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

Abstract

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.

Fig. 1.

Experimental setup and workflow for comparison of diet and age related changes in epididymal adipose proteome. A, Changes related to age were determined by comparing short term and long term diets within the same diet type, whereas short term and long term changes because of diet were determined by comparing the different diets for the same duration. B, Twenty mice at 8 weeks of age were placed on either low fat or high fat diets for either a short (8 weeks) or long (18 weeks) duration (5 mice per experimental group). Epididymal adipose was collected, lysed, and 100 mg subjected to trypsin digestion. Peptides from each individual sample, and from pooled internal reference samples, were randomly distributed and labeled across three TMT experiments. Following labeling, samples were pooled within their TMT experiment and separated with nine fraction two-dimensional reverse phase chromatography. Tandem mass spectrometry data were collected on the Orbitrap Fusion and proteins identified using Proteome Discoverer. C, Reporter ion intensities were processed and normalized first within TMT experiments and then across TMT experiments using internal reference scaling (IRS) normalization. D, Differentially expressed proteins were determined through group comparisons in edgeR and further characterized through gene enrichment and network analysis. Representative proteins were validated with Western blotting.

Fig. 2.

Metabolic parameters. All measurements were taken from mice on short-term or long-term low fat (LF) or high fat (HF) diets. Body weight (A) and epididymal adipose weight (B) were measured at the time of collection and used to determine adiposity (C): short-term low fat n = 10, short term high fat n = 12, long-term low fat n = 10, long-term high fat n = 8. D, Plasma glucose levels measured after a 16 h fast: short-term low fat n = 10, short term high fat n = 8, long-term low fat n = 31, long-term high fat n = 13. Plasma insulin (E), cholesterol (F), and triglycerides (G) were measured at the time of sacrifice, after a 4 h fast. For both triglycerides and insulin measurements: short-term low fat n = 11, short term high fat n = 8, long-term low fat n = 12, long-term high fat n = 8. For cholesterol: short-term low fat n = 11, short term high fat n = 11, long-term low fat n = 12, long-term high fat n = 8. Insulin (H) and glucose tolerance (I) tests were performed after a 4 h fast. For insulin tolerance tests: short-term low fat n = 12, short term high fat n = 16, long-term low fat n = 8, long-term high fat n = 10. For glucose tolerance tests: short-term low fat n = 9, short term high fat n = 13, long-term low fat n = 8, long-term high fat n = 8. All error bars are standard error of the mean. Significance was determined by ANOVA followed by a Tukey's posthoc analysis for multiple comparisons. For D–G significance is indicated as * for p < 0.05, **** for p < 0.0001, ns for not significant. For H-I significance is indicated as (a), short-term HF versus Long-term HF; (c), short-term LF versus long-term LF; (d), short-term LF versus short-term HF; an (ns), not significant. All error bars are standard error of the mean.

Fig. 3.

Sample acquisition and overview of data characteristics. A, Sample cluster heatmap analysis was performed with hierarchical clustering using the Pearson correlation method. B, Results from each TMT experiment database search. C, Venn diagram of proteins with significantly different abundance (FDR < 0.1) from each experimental group comparison.

Fig. 4.

Fold change distribution in comparisons. Log fold-change distribution histograms comparing (A) long-term high fat diet to short-term high fat diet, and (B) long-term high fat diet to long-term low fat diet. C–F, Volcano plots from different group comparisons. Gray points represent samples with p < 0.05, orange represent log₂ fold change > 0.5, purple represent both a log₂ fold change > 0.5 and p < 0.05, and green points represent an adjusted p < 0.1 and a log₂ fold change > 0.5.

Fig. 5.

Visualization of changing proteins and their biological pathways. A–D, Gene enrichment analysis was performed for proteins with FDR > 0.1, with DAVID/EASE, PANTHER, KEGG, and STRING databases. Functional categories were compiled and heatmaps generated from categories containing 2 or more protein groups.

Fig. 6.

Comparison of expression level measurements. A, Representative proteins from each group comparison were blotted from epididymal adipose tissue cell lysate. Loading controls were used to determine relative expression through analysis with ImageJ software. B, The reporter ion intensities for the blotted proteins were also plotted for comparison. All plots are mean with the standard error of the mean, and are analyzed using Student's t test.

Fig. 7.

The top key driver genes in response to aging and high-fat diet in adipose. The bigger nodes correspond to key driver genes whereas the different colors represent genes encoding protein signatures from different categories. The full list of key driver genes can be found in supplemental Table S3.