Extended Multiplexing of Tandem Mass Tags (TMT) Labeling Reveals Age and High Fat Diet Specific Proteome Changes in Mouse Epididymal Adipose Tissue

The lack of high-throughput methods to analyze the adipose tissue protein composition limits our understanding of the protein networks responsible for age and diet related metabolic response. We have developed an approach using multiple-dimension liquid chromatography tandem mass spectrometry and extended multiplexing (24 biological samples) with tandem mass tags (TMT) labeling to analyze proteomes of epididymal adipose tissues isolated from mice fed either low or high fat diet for a short or a long-term, and from mice that aged on low versus high fat diets. The peripheral metabolic health (as measured by body weight, adiposity, plasma fasting glucose, insulin, triglycerides, total cholesterol levels, and glucose and insulin tolerance tests) deteriorated with diet and advancing age, with long-term high fat diet exposure being the worst. In response to short-term high fat diet, 43 proteins representing lipid metabolism (e.g. AACS, ACOX1, ACLY) and red-ox pathways (e.g. CPD2, CYP2E, SOD3) were significantly altered (FDR < 10%). Long-term high fat diet significantly altered 55 proteins associated with immune response (e.g. IGTB2, IFIT3, LGALS1) and rennin angiotensin system (e.g. ENPEP, CMA1, CPA3, ANPEP). Age-related changes on low fat diet significantly altered only 18 proteins representing mainly urea cycle (e.g. OTC, ARG1, CPS1), and amino acid biosynthesis (e.g. GMT, AKR1C6). Surprisingly, high fat diet driven age-related changes culminated with alterations in 155 proteins involving primarily the urea cycle (e.g. ARG1, CPS1), immune response/complement activation (e.g. C3, C4b, C8, C9, CFB, CFH, FGA), extracellular remodeling (e.g. EFEMP1, FBN1, FBN2, LTBP4, FERMT2, ECM1, EMILIN2, ITIH3) and apoptosis (e.g. YAP1, HIP1, NDRG1, PRKCD, MUL1) pathways. Using our adipose tissue tailored approach we have identified both age-related and high fat diet specific proteomic signatures highlighting a pronounced involvement of arginine metabolism in response to advancing age, and branched chain amino acid metabolism in early response to high fat feeding. Data are available via ProteomeXchange with identifier PXD005953. The lack of high-throughput methods to analyze the adipose tissue protein composition limits our understanding of the protein networks responsible for age and diet related metabolic response. We have developed an approach using multiple-dimension liquid chromatography tandem mass spectrometry and extended multiplexing (24 biological samples) with tandem mass tags (TMT) labeling to analyze proteomes of epididymal adipose tissues isolated from mice fed either low or high fat diet for a short or a long-term, and from mice that aged on low versus high fat diets. The peripheral metabolic health (as measured by body weight, adiposity, plasma fasting glucose, insulin, triglycerides, total cholesterol levels, and glucose and insulin tolerance tests) deteriorated with diet and advancing age, with long-term high fat diet exposure being the worst. In response to short-term high fat diet, 43 proteins representing lipid metabolism (e.g. AACS, ACOX1, ACLY) and red-ox pathways (e.g. CPD2, CYP2E, SOD3) were significantly altered (FDR < 10%). Long-term high fat diet significantly altered 55 proteins associated with immune response (e.g. IGTB2, IFIT3, LGALS1) and rennin angiotensin system (e.g. ENPEP, CMA1, CPA3, ANPEP). Age-related changes on low fat diet significantly altered only 18 proteins representing mainly urea cycle (e.g. OTC, ARG1, CPS1), and amino acid biosynthesis (e.g. GMT, AKR1C6). Surprisingly, high fat diet driven age-related changes culminated with alterations in 155 proteins involving primarily the urea cycle (e.g. ARG1, CPS1), immune response/complement activation (e.g. C3, C4b, C8, C9, CFB, CFH, FGA), extracellular remodeling (e.g. EFEMP1, FBN1, FBN2, LTBP4, FERMT2, ECM1, EMILIN2, ITIH3) and apoptosis (e.g. YAP1, HIP1, NDRG1, PRKCD, MUL1) pathways. Using our adipose tissue tailored approach we have identified both age-related and high fat diet specific proteomic signatures highlighting a pronounced involvement of arginine metabolism in response to advancing age, and branched chain amino acid metabolism in early response to high fat feeding. Data are available via ProteomeXchange with identifier PXD005953. Obesity is a worldwide epidemic associated with increased incidence of metabolic complications such