Deficiency of FcεR1 increases body weight gain but improves glucose tolerance in diet-induced obese mice - PDF

Description
Deficiency of FcεR1 increases body weight gain but improves glucose tolerance in diet-induced obese mice The Harvard community has made this article openly available. Please share how this access benefits

Please download to get full document.

View again

of 28
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.
Information
Category:

Genealogy

Publish on:

Views: 15 | Pages: 28

Extension: PDF | Download: 0

Share
Transcript
Deficiency of FcεR1 increases body weight gain but improves glucose tolerance in diet-induced obese mice The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Citation Published Version Accessed Citable Link Terms of Use Lee, Yun-Jung. Conglin Liu, Mengyang Liao, Galina K. Sukhova, Jun Shirakawa, Meriem Abdennour, Karine Iamarene, Sebastien Andre, Karen Inouye, Karine Clement, Rohit N. Kulkarni, Alexander S. Banks, Peter Libby, Guo-Ping Shi Deficiency of FcεR1 increases body weight gain but improves glucose tolerance in diet-induced obese mice. Endrocrinology 156 (11): doi: /en March 12, :07:50 AM EST This article was downloaded from Harvard University's DASH repository, and is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at (Article begins on next page) Deficiency of FcεR1 increases body weight gain but improves glucose tolerance in diet-induced obese mice Yun-Jung Lee, Conglin Liu, Mengyang Liao, Galina K. Sukhova, Jun Shirakawa, Meriem Abdennour, Karine Iamarene, Sebastien Andre, Karen Inouye, Karine Clement, Rohit N. Kulkarni, Alexander S. Banks, Peter Libby, Guo-Ping Shi Department of Medicine, Brigham and Women s Hospital and Harvard Medical School, Boston, MA 02115, USA (Y.J.L., C.L., M.L., G.K.S., K.I., A.S.B., P.L., G.P.S.) Department of Cardiology, Institute of Clinical Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (C.L.) Institute of Cardiology, Union Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China (M.L.) Institute of Cardiometabolism and Nutrition, ICAN; INSERM, UMRS U1166, NutriOmique team, Paris, F France; Université Pierre et Marie Curie-Paris6, NutriOmique team, Paris, F France (M.A., S.A., K.C.) Department of Genetics and Complex Diseases, School of Public Health, Harvard University, Boston, MA (K.I.) Department of Cell Biology, Joslin Diabetes Center and Harvard Medical School, Boston, MA (J.S., R.N.K.) Running Title: FcεR1 in obesity and diabetes Key words: IgE, FcεR1, obesity, diabetes, glucose uptake, adipogenesis Disclosure summary: All authors declare no duality of interest associated with this study Abstract: 209 words Manuscript length: 4,616 words Figures: 7 Corresponding author: Guo-Ping Shi, D.Sc. Cardiovascular Medicine Brigham and Women s Hospital 77 Avenue Louis Pasteur, NRB-7 Boston, MA 02115, USA Tel.: Fax: Abstract Prior studies demonstrated increased plasma immunoglobulin E (IgE) in diabetic patients, but the direct participation of IgE in diabetes or obesity remains unknown. This study found that plasma IgE levels correlated inversely with body weight, body mass index, and body fat mass among a population of randomly selected obese women. IgE receptor FcεR1-deficient (Fcer1a / ) mice and diet-induced obesity (DIO) mice demonstrated that FcεR1 deficiency in DIO mice increased food intake, reduced energy expenditure, and increased body weight gain, but improved glucose tolerance and glucose-induced insulin secretion. White adipose tissue (WAT) from Fcer1a / mice showed increased expression of phospho-akt, C/EBPα, PPARγ, Glut4, and Bcl-2, but reduced UCP1 and phospho- JNK expression, tissue macrophage accumulation, and apoptosis, suggesting that IgE reduces adipogenesis and glucose uptake, but induces energy expenditure, adipocyte apoptosis, and WAT inflammation. In 3T3-L1 cells, IgE inhibited the expression of C/EBPα and PPARγ, and preadipocyte adipogenesis, and induced adipocyte apoptosis. IgE reduced 3T3-L1 cell expression of Glut4, phospho-akt, and glucose uptake, which concurred with improved glucose tolerance in Fcer1a / mice. This study established two novel pathways of IgE in reducing body weight gain in DIO mice by suppressing adipogenesis and inducing adipocyte apoptosis, while worsening glucose tolerance by reducing Glut4 expression, glucose uptake, and insulin secretion. 