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. Author manuscript; available in PMC: 2015 Apr 1.
Published in final edited form as: J Endocrinol. 2014 Jun 13;222(2):267–276. doi: 10.1530/JOE-14-0126

Increased serum CXCL1 and CXCL5 are linked to obesity, hyperglycemia, and impaired islet function

Craig S Nunemaker 1, H Grace Chung 1,2, Gretchen M Verrilli 1,3, Kathryn L Corbin 1, Aditi Upadhye 1, Poonam R Sharma 1
PMCID: PMC4135511  NIHMSID: NIHMS605610  PMID: 24928936

Abstract

Proinflammatory cytokines are thought to play a significant role in the pathogenesis of type 2 diabetes (T2D) and are elevated in the circulation even before the onset of the disease. However, the full complement of cytokines involved in the development of T2D is not known. In this study, 32 serum cytokines were measured from diabetes-prone BKS.Cg-m+/+Leprdb/J (db/db) mice and heterozygous aged-matched control mice at 5-weeks (non-diabetic/non-obese), 6-7-weeks (transitional-to-diabetes), or 11-weeks (hyperglycemic/obese) and then correlated with body weight, blood glucose, and fat content. Among these 32 cytokines, CXCL1 showed the greatest increase (+78%) in serum levels between db/db mice that were hyperglycemic (blood glucose: 519+/-23 mg/dl, n=6) compared to non-hyperglycemic (193+/-13 mg/dl, n=8). Similarly, increased CXCL1 (+68%) and CXCL5 (+40%) were associated with increased obesity in db/db mice; note that these effects could not be entirely separated from age. We next examined whether islets could be a source of these chemokines. 48-hour exposure to cytokines mimicking low-grade systemic inflammation (10 pg/ml IL-1beta + 20 pg/ml IL-6) upregulated islet CXCL1 expression by 53+/-3-fold and CXCL5 by 83+/-10-fold (n=4, p<0.001). Finally, overnight treatment with the combination of CXCL1 and CXCL5 at serum levels was sufficient to produce a significant decrease in the peak calcium response to glucose stimulation, suggesting reduced islet function. Our findings show that CXCL1 and CXCL5 1) are increased in the circulation with the onset of T2D, 2) are produced by islets under stress, and 3) synergistically impact islet function, suggesting these chemokines participate in the pathogenesis of T2D.

Keywords: islet cells, cytokines, calcium, insulin, diabetes

Introduction

Chronic low-grade inflammation is increasingly viewed as a contributing factor to many metabolic diseases including T2D. Obesity leads to excess fatty acids and lipids in the body that have toxic and damaging effects on the body's metabolism (Paolisso, et al. 1995, Poitout & Robertson. 2002, Robertson, et al. 2004) and also causes low-grade systemic inflammation (Wellen & Hotamisligil. 2003). This inflammation, particularly of fat tissue, increases the circulating levels of pro-inflammatory cytokines in the blood. These cytokines contribute to the two defining characteristics of T2D: 1) insulin resistance and 2) defective insulin secretion that lead to hyperglycemia (Greenberg & McDaniel. 2002). Our hypothesis is that increased levels of circulating cytokines caused by obesity can have potentially damaging effects in distal tissues, such as the pancreatic islets of Langerhans. We recently showed that exposure to circulating levels of certain cytokines (interleukin-(IL)-1B and IL-6 in combination) is sufficient to trigger dysfunction and apoptosis in islets from diabetes-prone mice without significantly disrupting islet function in healthy mice (O'Neill, et al. 2013).

Our objective in the present study was to identify other circulating cytokines and chemokines associated with T2D that could also contribute to changes in normal islet function. We examined 32 different cytokines/chemokines in serum from leptin-receptor-deficient db/db mice during the development of diabetes in order to identify additional cytokines that could directly contribute to or protect against islet decline in T2D. We identified two chemokines of interest that increased in serum with the development of obesity and hyperglycemia: C-X-C motif ligand 1 (CXCL1) and CXCL5. CXCL1 and CXCL5 both bind with the CXCR2 receptor and are associated with processes as diverse as angiogenesis, wound healing, and tumorigenesis. CXCL1 is expressed in macrophages, neutrophils and epithelial cells and plays a key role in inflammation as a chemoattractant for neutrophils. CXCL5 is expressed in eosinophils as well as epithelial cells and has a well-established role in stimulating the chemotaxis of angiogenic neutrophils, particularly in response to inflammation.