as type 2 diabetes, hypertension, dyslipidemia, and atherosclerosis. Intra-abdominal adipose tissue is a multifunctional endocrine organ that participates in whole body energy metabolism. Because of its anatomical location, intrinsic properties, and capacity to store and release energy through lipogenesis and lipolysis, it is a primary target of detrimental high fat diets. The obesity-related biological and metabolic changes within abdominal white adipose tissue could elucidate its role in the etiology of obesity related metabolic complications. The rapid spread of obesity and overweight has prompted efforts to understand the biological and metabolic dynamics of white adipose tissue in response to western living. Much progress has been made in defining the transcriptional networks controlling the terminal differentiation of preadipocytes into mature adipocytes or controlling the whole tissue response to high fat diet (1.Rosen E.D. MacDougald O.A. Adipocyte differentiation from the inside out.Nat. Rev. Mol. 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Differential responses of white adipose tissue and brown adipose tissue to caloric restriction in rats.Mech. Ageing Develop. 2012; 133: 255-266Crossref PubMed Scopus (40) Google Scholar). With the same approach, Joo and colleagues identified 70 differentially expressed proteins in WAT versus BAT. Most of the variations were thermogenic and lipogenic enzymes in adipose tissues of obese prone rats (9.Joo J.I. Oh T.S. Kim D.H. Choi D.K. Wang X. Choi J.-W. Yun J.W. Differential expression of adipose tissue proteins between obesity-susceptible and -resistant rats fed a high-fat diet.Proteomics. 2011; 11: 1429-1448Crossref PubMed Scopus (39) Google Scholar). A recent report from Gomez-Serrano et al. using 4-plex isobaric labeling and LC-MS to study human visceral adipose depot described similar findings as ours (11.Gómez-Serrano M. Camafeita E. García-Santos E. López J.A. Rubio M.A. Sánchez-Pernaute A. Torres A. Vázquez J. Peral B. 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We have developed a novel approach that uses tandem mass tags (TMT) 1The abbreviations used are: TMT, tandem mass tags;LC-MS/MS, liquid chromatography-tandem MS;IRS, internal reference scaling;FDR, false discovery rate. 1The abbreviations used are: TMT, tandem mass tags;LC-MS/MS, liquid chromatography-tandem MS;IRS, internal reference scaling;FDR, false discovery rate. (17.Thompson A. Schäfer J. Kuhn K. Kienle S. Schwarz J. Schmidt G. Neumann T. Johnstone R. Mohammed A.K.A. Hamon C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.Anal. Chem. 2003; 75: 1895-1904Crossref PubMed Scopus (1709) Google Scholar) in combination with in line two-dimensional liquid chromatography tandem mass spectrometry (2D LC-MS/MS) to overcome these limitations. Our goals were: (1) to provide a simple, reproducible, and detailed method for proteome analysis of adipose tissue, (2) to identify proteome changes in response to short- versus long-term high fat diet, and (3) to identify aging-related proteome changes while exposed to low versus high fat diet. Through three-dimensional integration of proteome profiles, metabolic profiles, and gene regulatory networks, we have identified unique sets of proteins and gene networks that characterize the changes within adipose tissue in response to short- versus long-term high fat feeding. Short-term high fat feeding was associated with mitochondria related metabolic changes and lipid metabolism, whereas long-term feeding led to extracellular matrix remodeling and activation of the immune system. Mice that grew older either on low or high fat diet shared aging-related responses, such as activation of urea cycle and changes in methionine and sulfur metabolism, whereas extracellular remodeling and immune activation was only captured for mice that grew older on high fat diet, thus indicating an interaction between advancing age and diet For metabolic experiments, we have used n = 8–13 mice per group. For mass spectrometry experiments we have used a subgroup (of the metabolic experiments) of n = 5 mice (biological replicates) per metabolic condition, as described in Fig. 1. Each TMT set (3 total) included 2 pooled control samples for across TMT-plex normalizations (details below). The samples were randomized using an Excel function. The statistical tests used for each experiment are described within each section. Triethylammonium bicarbonate (TEAB), tris(2-carboxyethyl)phosphine (TCEP), Tandem Mass Tag 10-plex