard M, Loqman MY, Damron TA, Hall AC. A key role for membrane transporter NKCC1 in mediating chondrocyte volume increase in the mammalian growth plate. J Bone Miner Res. 2010;25(7):1594–603. pmid:20200963.

88. Young SZ, Taylor MM, Wu S, Ikeda-Matsuo Y, Kubera C, Bordey A. NKCC1 knockdown decreases neuron production through GABA(A)-regulated neural progenitor proliferation and delays dendrite development. J Neurosci. 2012;32(39):13630–8. pmid:23015452.

89. Untereiner A, Abdo S, Bhattacharjee A, Gohil H, Pourasgari F, et al. GABA promotes beta-cell proliferation, but does not overcome impaired glucose homeostasis associated with diet-induced obesity. FASEB J. 2019;33(3):3968–84. pmid:30509117.

90. Purwana I, Zheng J, Li X, Deurloo M, Son DO, et al. GABA promotes human beta-cell proliferation and modulates glucose homeostasis. Diabetes. 2014;63(12):4197–205. pmid:25008178.

91. Bonner-Weir S, Guo L, Li WC, Ouziel-Yahalom L, Lysy PA, et al. Islet neogenesis: a possible pathway for beta-cell replenishment. Rev Diabet Stud. 2012;9(4):407–16. pmid:23804276.

92. Hoffmann EK, Lambert IH, Pedersen SF. Physiology of cell volume regulation in vertebrates. Physiol Rev. 2009;89(1):193–277. pmid:19126758.

93. Engstrom KG, Sandstrom PE, Sehlin J. Volume regulation in mouse pancreatic beta-cells is mediated by a furosemide-sensitive mechanism. Biochim Biophys Acta. 1991;1091(2):145–50. pmid:1995074.

94. Kinard TA, Goforth PB, Tao Q, Abood ME, Teague J, Satin LS. Chloride channels regulate HIT cell volume but cannot fully account for swelling-induced insulin secretion. Diabetes. 2001;50(5):992–1003. pmid:11334443.

95. Stangherlin A, Watson JL, Wong DCS, Barbiero S, Zeng A, et al. Compensatory ion transport buffers daily protein rhythms to regulate osmotic balance and cellular physiology. Nat Commun. 2021;12(1):6035. pmid:34654800.

96. Gilon P, Ravier MA, Jonas JC, Henquin JC. Control mechanisms of the oscillations of insulin secretion in vitro and in vivo. Diabetes. 2002;51 Suppl 1:S144–51. pmid:11815474.

97. Tilg H, Moschen AR, Roden M. NAFLD and diabetes mellitus. Nat Rev Gastroenterol Hepatol. 2017;14(1):32–42. pmid:27729660.

98. Sun Z, Lazar MA. Dissociating fatty liver and diabetes. Trends Endocrinol Metab. 2013;24(1):4–12. pmid:23043895.

99. Petersen MC, Shulman GI. Mechanisms of Insulin Action and Insulin Resistance. Physiol Rev. 2018;98(4):2133–223. pmid:30067154.

100. Rotondo F, Ho-Palma AC, Remesar X, Fernandez-Lopez JA, Romero MDM, Alemany M. Glycerol is synthesized and secreted by adipocytes to dispose of excess glucose, via glycerogenesis and increased acyl-glycerol turnover. Sci Rep. 2017;7(1):8983. pmid:28827624.

101. Langin D. Control of fatty acid and glycerol release in adipose tissue lipolysis. C R Biol. 2006;329(8):598–607; discussion 53–5. pmid:16860278.

102. Mahendran Y, Cederberg H, Vangipurapu J, Kangas AJ, Soininen P, et al. Glycerol and fatty acids in serum predict the development of hyperglycemia and type 2 diabetes in Finnish men. Diabetes Care. 2013;36(11):3732–8. pmid:24026559.

103. Thorens B, Tarussio D, Maestro MA, Rovira M, Heikkila E, Ferrer J. Ins1(Cre) knock-in mice for beta cell-specific gene recombination. Diabetologia. 2015;58(3):558–65. pmid:25500700.

104. Johnston NR, Mitchell RK, Haythorne E, Pessoa MP, Semplici F, et al. Beta Cell Hubs Dictate Pancreatic Islet Responses to Glucose. Cell Metab. 2016;24(3):389–401. pmid:27452146.

105. Nasteska D, Cuozzo F, Viloria K, Johnson EM, Thakker A, et al. Prolyl-4-hydroxylase 3 maintains beta cell glucose metabolism during fatty acid excess in mice. JCI Insight. 2021;6(16). pmid:34264866.

106. Rathod YD, Di Fulvio M. The feeding microstructure of male and female mice. PLoS One. 2021;16(2):e0246569. pmid:33539467.

107. Antoine MW, Hubner CA, Arezzo JC, Hebert JM. A causative link between inner ear defects and long-term striatal dysfunction. Science. 2013;341(6150):1120–3. pmid:24009395.

108. Koumangoye R, Omer S, Delpire E. Mistargeting of a truncated Na-K-2Cl cotransporter in epithelial cells. Am J Physiol Cell Physiol. 2018;315(2):C258–C76. pmid:29719172.

109. Halm ST, Bottomley MA, Almutairi MM, Di Fulvio M, Halm DR. Survival and growth of C57BL/6J mice lacking the BK channel, Kcnma1: lower adult body weight occurs together with higher body fat. Physiological reports. 2017;5(4). pmid:28242822.

110. Bligh EG, Dyer WJ. A rapid method of total lipid extraction and purification. Can J Biochem Physiol. 1959;37(8):911–7. pmid:13671378.

111. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9(7):676–82. pmid:22743772.

112. Lipsett M, Finegood DT. beta-cell neogenesis during prolonged hyperglycemia in rats. Diabetes. 2002;51(6):1834–41. pmid:12031971.