2 Introduction Immunoglobulin E (IgE) activates mast cells by binding to its high affinity receptor Fcε receptor-1 (FcεR1). This activity of IgE is essential to allergic responses (1), such as asthma. Recent studies demonstrated that IgE also activates macrophages and T cells (2, 3). All these IgE-targeting cells play detrimental roles in obesity and diabetes (4-6), suggesting the participation of IgE in these metabolic diseases. Although the direct role of IgE in obesity and diabetes remains untested, asthma associates with increased plasma IgE (7) and acts as an important risk factor of obesity and diabetes. Of 4,773 subjects aged 20 and older randomly selected from 10,348 individuals from 2005 to 2006 in the National Health and Nutrition Examination Survey (NHANES) in the United States, IgE concentrations correlated positively with obesity risk but not insulin resistance in asthmatic patients (8). Of 4,321 children aged 2 to 19 from the same population, obese and overweight children had higher plasma total IgE levels, driven largely by allergic sensitivity to foods (9). A respective study of 246 adults with asthma and other atopic disorders revealed that asthmatic patients had higher body mass indices (BMI) than nonasthmatics. Obesity associated with increased serum IgE among those patients (10). Yet in a population study of 666 patients with severe asthma, plasma IgE levels correlated negatively with BMI (11). These studies therefore do not prove the direct participation of IgE in body weight gain. Previous studies investigated IgE in patients and animals with diabetes. A linear regression analysis of a population study of 340 patients aged 55 to 75 revealed a positive correlation between plasma IgE and type-2 diabetes mellitus and prediabetes status. Ordinal logistic regression demonstrated that plasma IgE correlates with the incidence of type-2 diabetes before and after adjusting for common diabetes risk 3 factors (12, 13). In non-obese diabetic (NOD) mice, anti-fcεr1 antibody therapy activated basophils and MCs, but delayed type 1 diabetes (14). These observations from diabetic patients and mice highlight the role of IgE in diabetes. This study design was twofold: to test the direct role of IgE in obesity and diabetes using FcεR1-deficient Fcer1a / mice in diet-induced obese and diabetic mice; and to understand the molecular and cellular mechanism by which this immunoglobulin molecule contributes to these metabolic diseases. Materials and Methods Patients A random selection from a bariatric surgery program from the Institute of Cardiometabolism and Nutrition (ICAN), Pitié-Salpêtrière Hospital (Paris, France) yielded a cohort of 50 Caucasian women with morbid obesity. These patients met the criteria for bariatric surgery (BMI 40 kg/m 2, or 35 kg/m 2 with at least one comorbidity: hypertension, type-2 diabetes, dyslipidemia, or obstructive sleep apnea syndrome), but without allergic or autoimmune diseases or anti-allergy and antiautoimmunity medications that may affect plasma IgE levels. Subjects had stable weights (±3 kg) for at least 3 months before the surgery. Of the 50 patients, 18 (36 %) had type 2 diabetes as defined by a fasting glycemia 7 mmol/l and/or the use of an anti-diabetic drug. The ethics committees of the CPP Ile de France 1 (number ) approved the clinical investigations. All subjects gave written informed consent. Spearman s correlation test helped test the correlation between plasma IgE concentration and clinical and biological parameters at baseline. Patient body composition was determined by dual- 4 energy X-ray absorptiometry (DEXA, Hologic, Bedford, MA). Blood samples were obtained before the bariatric surgery after 12 hours of fasting to measure total cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, insulin, glucose, hemoglobin (HbA1c), leptin, adiponectin, inflammatory markers (highly sensitive C-reactive protein (hs-crp) and interleukin-6 (IL6), and IgE as previously described (12, 13, 15, 16). Mice We used C57BL/6 (Jackson Laboratory, Bar Harbor, ME) and Fcer1a / mice (C57BL/6, N9) (2, 3). All mice used in this study were littermates. Males (or female) mice at 6 weeks of age from each group were fed a high-fat diet (HFD, D12492: 60 kcal% fat, Research Diets Inc. New Brunswick, NJ) for 17 weeks. Mouse body weight was monitored weekly. After 17 weeks on a HFD, mouse total body fat and lean masses were assessed by dual energy X-ray absorptiometry (DEXA; PIXImus, Fitchburg, WI). For calorimetric analysis, these mice were placed individually in an indirect open circuit calorimeter (Oxymax System; Columbus Instruments, Columbus, OH). Oxygen and carbon dioxide concentrations by volume were monitored at the inlet and outlet parts of a partially sealed chamber, through which a known flow of ambient air was forcibly ventilated. The concentration difference measured between the parts was used to compute oxygen consumption (VO 2 ) and carbon dioxide production (VCO 2 ). The consumption and production information were presented in units of ml/kg/h and normalized to 25 C and 760 mmhg. Food intake was investigated by using the Oxymax Feed Scale Device (Columbus Instruments) for three continuous days and data were presented as the average food intake per day of the last two days without considering the first day acclimation 5 period. The physical activity of the mice was monitored with OPTO-M3 Activity Application Device (Columbus Instruments). The movements (other than scratching, grooming, digging, etc.) of each animal were determined by infrared beams in x, y, and z axes. After 17 weeks on a HFD, an intraperitoneal glucose tolerance test (1.5 g glucose/kg body weight) and an insulin tolerance test (ITT) (1.5 U/kg body weight) were also performed after an overnight (16 hours) and daytime 5-hour fast, respectively. Mice were sacrificed and fat tissue was collected. Mice were bred and maintained according to the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health. Harvard Medical School Standing Committee on Animals approved all animal protocols. Cell culture 3T3-L1 (ATCC, CL-173) cells were cultured in Dulbecco s Modified Eagle s Medium (DMEM; Life Technologies, Woburn, MA) including 10% calf serum and L-glutamine. To induce adipogenesis, complete confluent 3T3-L1 cells were cultured in induction media containing DMEM (Life Technologies), 10% fetal bovine serum, L-glutamine, MEM sodium pyruvate, g/ml 3-isobutyl-1-methylxanthine (IBMX; Sigma, St. Louis, MO), 1 mm dexamethasone (Sigma), and 167 µm insulin (Sigma) for 2 days and for additional 6 days without IBMX and dexamethasone. Islet isolation and glucose-stimulated insulin secretion (GSIS) by islets Islets were isolated from 2-month-old male C57BL/6J mice (Jackson Laboratory) by the intraductal collagenase digestion method, as described previously (17). For GSIS assay, 6 after culturing for 12 hours in RPMI 1640 medium containing 5.6 mm glucose and supplemented with 10% fetal calf serum, ten size-matched islets were incubated at 37 C for 1.5 hours in Krebs-Ringer bicarbonate buffer containing 2.8, 8.3 or 22.2 mm glucose with or without IgE (0.01, 0.1, 1, 10, 100 µg/ml). The insulin levels in the culture media were measured using an insulin ELISA kit (Crystal Chem Inc., Downers Grove, IL). FcεR1α mrna levels were measured in total RNA extracted from 50 islets that were incubated at 37 C for 24 hours in RPMI 1640 medium containing 5.6 mm glucose with 10% fetal calf serum in the presence or absence of IgE (0.01, 0.1, 1, 10, 100 µg/ml ). Each quantitative reaction was performed in duplicate. Quantitative real-time PCR Total RNA was extracted from WAT, 3T3-L1 cells, bone marrow-derived macrophages, or islets using a Qiagen RNA extraction kit (Qiagen, Valencia, CA). Quantified total RNA using Nanodrop 2000 (Thermo