Using SRM-MS to quantify nuclear protein abundance differences between adipose tissue depots of insulin-resistant mice

Abstract

Insulin resistance (IR) underlies metabolic disease. Visceral, but not subcutaneous, white adipose tissue (WAT) has been linked to the development of IR, potentially due to differences in regulatory protein abundance. Here we investigate how protein levels are changed in IR in different WAT depots by developing a targeted proteomics approach to quantitatively compare the abundance of 42 nuclear proteins in subcutaneous and visceral WAT from a commonly used insulin-resistant mouse model, Lepr(db/db), and from C57BL/6J control mice. The most differentially expressed proteins were important in adipogenesis, as confirmed by siRNA-mediated depletion experiments, suggesting a defect in adipogenesis in visceral, but not subcutaneous, insulin-resistant WAT. Furthermore, differentiation of visceral, but not subcutaneous, insulin-resistant stromal vascular cells (SVCs) was impaired. In an in vitro approach to understand the cause of this impaired differentiation, we compared insulin-resistant visceral SVCs to preadipocyte cell culture models made insulin resistant by different stimuli. The insulin-resistant visceral SVC protein abundance profile correlated most with preadipocyte cell culture cells treated with both palmitate and TNFα. Together, our study introduces a method to simultaneously measure and quantitatively compare nuclear protein expression patterns in primary adipose tissue and adipocyte cell cultures, which we show can reveal relationships between differentiation and disease states of different adipocyte tissue types.

Keywords: adipocytes; insulin resistance; obesity; peroxisome proliferator-activated receptors; quantitative proteomics; selected reaction monitoring mass spectrometry.

Fig. 1.

Development of a method to quantitatively profile nuclear protein concentrations in different adipose depots in insulin-resistant versus control mice. A: Adipose tissues were digested with collagenase and separated into mature adipocytes and SVCs. Nuclear proteins were isolated from cells and digested using trypsin. B: To carry out SRM-MS analysis, the samples were injected into a triple-quadrupole mass spectrometer, and the intensity of specifically targeted peptides was measured over time. C: Total ion chromatogram of adipocytes isolated from C57BL/6J mice. Heavy peptides (internal standards) were added to each sample at a known concentration. The heavy peptides (blue) and light endogenous peptides (red) eluted at the same time. The ratio of the light to heavy peptides was calculated to determine relative abundance of each peptide.

Fig. 2.

Nuclear protein expression levels are changed differently in visceral and subcutaneous adipocytes in insulin-resistant mice. A: The insulin sensitivities of 10-week-old db/db and C57BL/6J mice were determined by ITT and GTT. Blood glucose levels subsequent to intraperitoneal injection of insulin or glucose were monitored for the indicated times. Error bars show SEM. The ITT was carried out on nine db/db and eight C57 mice. The GTT was carried out on six db/db and four C57 mice. *P < 0.05 determined by Student’s t-test. B: Heat map showing changes in protein expression in visceral and subcutaneous fat in insulin-resistant mice plotted on a log-scale. Each value represents the average of three experiments (biological replicates). Each experiment used adipose tissue from either six C57BL/6J or two db/db mice. See supplementary Fig. 2 for bar plots with error bars. The proteins that are most differentially expressed between visceral and subcutaneous insulin-resistant adipocytes are marked in red.

Fig. 3.

The proteins that are most differentially expressed between insulin-resistant visceral and subcutaneous fat affect adipogenesis. A: OP9 cells were differentiated over 4 days in culture following a standard protocol. Images for BODIPY- and PPARG-stained cells are shown at different time points during differentiation. Scale bar represents 40 μm. B, C: OP9 cells were transfected on day 0 with the indicated siRNA and differentiated in culture. siRNA targeting Yfp was used as a negative control, and siRNA targeting Pparg was used as a positive control. B: Cells were fixed at days 1–4 during differentiation and stained for PPARG intensity. Each datapoint (square) on the heatmap represents the average PPARG intensity in ∼15,000 cells transfected with the indicated target siRNA (siTarget) divided by the average PPARG intensity in ∼15,000 cells transfected with control siRNA targeting YFP and fixed at day 1 or 24 h after transfection (siYFP₁). C: Cells were fixed at days 3 and 4, and stained for BODIPY to assess lipid content. Each datapoint on the heatmap represents the average BODIPY intensity in ∼15,000 cells transfected with the indicated target siRNA (siTarget) divided by the average BODIPY intensity in ∼15,000 cells transfected with control siRNA targeting YFP and fixed at day 3 or 72 h after transfection (siYFP₃).

Fig. 4.

Immunocytochemistry analysis indicates that visceral, but not subcutaneous, SVCs are defective in adipogenesis. A: SVCs isolated from visceral and subcutaneous adipose tissues of db/db and C57BL/6J mice were cultured and analyzed by immunocytochemistry using anti-pAKT. Intensity levels in response to insulin were quantified and plotted in a bar graph. For each biological replicate, ∼5,000 cells were analyzed. B: SVCs from visceral and subcutaneous adipose tissues were differentiated over 8 days in culture. Cells were stained with BODIPY and Hoescht. C: On day 8, cells were also stained for PPARG and CEBPA, and intensities were quantified. For each biological replicate, ∼8,000 cells were analyzed. Error bars indicate SEM (n = 3 biological replicates). *P < 0.05 determined by the Student’s t-test.

Fig. 5.

TNFα and PA induce IR and defective differentiation in cell culture. A: OP9 preadipocytes were treated with TNFα, PA, or both TNFα and PA for 24 h. Water was used as a control for TNFα, and BSA-ethanol (BSA) was used as a control for PA and PA+TNFα treatments. Insulin sensitivity was determined by staining cells for pAKT by immunocytochemistry. Intensities were quantified and plotted on a bar graph. B: To determine the effect of different treatments on differentiation, OP9 cells were differentiated in the presence of TNFα, PA, or both TNFα and PA. Cells were stained for PPARG, CEBPΑ, BODIPY, and pAKT on day 4, and intensities were quantified. Error bars indicate SEM (n = 3 biological replicates). For each biological replicate, ∼15,000 cells were analyzed. *P < 0.05 determined by the Student’s t-test.

Fig. 6.

Principal component analysis shows that the protein profiles of insulin-resistant primary adipocytes, primary SVCs, and OP9 cell culture models are distinct based on changes in protein abundances. The proximity of the clusters indicates how similar the samples are, and interestingly, the protein profile of visceral SVCs most closely matches that of OP9 preadipocytes treated with both PA and TNFα. Supplementary Fig. 6 shows how the different proteins contribute to the first two principal components.