CXCL1 and CXCL5 are also associated with diabetes. Increased serum levels of CXCL1 have been reported in patients with type 1 diabetes (Hakimizadeh, et al. 2013, Takahashi, et al. 2011)and more recently in T2D (Sajadi, et al. 2013). Increased serum CXCL5 has also been observed in obesity and insulin resistance in mice and humans (Chavey, et al. 2009) and is associated with complications of diabetes including nephropathy (Higurashi, et al. 2009) and atherosclerosis (Chen, et al. 2011). CXCL1 has also been reported to be a CD40-induced chemokine in isolated human pancreatic islets (Klein, et al. 2008) that is also expressed in response to amyloid in T2D (Westwell-Roper, et al. 2011). CXCL1 expression is associated with increased rates of islet transplant failure (Citro, et al. 2012, Cowley, et al. 2012), and blocking the CXCL1 receptor CXCR2 improves transplant outcomes (Citro, et al. 2012). In this study, we show that CXCL1 and CXCL5 both increase in serum as diabetes-prone db/db mice become obese and hyperglycemic. Further, we show for the first time that exposure to CXCL1 and CXCL5 at circulating levels can directly impact islet function, and we demonstrate that islet cell stress can induce the expression of CXCL1 and CXCL5. Our findings together suggest a role for these chemokines in T2D both systemically and within the pancreatic islet.

Materials and methods

Mice

Studies of serum cytokine levels were conducted using male BKS.Cg-Dock7m +/+ Leprdb/J (db/db) mice as a model of T2D, with age-matched heterozygous mice as controls (Jackson Laboratories, Bar Harbor, ME). Mice were used at ages 5, 6-7, and 11 weeks. Follow-up studies of cytokine effects on normal pancreatic islets were performed using outbred CD-1 mice at ages of 8-12 weeks (Charles River Laboratories, MA). All animal procedures were approved by the University of Virginia (UVA) Institutional Animal Care and Use Committee.

DEXA analysis

A Lunar PixiMUS densitometer (GE Medical Systems) performed dual-emission X-ray absorptiometry (DEXA) scans to determine fat and bone mineral content. As previously described (Roland, et al. 2010), mice were anesthetized by intraperitoneal injection of 20 mg/ml xylazine and 100 mg/ml ketamine in 0.9% sterile saline at a dose of 5 uL/g body weight and then placed on the Lunar PIXImus tray for scanning. After running a quality control test, the animal was scanned to measure area, bone mineral density (BMD), bone mineral content (BMC), lean body mass, fat body mass, total body mass, and percent body fat. Following the scan, mice were injected subcutaneously with 1 mL 0.9% sterile saline for hydration and then placed on a heating pad and monitored until recovery from the anesthesia.

Cytokine panel

Thirty-four db/db and thirty-four het mice varying in age from 5, 6-7, and 11 weeks old were euthanized by CO2. Blood was immediately collected by heart puncture, allowed to clot at room temperature, and then centrifuged to collect serum. Samples were frozen at -20°C for long-term storage. Serum was thawed briefly to extract 60 uL and shipped to Millipore Inc. (St. Charles, MO) on dry ice for use in a 32-plex mouse cytokine assay. Millipore diluted samples 1:2 and ran in singlet following their bead-based assay protocol.

Islet isolation and treatment

Pancreatic islets were isolated by collagenase-P digestion (Roche Diagnostics, Indianapolis, IN) followed by centrifugation with Histopaque 1100 (Sigma-Aldrich, St. Louis, MO) as previously described (Carter, et al. 2009). Islets were incubated overnight in RPMI 1640 medium (Invitrogen) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin to allow recovery from collagenase digestion before further treatment. Various islet stressors were prepared as follows: Rotenone and thapsigargin were purchased from Sigma-Aldrich and prepared in stocks of DMSO to final concentrations less than 0.1%. Glucose-free RPMI medium (10% FBS and 1% penicillin/streptomycin) was supplemented with 1M glucose stock to produce the 28G condition. Stocks of the murine forms of IL-1B, IL-6, CXCL1, and CXCL5 (purchased from R&D Systems, Inc., Minneapolis, MN) were prepared in PBS with 0.1% BSA. Oleate, linoleate, and palmitate were purchased from Sigma-Aldrich and were prepared in 100mM stock concentrations in methanol and stored in -80. To treat the islets, the required amount of each fatty acid was taken in a glass tube and dried under a stream of nitrogen to remove methanol. The dried mixture of fatty acids thus obtained was resuspended in the RPMI medium with 0.1% BSA followed by vortexing and sonication. All experiments were completed within 48-72 hours post isolation.