isobaric reagents, and organic solvents were from Thermo Fisher Scientific (Rockford, IL). Sequencing grade LysC/trypsin was from Promega (Madison, WI). Unless otherwise noted all other chemicals were from Sigma-Aldrich (St. Louis, MO). All studies were approved by the Institutional Animal Care and Use Committee of the University of Washington. C57Bl/6J male mice (Jackson Labs, #000664) were housed (3–5 mice per cage) in a specific pathogen-free barrier facility in a temperature-controlled room (22 °C) with a 12-h light/dark cycle, and given free access to food and water. At 8 weeks of age, the mice were fed either a low-fat (4%) regular chow diet (Wayne Rodent BLOX 8604; Harlan Teklad Laboratory, Madison, WI), or a high-fat (60% calories from fat, Bioserve, Flemington, NJ, #F1850) diet and were analyzed at 16 weeks and 26 weeks of age. Before necropsy, mice were fasted for 4 h in the morning, bled from the retro-orbital sinus into tubes containing 1 mm EDTA, and euthanized by isofluorane inhalation. Whole epididymal adipose depots were collected, weighted, snap frozen in liquid nitrogen, and stored at −80 °C until analysis. For metabolic measurements, we have based the numbers of mice required on previously published research by our group (18.Pamir N. McMillen T.S. Edgel K.A. Kim F. LeBoeuf R.C. Deficiency of lymphotoxin-α does not exacerbate high-fat diet-induced obesity but does enhance inflammation in mice.. 2012; 302: E961-E971Google Scholar, 19.Pamir N. McMillen T.S. Kaiyala K.J. Schwartz M.W. LeBoeuf R.C. Receptors for tumor necrosis factor-alpha play a protective role against obesity and alter adipose tissue macrophage status.Endocrinology. 2009; 150: 4124-4134Crossref PubMed Scopus (64) Google Scholar) Insulin and glucose tolerance tests were performed after a 4-h fast. Mice were injected intraperitoneally with human insulin (1.0 U/kg body weight; Eli Lilly, Indianapolis, IN) or glucose (1 mg/g body weight) (20.Pamir N. Liu N.-C. Irwin A. Becker L. Peng Y. Ronsein G.E. Bornfeldt K.E. Duffield J.S. Heinecke J.W. Granulocyte/macrophage colony-stimulating factor-dependent dendritic cells restrain lean adipose tissue expansion.J. Biol. Chem. 2015; 290: 14656-14667Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar) and blood glucose level was measured at baseline, 15, 30, 60, and 120 min time points. Under sterile conditions, adipose tissue was extracted and separated into stromal vascular cell and adipocyte fractions (21.Soukas A. Socci N.D. Saatkamp B.D. Novelli S. Friedman J.M. Distinct transcriptional profiles of adipogenesis in vivo and in vitro.J. Biol. Chem. 2001; 276: 34167-34174Abstract Full Text Full Text PDF PubMed Scopus (331) Google Scholar). Minced tissue in digestion buffer (Dulbecco's PBS supplemented by calcium and magnesium, Thermo Scientific) was incubated with 2 mg/ml type I collagenase (Worthington, Lakewood, NJ) for 45 min at 37 °C on an orbital shaker, filtered through 250 μm nylon mesh, and centrifuged at 500 × g for 5 min. The pellet was resuspended in erythrocyte lysis buffer (Cell Signaling, Danvers, MA), incubated at room temperature for 5 min, and then filtered through a 70 μm nylon mesh and washed by centrifugation as above. At the time of sacrifice, blood was collected after a 4 h fast, and insulin, triglyceride, and cholesterol levels were determined using an ultrasensitive insulin ELISA (Linco, Billerica, MA), l-Type TG M assay (Wako Diagnostics, Richmond, VA), and Amplex Red Cholesterol Assay Kit (Invitrogen, Carlsbad, CA). Total RNA samples were isolated from epididymal adipose tissue using the EZNA Total RNA kit II (Omega, Norcross, GA) and quantified by spectrometry. First-strand cDNAs were synthesized from 0.1 to 0.5 mg of total RNA using iScript cDNA synthesis kit (BioRad, Hercules, CA). Primers and probes were purchased from Thermo Fisher; IL12-α (cat: Mm00434165), IL1-β (cat: Mm00434228), RpL32 (cat: Mm02528467), IL-6 (cat: Mm00446191), Tnf-α (cat:Mm00443258). Results were analyzed using the CT method (22.Livak K.J. Schmittgen T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.Methods. 