Adipocytes play a central role in the control of energy balance and lipid homeostasis. As the primary storage depot for triglycerides (TG), adipose tissue is the most efficient source of energy reserve in humans as TG is anhydrous and therefore is stored at a maximum caloric density of ~9 kcal/g.(1
) Obesity, resulting from both hyperplasia and hypertrophy of adipocytes, is tightly linked to type 2 diabetes and cardiovascular diseases; as such, it is a major health risk in the world.(2
) Aside from being a fat-storage depot, adipocytes are also endocrine cells that actively regulate signaling pathways responsible for energy balance and lipid homeostasis through the secretion of hormones, cytokines, growth factors and other proteins, collectively termed adipokines.(3
) Among the well-studied adipokines are adiponectin, leptin, resistin, plasminogen activated inhibitor 1 (PAI-1), and proinflammatory cytokines IL-6 and TNF-α. Dysregulation in the circulating levels and actions of adipokines are causally linked to the pathogenesis of insulin resistance, diabetes and obesity.
The differentiation of preadipocytes into adipocytes is a complex process that is tightly regulated and orchestrated by a network of transcription factors acting in a precisely controlled temporal fashion to coordinate the expression of the machinery required to specify a fully functional, mature adipocyte.(4
) The transcription factor, peroxisome proliferator-activated receptor-gamma (PPAR-gamma), plays a central role in driving the adipogenic program; ectopic expression of PPAR-gamma in nonadipogenic mouse fibroblasts is sufficient to recapitulate much of the adipocyte phenotype.(5
) The important role of PPAR-gamma in adipogenesis is supported by many in vitro
and in vivo
Major advances in understanding the molecular underpinning of adipogenesis were made possible by the establishment of a fibroblast cell line (3T3-L1) highly capable of differentiating into mature adipocytes filled with lipid droplets.(8
) This in vitro
system has allowed investigators to employ molecular biology techniques to identify specific genes induced during adipocyte differentiation in culture, allowing the establishment of temporal gene expression patterns that specify sequential events in this process. Although microarray-based approaches have been extensively and successfully used to analyze changes in gene expression during adipogenesis, only a limited number of studies have been carried out to evaluate alterations in protein content, due primarily to the greater technical challenge.(9
Recently, several mass spectrometry-based proteomics studies have been reported in primary mouse adipose tissue or in vitro
differentiated 3T3-L1 mouse adipocytes.10−13
These studies demonstrate that, during differentiation, the entire secretory proteome (termed the secretome) of 3T3-L1 adipocytes changes dramatically with the most prominent changes involving the extracellular matrix components, cytokines, antioxidants, and complement factors. One mass spectrometry study has also been carried out on primary rat adipocytes.(14
) To date, two groups have characterized the secretome of differentiated human adipocytes.15,16
A major limitation of these studies is the use of 2-dimensional gels to separate proteins prior to identification by mass spectrometry, thus precluding a greater depth of analysis. A second limitation relates to the scope; by restricting the analysis of the secretome to preadipocytes versus mature adipocytes, the investigators were not able to capture the dynamic temporal changes in protein expression throughout the differentiation process. To overcome these limitations, we have previously described a 5-plex SILAC strategy to quantify temporal changes of the secretome during mouse 3T3-L1 adipocyte differentiation in culture;(12
) however, a similar study has not been carried out in humans.
Isobaric tags for relative and absolute quantification (iTRAQ) can be used for multiplexed quantitation of proteins by tandem mass spectrometry.17,18
In this study, we employed an iTRAQ-based strategy to specifically characterize the secretory proteome and to profile the temporal changes during human adipogenesis. In addition to identifying many proteins previously known to be secreted by adipocytes such as adiponectin and adipsin, we also uncovered proteins not known to be present in the secretome during adipogenesis. Further, we employed a high-throughput antibody array method to validate some of our proteomic data and to profile the secretome for additional proteins not originally detected by mass spectrometry. Quantitation of the secretome during adipogenesis revealed dynamic expression patterns of these adipokines that were underappreciated in proteomics studies in humans. Our study represents the largest proteomic analysis of the primary human adipocyte secretome carried out to date.