Glucose-stimulated calcium measurements

Intracellular calcium ([Ca2+]i) was measured using the ratiometric [Ca2+]i indicator fura-2 AM as previously described (Corbin, et al. 2011, Crim, et al. 2010). Briefly, Cell Tracker Red CMTPX (CTR, Invitrogen), a membrane penetrating fluorescent probe, was used in order to distinguish cytokine-treated islets from control islets by selectively labeling only one of the two groups, thus enabling a simultaneous comparison of the two treatment groups (see (Corbin, et al. 2011) for additional details). All islets were loaded with 1 uM fura-2 AM for 30 minutes in the presence or absence of 200 nM CTR, washed, and then recorded with a Hamamatsu ORCA-ER camera (Hamamatsu Photonics, Japan) attached to an Olympus BX51WI fluorescence microscope (Olympus, Tokyo, Japan) using 340 and 380 nm excitation light and 510 nm emission as previously described (Jahanshahi, et al. 2009). Data were recorded and analyzed with IP Lab software Version 4.0 (Scanalytics, Rockville, MD).

Glucose-stimulated insulin secretion

After overnight incubation, islets were tested for insulin secretion as described previously (Crim, et al. 2010). Briefly, islets were preincubated at 37 °C and 5% CO2 for one hour in a standard KRB solution, then washed and incubated in KRB supplemented with 3 mM glucose for one hour followed by treatment with KRB containing 11 mM glucose for one hour. The supernatant was collected after each treatment and insulin concentration in the supernatant was measured by an ELISA method (Mercodia, Uppsala, Sweden) according to the manufacturer's instructions.

Real-time polymerase chain reaction

RNA was collected from islets treated with cytokines associated with low-grade inflammation (IL-6 + IL-1beta). Untreated islets served as a control. RNA and cDNA preparation and real-time polymerase chain reactions (RT-PCR) were performed as previously described (O'Neill, et al. 2013). RNA purity and concentration were determined using a Nanodrop spectrophotometer.

Data analysis

An unpaired two-tailed t-test was used to compare het and db/db groups, with a p-value of p<0.05 used as an indication of statistical significance. All comparisons of serum cytokine levels assumed a minimum of four detectable samples. Cytokines with fewer than four detectable samples were considered undetectable for statistical evaluation.

Results

Observed differences in weight, blood glucose, and body composition in db/db mice

We first measured body weight and blood glucose for db/db mice and heterozygous controls at each of the key developmental stages of T2D (5, 6-7, and 11 weeks). As shown in Figure 1, db/db mice showed both increased body weight (Figure 1A) and blood glucose (Figure 1B) as early as 6-7 weeks of age. By 11 weeks, there was a more substantial difference in weight (P < 0.001) and blood glucose (P < 0.001) when compared to het mice. There were no significant differences in either parameter between het and db/db mice at 5 weeks.

Figure 1.

Figure 1

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Db/db mice have progressively higher (A) body weight and (B) blood glucose with increasing age compared to het mice. **P< 0.01, ***P<0.001.

To further examine whether there could be more nuanced differences between strains in the early stages of disease progression, we examined body composition by DEXA for the 5-week-old mice only. As shown in Table 1, substantial differences in fat pads, bone mineral content, and percent body fat were observed between non-diabetic (het) and pre-diabetic (db/db) mice (P < 0.001). There were also variations in bone mineral density (P < 0.01) and to a lesser extent, lean body mass and body fat (P < 0.05). These differences in lean vs. fat mass may account for the similarity in total body weight at this age.

Table 1. Key body composition and DEXA (Dual-energy X-ray absorptiometry) results for db/db (pre-diabetic) and het mice at 5-weeks of age.

Measurement heterozygous db/db
Weight (g) 20.7 ± 0.9 21.2 ± 1.0
Blood Glucose (mg/dL) 154 ± 3 182 ± 28
Fasting BG (mg/dL) 146 ± 5 128 ± 22
Fat Pads (mg) *** 189 ± 26 620 ± 57
BMD (mg/cm2) ** 35 ± 1 30 ± 1
BMC (mg) *** 237 ± 15 136 ± 6
Lean Body Mass (g) * 15.8 ± 0.7 13.9 ± 0.5
Body Fat (g) * 3.8 ± 0.3 6.6 ± 0.7
% Body Fat *** 19 ± 1 32 ± 1
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*

P<0.05

**

P< 0.01

***

P<0.001

Serum cytokine differences between strains at each age

Cytokine milieu differences between strains at the various ages were very few. Among 32 cytokines tested, 12 cytokines were not detectable (n<4 samples/strain) across all age groups. The remaining cytokines that could be evaluated showed no differences between db/db and het at either 6-7 weeks or 11 weeks. The only statistical difference between strains was observed for serum IL-1a from the 5-week-old mice. IL-1a was 322+/-67 ng/ml in db/db mice (n=15) vs. 574+/-86 ng/ml in het controls (n=14, P=0.03).

CXCL1 and CXCL5 associated with obesity and hyperglycemia

We hypothesized that serum levels of cytokines might also vary within the diabetes-prone strain as the disease progresses to obesity and to hyperglycemia. We thus made comparisons of serum cytokine levels between the most vs. least obese db/db mice or between the most vs. least hyperglycemic db/db mice. Because there were no cases of hyperglycemia or obesity among the youngest mice, analysis was focused on the transition to diabetes in the 6-7 and 11-week-old groups. As shown in Figure 2A, serum levels of CXCL1 and CXCL5 were both higher in obese mice (body weight >40g, n=6) compared to non-obese mice (body weight <35g, n=10, P < 0.001). Note that because serum levels of different cytokines can differ by orders of magnitude, data are presented for cytokine levels in obese mice as a percent of the cytokine levels in non-obese controls. Scatter plots for CXCL1 and CXCL5 vs. body weight are shown in Figure 2B and C, respectively. As shown in Figure 2D, serum levels of CXCL1 were similarly higher among hyperglycemic mice (blood glucose >400 mg/dl, n=5) compared with non-hyperglycemic mice (blood glucose <250 mg/dl, n=8, P < 0.001). CXCL5 was increased as well, but not significantly (P=0.098). Scatter plots for each chemokine vs blood glucose are shown in Figure 2E-F. See also Supplemental Figure 1 for serum cytokine levels reported in pg/ml.

Figure 2.

Figure 2

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CXCL1 and CXCL5 are closely associated with obesity and hyperglycemia. (A) Serum levels of cytokines/chemokines in obese db/db mice (body weight: 43.4 ± 0.4 g, n=6 mice) as a percent of non-obese controls (29.0 ± 1.1 g, n=13 mice). (B-C) Scatter plots of serum CXCL1 levels (B) and CXCL5 levels (C) vs. body weight. (D) Serum levels of cytokines/chemokines in hyperglycemic db/db mice (blood glucose: 519±23 mg/dl, n=6 mice) as a percent of non-hyperglycemic controls (193±13 mg/dl, n=8 mice). (E-F) Scatter plots of serum CXCL1 levels (B) and CXCL5 levels (C) vs. blood glucose. *P<0.05. See supplemental Table 1 for cytokine/chemokine values in pg/ml.

Increased gene expression of Cxcl1 and Cxcl5 in pancreatic islets in response to cell stress

We next examined various stressors hypothesized to trigger beta-cell failure in T2D (Montane, et al. 2014) for their effects on Cxcl1 and Cxcl5 gene expression. Islets from CD-1 mice were exposed for 48-hrs to one of the following stressors: 20 nM rotenone as a model of oxidative stress (Hoehn, et al. 2009), 100nM thapsigargin as a model of ER stress (Eizirik, et al. 2008), 10 pg/ml IL-1β + 20 pg/ml IL-6 as a model of low-grade inflammation (cytokines; (O'Neill, et al. 2013, Spranger, et al. 2003)), 28 mM glucose as a model of glucotoxicity (28G, (Tang, et al. 2012)), or free fatty acids (FFA: 50 μM palmitate + 100 μM oleate + 50 μM linoleate) as a model of lipotoxicity (Watt, et al. 2012). Islets incubated in standard RPMI 1640 media containing 10% fetal bovine serum and 1% penicillin/streptomycin were used as controls. As shown in Figure 3, we found that cytokine treatment substantially stimulated Cxcl1 (∼50-fold increase, p<0.001) and Cxcl5 expression (∼80-fold, p<0.001). Thapsigargin also appeared to consistently stimulate Cxcl1 expression (Figure 3A), but the degree of stimulation was highly variable across trials and did not reach significance (3.7-, 7.8-, 16.5-, and 55.5-fold increase; P=0.14). As shown in Figure 3B, thapsigargin-induced Cxcl5 expression showed similar variability (2.3-, 11.8-, 23.6-, and 44.0-fold increase; P=0.07). FFA treatment also mildly, but significantly, upregulated Cxcl5 expression by ∼8-fold (Figure 3B, P<0.05). Overall, exposure to low-dose cytokines had the most robust effect on Cxcl1 and Cxcl5 expression, suggesting that the downstream effects of low-grade inflammation may be mediated, at least in part, by these chemokines.