2001; 25: 402-408Crossref PubMed Scopus (123424) Google Scholar). One hundred to 300 mg of epididymal adipose tissue from individual mice was homogenized on ice in 1 ml homogenization buffer (150 mm NaCl, 50 mm HEPES pH 8.5, 1× GBiosciences ProteaseArrest) using a polytron tissue homogenizer. Homogenized samples were spun at 10,000 × g for 10 min at 4 °C and the top lipid layer removed. Supernatant and pellet were lysed by addition of SDS to a final concentration of 2.5% and sonicated three times at 2 watts for 5 s each with 30 s rests between. Chloroform-methanol precipitation was performed to further eliminate lipids. In brief, four parts methanol, two parts chloroform, and three parts water were added to each sample, mixed, and spun down. The top fraction was removed and the protein layer was washed four times with 100% methanol. Proteins were dried by vacuum centrifugation and stored at −80 °C. Epididymal adipose protein samples were reconstituted in 50 mm HEPES with brief sonication to aid in protein solubilization, and protein concentration was determined using the Pierce bicinchoninic acid (BCA) protein assay with a BSA standard (Thermo Fisher Scientific, Rockford IL). The following steps were carried out with 100 μg protein of each sample in 0.1% Rapigest (Waters, Milford, MA). Disulfide bonds were reduced with 5 mm tris(2-carboxyethyl) phosphine (TCEP) for 30 min at 37 °C. Cysteines were alkylated with 15 mm iodoacetamide for 30 min at room temperature in the dark. Excess iodoacetamide was quenched with 5 mm DTT for 15 min at room temperature in the dark. Protein was digested with a mixture of LysC and Trypsin (Cat # V5071, Promega, Madison, WI) at a 1:100 w/w protease/protein ratio for 3 h at 37 °C, then at a 1:50 w/w ratio overnight at 37 °C. Digestion was terminated by the addition of trifluoroacetic acid to 0.5%. Particulates were then removed by spinning at 12,000 × g for 15 min, and peptides were solid phase extracted using Waters Sep-Pak tC18 cartridges according to manufacturer's instructions, dried down, and stored at −80 °C. Peptides were reconstituted in 100 mm triethylammonium bicarbonate (TEAB) and their concentration determined by the BCA assay described above. A pooled sample for normalization between runs was prepared by combining 6.25 μg of peptide from each individual sample. TMT labeling was carried out on 25 μg of peptides from each individual sample and the pooled sample. Samples were randomly distributed between three 10-plex label sets, along with 2 pooled samples per set. TMT 10-plex labeling reagents (0.8 mg) were each dissolved in 52 μl anhydrous acetonitrile (ACN). Each sample containing 25 μg of peptide in 25 μl volume of TEAB buffer was combined with 12 μl of its respective 10-plex TMT reagent and incubated for 1 h at room temperature. Two μl of each reaction mixture was then mixed, 2 μl of 5% hydroxylamine added, and the combined sample incubated for a further 15 min. The mixture was then dried down, dissolved in 5% formic acid, and 2 μg of peptide analyzed by a single 2 h LC-MS/MS method using an Orbitrap Fusion as described below. This run was performed to normalize the total reporter ion intensity of each multiplexed sample and check labeling efficiency. The remaining samples were quenched by addition of 2 μl of 5% hydroxylamine as above, then combined in a 1:1:1:1:1:1:1:1:1:1 ratio based on total reporter ion intensities determined during the normalization run, and dried down in preparation for 2D-LC-MS/MS analysis. TMT (17.Thompson A. Schäfer J. Kuhn K. Kienle S. Schwarz J. Schmidt G. Neumann T. Johnstone R. Mohammed A.K.A. Hamon C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.Anal. Chem. 2003; 75: 1895-1904Crossref PubMed Scopus (1709) Google Scholar), isobaric quantitative labeling reagent, allows up to 10 biological samples to be analyzed in a single mass spectrometry experiment. High-resolution instruments with advanced ion collection methods (23.Senko M.W. Remes P.M. Canterbury J.D. Mathur R. Song Q. Eliuk S.M. Mullen C. Earley L. Hardman M. Blethrow J.D. Bui H. Specht A. Lange O. Denisov E. Makarov A. Horning S. Zabrouskov V. Novel Parallelized Quadrupole/Linear Ion Trap/Orbitrap Tribrid Mass Spectrometer Improving Proteome Coverage and Peptide Identification Rates.Anal. Chem. 2013; 85: 11710-11714Crossref PubMed Scopus (176) Google Scholar) allow highly multiplexed studies where expression changes can be measured with wide dynamic range and excellent accuracy. Multiplexed TMT-labeled samples were reconstituted in 5% formic acid and separated by two-dimensional reverse-phase liquid chromatography using a Dionex NCS-3500RS UltiMate RSLCnano UPLC system. A 20 μl sample (40 μg) was injected onto a NanoEase 5 μm XBridge BEH130 C18 300 μm x 50 mm column (Waters) at 3 μl/min in a mobile phase containing 10 mm ammonium formate (pH 9). Peptides were eluted by sequential injection of 20 μl volumes of 14, 20, 22, 24, 26, 28, 