Fisher Scientific Inc., Waltham, MA) was transcribed into first strand cdna using Superscript First Strand kit (Life Technologies). Real-time PCR (RT-PCR) was performed using SYBR green super mix (Bio-Rad) in Bio-Rad icycler iq to determine the mrna levels of C/EBPα, PPARγ, and three FcεR1 chains (α, β, and γ) using 36B4 (acidic ribosomal phosphoprotein PO) and β-actin as internal controls to normalize gene expression. RT-PCR data was analyzed based on delta delta CT calculation and presented as the fold of change obtained from the value of 2^(- CT). All RT-PCR primer sequences are listed in Supplementary Table 1. Immunoblotting and immunohistochemistry 7 WAT, brown adipose tissue (BAT), and cells were lysed in a RIPA buffer containing 50 mm Tris, ph 7.4, 150 mm NaCl, 2 mm EDTA, 1% NP-40, 0.1% SDS, proteinase inhibitor (Roche Diagnostics Corporation, Indianapolis, IN), and phosphatase inhibitor cocktail (Roche). Tissue lysates were centrifuged at 20,000 xg for 15 min. Supernatant was removed without interrupting the upper layer fat for protein concentration determination using the DC protein assay kit (Bio-Rad, Hercules, CA). Tissue or cell lysate was separated by SDS-PAGE, blotted, and detected with different antibodies, including FcεR1a, glucose transporter-4 (Glut4), Bcl-2, p-jnk, total JNK, p-akt, total AKT, CCAAT/enhancer binding protein-α (CEBPα), peroxisome proliferator-activated receptor-γ (PPARγ), uncoupling protein 1 (UCP1), and β-actin or glyceraldehyde 3- phosphate dehydrogenase (GAPDH). WAT paraffin sections (6 µm) were prepared for immunohistochemistry with antibodies to detect macrophages (Mac-2), T cells (CD3), and FcεR1, and TUNEL staining (In Situ Cell Death Detection Kit, Roche Diagnostics Corp) to detect apoptotic cells. We used AlexaFluor conjugated with different fluorochromes (Invitrogen) to show localization of FcεR1 to inflammatory cells. All antibodies are listed in Supplementary Table 2. ELISA ELISA determined plasma IL6 (ebioscience), monocyte chemotactic protein-1 (MCP-1) (ebioscience), IgE (BD Biosciences, Bedford, MA), insulin (Crystal Chem Inc.) and serum amyloid A (Life Technologies), according to the manufacturers instructions. 2-Deoxyglucose (2DG) uptake assay 8 Preadipocyte 3T3L1 cells were differentiated to adipocytes in a 48-well plate with and without IgE (0, 1, 10, 50 µg/ml). After 2 days, glucose uptake was performed using a 2- deoxyglucose (2DG) uptake measurement kit (Cosmo Bio Co. Ltd., Tokyo, Japan), according to manufacturer s instructions. sirna transfection Both FcεR1α and scramble control sirnas (100 nm, Santa Cruz) were transfected to preadipocyte 3T3-L1 cells in a 12 well-plate after electroporation with an Amaxa Cell Line Nucleofector Kit (Lonza, Allendale, NJ). After 24 hours, cells were differentiated in an induction medium and cultured for 4 days followed by starvation and stimulation with 25 µg/ml IgE for 10 min. Cells were lysed for protein analysis. Cell Cytotoxicity assay Preadipocyte 3T3-L1 cells were differentiated to adipocytes on an 8-well chamber slide or a 96-well plate with and without IgE (50 µg/ml) for 2 8 days before TUNEL staining (In Situ Cell Death Detection Kit, Roche Diagnostics Corp.), cell counting kit-8 (CCK-8), cell viability assay (Dojindo Molecular Technologies, Inc, Rockville, MD), or lactate dehydrogenase cytotoxicity assay (LDH, Promega, Madison, WI), according to the manufacturers instructions. Oil-red O staining Differentiated 3T3-L1 cells with and without IgE (50ug/ml) in a 96-well plate were fixed with 10% formalin for one hour, washed with 100% propylene glycol, and stained with 0.5% oil-red O for 4 hours. This procedure was followed by washing with 85% propylene 9 glycol. For quantitative analysis, stained cell layers were extracted with isopropanol and measured at OD 510 nm. Statistical analysis All human data are expressed as means ± SD. Correlation analyses between IgE concentration and clinical parameters were performed using Spearman's correlation. Regression plots were built after log transformation