Figure 3.

Figure 3

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Induction of CXCL1 and CXCL5 after treatment with various cell stressors. (A) CXCL1 and (B) CXCL5 expression in CD-1 islets following a 48-hour treatment with 20 nM rotenone, 100nM thapsigargin, 10 pg/ml IL-1β + 20 pg/ml IL-6 (cytokines), 28 mM glucose (Glucose 28G), or free fatty acids (FFA): 50 μM palmitate + 100 μM oleate + 50 μM linoleate. Islets incubated in RPMI 1640 for 48 hours were used as controls. N=4 independently isolated sets of islets for each condition (note one outlier was removed from the 28G set for CXCL5). #P<0.10, *P<0.05, ***P<0.001 by two tailed t-test. Error bars represent SEM.

Combined effect of CXCL1 and CXCL5 on islet function

We previously showed that circulating levels of proinflammatory cytokines could directly affect islet function (O'Neill, et al. 2013). We thus examined whether CXCL1 and CXCL5 could have direct impact on pancreatic islet function at concentrations consistent with serum levels. Pancreatic islets were treated overnight with individual dosages of 100 pg/ml CXCL1, 10 ng/ml CXCL5, both or neither; these doses approximate the serum levels measured in the 32-plex cytokine panel. Islet function was then assessed by glucose-stimulated insulin secretion. As shown in Figure 4A, we did not observe any significant differences in insulin release during incubation in low (3 mM) glucose among treatment groups, although there was a slight tendency for greater insulin release among chemokine-treated islets compared to untreated controls (not significant, P>0.25). Chemokines also had no affect on insulin secretion in stimulatory glucose (11 mM) conditions (Figure 4B). This lack of effect on insulin release is not necessarily surprising. We have previously shown that other proinflammatory cytokines in combination at low levels do not significantly affect insulin release in normal healthy islets, but they do disrupt calcium handling (Dula, et al. 2010, O'Neill, et al. 2013).

Figure 4.

Figure 4

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CXCL1 and CXCL5 do not affect insulin secretion. (A) Insulin secretion from islets in low (3 mM) glucose following overnight incubation in one of the following conditions: untreated, 100 pg/ml CXCL1, 10 ng/ml CXCL5, or both CXCL1 and CXCL5. (B) Insulin secretion from the same islets exposed to 11 mM glucose. Sets of 20 islets were used for each condition (N=9 replicate sets of islets per condition). No significant differences were observed.

We next examined islet calcium responses to glucose stimulation following overnight exposure to 100 pg/ml CXCL1, 10 ng/ml CXCL5, both chemokines, or neither. As shown in Figure 5A, overnight exposure to CXCL1 had no effect on basal calcium (3mM glucose), the phase 1 response to glucose stimulation (also called the peak response), or the phase 2 response (also called the plateau). As shown in Figure 5B, overnight exposure to CXCL5 similarly had no effect on intracellular calcium. Since CXCL1 and CXCL5 both bind to the same receptor, CXCR2, we hypothesized that these two chemokines could have a synergistic effect. As shown in Figure 5C, a combined treatment of 100 pg/ml CXCL1 and 10 ng/ml CXCL5 resulted in a significant decrease in the peak calcium response to glucose stimulation. The peak calcium response to glucose stimulation was reduced by ∼40% (Figure 5D, p<0.01) and the sustained plateau response by ∼15% among six trials (Figure 4D, p<0.05). This supports our hypothesis, suggesting that the presence of both serum CXCL1 and CXCL5 is necessary to affect islet function.

Figure 5.

Figure 5

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Synergistic effect of CXCL1 and CXCL5. Representative traces of glucose-stimulated calcium (GSCa) responses for islets treated overnight with (A) 100 pg/ml CXCL1 (n=5) vs. untreated controls (n=7), (B) 10 ng/ml CXCL5 (n=8) vs. untreated controls (n=6), or both CXCL1 and CXCL5 (n=11) vs. untreated controls (n=10). Each panel shows islets recorded from one of at least three trials conducted per treatment. (D) Mean values (calculated in nM) for basal calcium, phase 1 (peak), and phase 2 (plateau) responses to glucose stimulation for islets treated overnight with 100 pg/ml CXCL1 + 10 ng/ml CXCL5 (n=36) compared to untreated islets (n=42). Six trials conducted in total. *P<0.05, **P<0.01.

Discussion

In this study, we provide evidence that CXCL1 and CXCL5 are central to low-grade systemic inflammation associated with islet decline in T2D. We showed that 1) only CXCL1 and CXCL5 were significantly associated with the onset of obesity and hyperglycemia in serum panel measurements of 32 cytokines/chemokines, 2) cytokine-induced stress induced substantial upregulation of Cxcl1 and Cxcl5 expression in islets, and 3) overnight exposure to CXCL1 and CXCL5 together could disrupt normal islet function. Collectively, these data suggest that these chemokines play a role both in systemic inflammation as evidenced by the increased levels in serum and in the inflammatory response within the islet itself.

The primary source of proinflammatory cytokines in obesity is adipose tissue. Both resident immune cells in adipose tissue and adipocytes themselves can contribute to the increase in circulating cytokines. Among 32 cytokines/chemokines tested in mouse serum, only CXCL1 and CXCL5 were positively correlated with the development of obesity and hyperglycemia. Our data are consistent with other studies showing that high fat diet can increase CXCL1 levels in adipose tissue (Oliveira, et al. 2013) and that serum CXCL5 is elevated in serum of human obese individuals compared to lean individuals (Chavey, et al. 2009). Conversely, CXCL5 concentration is decreased in obese subjects following weight loss (Chavey, et al. 2009, Kovacikova, et al. 2011). We demonstrated that exposure to low-dose proinflammatory cytokines cause substantial upregulation of Cxcl1 and Cxcl5 mRNA in islet tissue, suggesting that islets may also be a source of CXCL1 and CXCL5.

It should be noted that we cannot exclude age as a factor driving our observed changes in chemokine levels in db/db mice. However, there are reasons to favor the hypothesis that these chemokines are associated with obesity and hyperglycemia, more so than age alone. First, although most obese/hyperglycemic mice were of 11 weeks of age, one diabetic mouse came from the 6-7-week age group and one 11-week-old mouse was not included among the obese or hyperglycemic category. Some mice were also excluded from analysis because they fell between the two cutoffs for normal blood glucose vs. hyperglycemic. Second, similar associations between blood glucose and CXCL1 were found with similar stratified analysis for heterozygous controls. We observed six mice (2 at 6-7 weeks and 4 at 11 weeks of age) that had non-fasted blood glucose levels of 210-250 mg/dl, which we compared with 9 mice with blood glucose levels <175 mg/dl. CXCL1 levels were borderline higher (p=0.056) in the mice with the higher blood glucose level. Differences were not observed for CXCL5, however. Similar analysis in heterozygous mice was not possible for body weight because weight differences were small and entirely age-dependent. Third, our data are consistent with other groups that have reported a relationship between these chemokines and obesity, insulin resistance, and type 2 diabetes (Chavey, et al. 2009, Oliveira, et al. 2013, Sajadi, et al. 2013, Westwell-Roper, et al. 2011), for which age was not a factor.

Whether derived from fat tissue, islets, immune cells or other sources, our data suggest that CXCL1 and CXCL5 can directly impact islet function. Although neither CXCL1 nor CXCL5 alone appeared to affect islets, overnight exposure to both CXCL1 and CXCL5 at concentrations detected in serum significantly reduced the calcium response to glucose stimulation, a key component of the stimulus-secretion pathway for insulin (Ramadan, et al. 2011, Straub & Sharp. 2002). Since CXCL1 and CXCL5 both bind to the chemokine receptor CXCR2, it is possible that both ligands are required to activate CXCR2 to produce downstream effectors that act on islet cells. Ours is the first evidence that these chemokines can directly affect islet function.