30, 40, and 90% ACN in 10 mm ammonium formate (pH 9) at 3 μl/min flow rate. Eluted peptides were diluted with mobile phase containing 0.1% formic acid at 24 μl/min flow rate and delivered to an Acclaim PepMap 100 μm x 2 cm NanoViper C18, 5 μm trap on a switching valve. After 10 min of loading, the trap column was switched on-line to a PepMap RSLC C18, 2 μm, 75 μm x 25 cm EasySpray column (Thermo Scientific). Peptides were then separated at low pH in the second dimension using a 7.5–30% ACN gradient over 90 min in mobile phase containing 0.1% formic acid at 300 nl/min flow rate. Each second-dimension LC run required 2 h for separation and re-equilibration, so each 2D LC-MS/MS method required 18 h for completion. Tandem mass spectrometry data was collected using an Orbitrap Fusion Tribrid instrument configured with an EasySpray NanoSource (Thermo Scientific). Survey scans were performed in the Orbitrap mass analyzer (resolution = 120,000), and data-dependent MS2 scans performed in the linear ion trap using collision-induced dissociation (normalized collision energy = 35) following isolation with the instrument's quadrupole. Reporter ion detection was performed in the Orbitrap mass analyzer (resolution = 60,000) using MS3 scans following synchronous precursor isolation of the top 10 ions in the linear ion trap, and higher-energy collisional dissociation in the ion-routing multipole (normalized collision energy = 65). RAW instrument files were processed using Proteome Discoverer (PD) version 1.4.1.14 (Thermo Scientific). For each of the TMT experiments, raw files from the 9 fractions were merged and searched with the SEQUEST HT search engine with a Mus musculus Swiss-Prot protein database downloaded July 2015 (16,716 entries). Searches were configured with static modifications for the TMT reagents (+229.163 Da) on lysines and N termini, carbamidomethyl (+57.021 Da) on cysteines, dynamic modifications for oxidation of methionine residues (+15.9949 Da), parent ion tolerance of 1.25 Da, fragment mass tolerance of 1.0005 Da, monoisotopic masses, and trypsin cleavage (max 2 missed cleavages). The large parent ion tolerance was used to increase the number of peptides being scored to improve discrimination of true versus false identifications (24.Hsieh E.J. Hoopmann M.R. MacLean B. MacCoss M.J. Comparison of database search strategies for high precursor mass accuracy MS/MS data.J. Proteome Res. 2010; 9: 1138-1143Crossref PubMed Scopus (99) Google Scholar). Searches used a reversed sequence decoy strategy to control peptide false discovery and identifications were validated by Percolator software (25.Käll L. Canterbury J.D. Weston J. Noble W.S. MacCoss M.J. Semi-supervised learning for peptide identification from shotgun proteomics datasets.Nat. Methods. 2007; 4: 923-925Crossref PubMed Scopus (1368) Google Scholar). Protein false discovery rate (FDR) estimates are unavailable in PD 1.4, but we expect protein FDR to be very low because we are quantifying the intersection of identifications from three TMT sets. Only peptides with q scores ≤ 0.05 were accepted, and at least one unique peptide was required for matching a protein entry for its identification. Search results and TMT reporter ion intensities were exported as text files and processed with in-house scripts. A median reporter ion intensity peak height cutoff of 700 was used, and all reporter ion intensities for unique peptides matched to each respective protein were summed to create total protein intensities. We employed two normalization procedures to handle the 30-plex experiment (3 TMT experiments with 10 channels each). The first was applied within each 10-plex experiment. The grand total reporter ion intensity for each channel was multiplied by global scaling factors to adjust its total intensity to the average total intensity across the 10 channels. This corrects for small sample loading and labeling reaction efficiency differences. MS2 scans are selected stochastically by the mass spectrometer for each peptide. Two identical peptides in two different TMT experiments having identical concentrations would be extremely unlikely to have similar reporter ion signals, because their sampled intensities would depend on the peptide concentration at the time of MS2 sequencing. Therefore, common, pooled internal standards were used to normalize reporter ion intensities of proteins between different TMT experiments. This allowed preservation of individual intensity-scale measurements and avoided calculation of rela