Differential proteomic analysis of white adipose tissues from T2D KKAy mice by LC-ESI-QTOF

Differential Effects of Insulin-Deficient Diabetes Mellitus on Visceral vs. Subcutaneous Adipose Tissue-Multi-omics Insights From the Munich MIDY Pig Model

Adipose tissue (AT) is no longer considered to be responsible for energy storage only but is now recognized as a major endocrine organ that is distributed across different parts of the body and is actively involved in regulatory processes controlling energy homeostasis. Moreover, AT plays a crucial role in the development of metabolic disease such as diabetes. Recent evidence has shown that adipokines have the ability to regulate blood glucose levels and improve metabolic homeostasis. While AT has been studied extensively in the context of type 2 diabetes, less is known about how different AT types are affected by absolute insulin deficiency in type 1 or permanent neonatal diabetes mellitus. Here, we analyzed visceral and subcutaneous AT in a diabetic, insulin-deficient pig model (MIDY) and wild-type (WT) littermate controls by RNA sequencing and quantitative proteomics. Multi-omics analysis indicates a depot-specific dysregulation of crucial metabolic pathways in MIDY AT samples. We identified key proteins involved in glucose uptake and downstream signaling, lipogenesis, lipolysis and β-oxidation to be differentially regulated between visceral and subcutaneous AT in response to insulin deficiency. Proteins related to glycogenolysis, pyruvate metabolism, TCA cycle and lipogenesis were increased in subcutaneous AT, whereas β-oxidation-related proteins were increased in visceral AT from MIDY pigs, pointing at a regionally different metabolic adaptation to master energy stress arising from diminished glucose utilization in MIDY AT. Chronic, absolute insulin deficiency and hyperglycemia revealed fat depot-specific signatures using multi-omics analysis. The generated datasets are a valuable resource for further comparative and translational studies in clinical diabetes research.

Proteomics reveals different pathological processes of adipose tissue, liver, and skeletal muscle under insulin resistance

Type 2 diabetes mellitus is the most common type of diabetes, and insulin resistance (IR) is its core pathological mechanism. Proteomics is an ingenious and promising Omics technology that can comprehensively describe the global protein expression profiling of body or specific tissue, and is widely applied to the study of molecular mechanisms of diseases. In this paper, we focused on insulin target organs: adipose tissue, liver, and skeletal muscle, and analyzed the different pathological processes of IR in these three tissues based on proteomics research. By literature studies, we proposed that the main pathological processes of IR among target organs were diverse, which showed unique characteristics and focuses. We further summarized the differential proteins in target organs which were verified to be related to IR, and discussed the proteins that may play key roles in the emphasized pathological processes, aiming at discovering potentially specific differential proteins of IR, and providing new ideas for pathological mechanism research of IR.

Comprehensive map and functional annotation of the mouse white adipose tissue proteome

White adipose tissue (WAT) plays a significant role in energy metabolism and the obesity epidemic. In this study, we sought to (1) profile the mouse WAT proteome with advanced 2DLC/MS/MS approach, (2) provide insight into WAT function based on protein functional annotation, and (3) predict potentially secreted proteins. A label-free 2DLC/MS/MS proteomic approach was used to identify the WAT proteome from female mouse WAT. A total of 6,039 proteins in WAT were identified, among which 5,160 were quantified (spanning a magnitude of 10⁶) using an intensity-based absolute quantification algorithm, and 3,117 proteins were reported by proteomics technology for the first time in WAT. To comprehensively analyze the function of WAT, the proteins were divided into three quantiles based on abundance and we found that proteins of different abundance performed different functions. High-abundance proteins (the top 90%, 1,219 proteins) were involved in energy metabolism; middle-abundance proteins (90–99%, 2,273 proteins) were involved in the regulation of protein synthesis; and low-abundance proteins (99–100%, 1,668 proteins) were associated with lipid metabolism and WAT beiging. Furthermore, 800 proteins were predicted by SignalP4.0 to have signal peptides, 265 proteins had never been reported, and five have been reported as adipokines. The above results provide a large dataset of the normal mouse WAT proteome, which might be useful for WAT function research.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Protein Expression Profile of Twenty-Week-Old Diabetic db/db and Non-Diabetic Mice Livers: A Proteomic and Bioinformatic Analysis

Type 2 diabetes mellitus is characterized by insulin resistance in the liver. Insulin is not only involved in carbohydrate metabolism, it also regulates protein synthesis. This work describes the expression of proteins in the liver of a diabetic mouse and identifies the metabolic pathways involved. Twenty-week-old diabetic db/db mice were hepatectomized, after which proteins were separated by 2D-Polyacrylamide Gel Electrophoresis (2D-PAGE). Spots varying in intensity were analyzed using mass spectrometry, and biological function was assigned by the Database for Annotation, Visualization and Integrated Discovery (DAVID) software. A differential expression of 26 proteins was identified; among these were arginase-1, pyruvate carboxylase, peroxiredoxin-1, regucalcin, and sorbitol dehydrogenase. Bioinformatics analysis indicated that many of these proteins are mitochondrial and participate in metabolic pathways, such as the citrate cycle, the fructose and mannose metabolism, and glycolysis or gluconeogenesis. In addition, these proteins are related to oxidation⁻reduction reactions and molecular function of vitamin binding and amino acid metabolism. In conclusion, the proteomic profile of the liver of diabetic mouse db/db exhibited mainly alterations in the metabolism of carbohydrates and nitrogen. These differences illustrate the heterogeneity of diabetes in its different stages and under different conditions and highlights the need to improve treatments for this disease.

Quantitative proteomic analysis of murine white adipose tissue for peritoneal cancer metastasis

Cancer metastasis risk increases in older individuals, but the mechanisms for this risk increase are unclear. Many peritoneal cancers, including ovarian cancer, preferentially metastasize to peritoneal fat depots. However, there is a dearth of studies exploring aged peritoneal adipose tissue in the context of cancer. Because adipose tissue produces signals which influence several diseases including cancer, proteomics of adipose tissue in aged and young mice may provide insight into metastatic mechanisms. We analyzed mesenteric, omental, and uterine adipose tissue groups from the peritoneal cavities of young and aged C57BL/6J mouse cohorts with a low-fraction SDS-PAGE gelLC-MS/MS method. We identified 2308 protein groups and quantified 2167 groups, among which several protein groups showed twofold or greater abundance differences between the aged and young cohorts. Cancer-related gene products previously identified as significant in another age-related study were found altered in this study. Several gene products known to suppress proliferation and cellular invasion were found downregulated in the aged cohort, including R-Ras, Arid1a, and heat shock protein β1. In addition, multiple protein groups were identified within single cohorts, including the proteins Cd11a, Stat3, and Ptk2b. These data suggest that adipose tissue is a strong candidate for analysis to identify possible contributors to cancer metastasis in older subjects. The results of this study, the first of its kind using uterine adipose tissue, contribute to the understanding of the role of adipose tissue in age-related alteration of oncogenic pathways, which may help elucidate the mechanisms of increased metastatic tumor burden in the aged. Graphical abstract We analyzed mesenteric, omental, and uterine adipose tissue groups from the peritoneal cavities of young and aged C57BL/6J mouse cohorts with a low-fraction SDS-PAGE gelLC-MS/MS method. These fat depots are preferential sites for many peritoneal cancers. The results of this study, the first of its kind using uterine adipose tissue, contribute to the understanding of the role of adipose tissue in age-related alteration of oncogenic pathways, which may help elucidate the mechanisms of increased metastatic tumor burden in the aged.