Whether the primary purpose of CXCL1 and CXCL5 in islets is to initiate an immune response or to modify islet activity remains an open question. Many endocrine tissues, including the endocrine cells within pancreatic islets, have been shown to express the CXCR2 receptor (Tecimer, et al. 2000), leaving open the possibility that the effects of these chemokines are mediated in an autocrine or paracrine manner entirely within the islet. Blockade of the CXCR1/2 pathway improved islet engraftment in mice and human transplant recipients, and blockade also reduced recruitment of leukocytes and NKT cells to the site of the islet graft in mice (Citro, et al. 2012). These findings suggest that blocking CXCR2 directly reduces inflammatory responses, but the improved islet engraftment could also be due effects of blockade within the islet improving islet function. In a cyclophosphamide-induced transgenic mouse model of type 1 diabetes, marked upregulation of both CXCL1 and CXCL5 was thought to derive from inside the inflammatory infiltrate, not the islet cells themselves, suggesting primarily an immune-mediated response (Matos, et al. 2004). Our findings suggest that CXCL1 and CXCL5 can synergistically inhibit the function of islets in vitro, where the islets are isolated from immune input. However, various resident immune cells, particularly macrophages, have been observed in isolated islets (Boni-Schnetzler, et al. 2008), so we cannot rule out these possible effects.

Regarding the regulation of CXCL1 and CXCL5 within islets, we examined a number of stressors that are hypothesized to trigger islet decline and failure in type 2 diabetes (Donath, et al. 2005). The combination of IL-1beta and IL-6 at the low levels associated with low-grade inflammation had by far and away the strongest effect on Cxcl1 and Cxcl5 gene expression. This stands to reason since IL-1beta has been previously shown to upregulate Cxcl1 and that this upregulation is dependent upon activation of NFkB (a target of IL-1beta signaling) and STAT signaling (associated with IL-6) (Burke, et al. 2014). Increased circulating levels of IL-1B and IL-6 are associated with increased risk of type 2 diabetes (Spranger, et al. 2003), and we have shown previously that circulating levels of these cytokines can increase islet dysfunction and apoptosis in islets from diabetes-prone mice (O'Neill, et al. 2013). We also observed in the present study that exposure to free fatty acids upregulated Cxcl5 (and CXCL1 to a minor extent), which is consistent with palmitate-induced Cxcl1 expression observed in human islets (Igoillo-Esteve, et al. 2010). Finally, thapsigargin-induced ER stress also appeared to upregulate Cxcl1 and Cxcl5, though the degree of upregulation was highly variable from trial to trial. This is intriguing since silencing of the transcription factor C/EBP-delta has been linked to increased Cxcl1 expression and increased Ddit3 expression (also known as CHOP, a key pro-apoptotic factor in ER stress) in rat islets and beta-cell lines (Moore, et al. 2012).

CXCL1 and CXCL5 are thus highly sensitive to low levels of inflammation in islets, and these same chemokines appear to be capable of synergistically affecting islet function. Our data suggest that CXCL1 and CXCL5 are markers of islet dysfunction, and they may be key instigators of islet failure in type 2 diabetes. More work is required to determine why islets are so strongly induced to produce these chemokines and to determine whether CXCL1 and CXCL5 act on endocrine cells or immune cells within the islet or both to inhibit islet function.

Supplementary Material

1

Acknowledgments

Mouse islets were acquired through the UVA Cell and Islet Isolation Core facility. We would like to thank Dr. Susanna Keller and Stefan Hargett in the UVA Diabetes Center Animal Characterization Core for performing the DEXA and analyzing the data.

Funding: This work was supported by National Institutes of Health K01 DK081621 and R01 DK089182 to C.S.N.

Footnotes

Declaration of Interest: There is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Author Contributions: Craig S. Nunemaker: wrote manuscript, designed experiments, acquired and analyzed data, edited manuscript, provided funding. C.S.N. is guarantor of this article and, as such, has full access to all the data in the study and takes responsibility for the integrity and accuracy of the data.

H. Grace Chung: acquired and analyzed data, edited manuscript

Gretchen M. Verrilli: acquired and analyzed data

Kathryn L. Corbin: acquired data

Aditi Upadhye: acquired data, edited manuscript

Poonam R. Sharma: acquired and analyzed data, developed methods.

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