of IgE values for normalization purpose. All P-values are two-sided, and P-values of 0.05 were considered to be statistically significant. All analyses were performed using R software, version All mouse data were expressed as mean ± SEM. Due to our small sample sizes and often skewed data distributions, we performed a pairwise non-parametric Mann-Whitney test followed by Bonferroni corrections to examine the statistical significance. Results Inverse correlation between human plasma IgE and obesity Data obtained from the 50 obese women (age: 42±11 years, BMI: 50.67±8.26 kg/m 2 ) showed that serum IgE correlated negatively with BMI (P=0.018, Rho= -0.33) (Figure 1A), body weight (P= 0.016, Rho= -0.34) (Figure 1B), and fat mass (P=0.023, Rho= -0.34) (Figure 1C). Fasting glycemia, insulin, HbA1C, triglyceride, high-density lipoprotein HDL, ApoA1, ApoB, aspartate amino-transferase AST, alanine aminotransferase ALT, γ-glutamyl transpeptidase γgt, leptin, adiponectin, IL6, and hs-crp did not associate with IgE levels. Only total cholesterol correlated positively with IgE (P= 0.028, Rho=0.31) (Supplementary Table 3). Of the 50 severely obese patients, 18 10 had type 2-diabetes. Diabetic obese patients were significantly older and exhibited a higher BMI, fasting glycemia, fasting insulin, and HbA1C as expected. These patients also had lower HDL and higher triglyceride, ALT, γgt, IL6 and hs-crp levels than nondiabetic obese patients. Diabetic and non-diabetic obese patients did not exhibit significantly different plasma IgE levels, however (data not shown). FcεR1 deficiency increases body weight gain, but improves glucose tolerance in mice This study monitored the body weight and included glucose and insulin tolerance assays in both male and female WT and FcεR1-deficient Fcer1a / mice. Male (Figure 2A) or female (data not shown) FcεR1-deficient Fcer1a / mice gained significantly more body weight than WT control mice on a HFD. Fcer1a / mice consumed significantly more food and gained more lean and fat mass, as determined by DEXA analysis (Figure 2B). Fcer1a / mice demonstrated significantly improved glucose tolerance but exhibited no difference in insulin tolerance when compared to WT control mice (Figure 2C), suggesting that Fcer1a / mice had improved glucose metabolism but a similar degree of insulin resistance to that of WT mice. Consistently, overnight-fasted Fcer1a / mice exhibited elevated glucose-induced insulin release, which showed no significant difference from WT mice at 90 minutes after the first glucose stimulation (Figure 2D). Islets from WT mice released insulin responding to glucose in a dose-dependent manner, but IgE did not affect islet insulin production at any tested doses of up to 100 µg/ml (Figure 2E). The low level expression of FcεR1 on islets possibly triggered insignificant insulin induction responding to IgE. RT-PCR revealed about 6-fold lower FcεR1α expression on islets than that on bone marrow-derived macrophages (Figure 2F). Non- 11 fasted WT and Fcer1a / mice on a HFD showed no difference between the basal levels of plasma IgE or insulin (Figure 2G). WAT from Fcer1a / mice, however, had significantly lower IgE levels than WT mice (Figure 2H). Although a direct comparison remains impossible, WAT milieu may have much higher IgE concentrations (about 1,600 ng per mg WAT protein from WT mice) than the plasma (about 150 ng/ml from WT mice). Consistent with increased body weight gain, Fcer1a / mice had higher plasma serum amyloid A (SAA), IL6, and MCP-1 than WT control mice after consuming a HFD, although the difference in MCP-1 levels did not reach statistical significance (Figure 2I). Yet data showed significantly fewer Mac2-positive macrophages in both subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) from Fcer1a / mice than those from WT control mice (Figure 3A/3B). VAT from Fcer1a / mice also contained fewer CD3 + T cells than VAT from WT mice (Figure 3C). TUNEL staini
Related Search
Similar documents
View more...
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks