**4. Proteomics**

While genetic regulation in a biological system is unequivocally vital to health and disease, mRNA transcript levels generally only partially correlate with protein expression [16]. Typically, transcript abundance explains approximately one‐ to two‐thirds of the variance in protein levels, depending on the organism [16]. This is due to the fact that it is not only the transcription that determines protein abundance but also post‐transcriptional factors such as RNA processing and stability, translation, protein stability/turnover and protein modification. So while transcription data can provide a starting point as to whether or not a protein will be found and its likely level of abundance in a given sample, changes in expression levels may not correlate to changes in protein levels. Consequently, proteomics is an important area of research to enable the characterisation of the proteome. Traditionally, the expression of individual proteins has been quantified using antibodies and techniques such as western blotting but today many proteins and the whole proteome of a sample can be assessed at once by using various mass spectrometry approaches. Proteins are regulated by a wide variety of chemical alterations after they have been translated. These post‐translational modifications can include but is not limited to phosphorylation, ubiquitination, acetylation, glycosylation, nitrosylation, acetylation and methylation, and consequently, these are all sub‐branches of proteomics.

#### **4.1. Proteomic analysis in adipocyte cell culture models**

Insulin plays a major role in the regulation of metabolic homeostasis. In adipose tissue, insulin‐stimulated glucose uptake and the inhibition of lipolysis are two major functions of insulin. Quantitative phosphoproteomics using stable isotope labelling with amino acids in cell culture (SILAC) was used to interrogate the insulin signalling network in response to insulin stimulation in the 3T3‐L1 adipocytes cell culture model [17]. The phosphoproteomics identified 37,248 phosphorylation sites that spanned 5705 proteins. Of these, around 15% were regulated by insulin demonstrating the complexity of the insulin signalling network in adipose cells [17]. A time course analysis also revealed a large variation in when phosphorylation events occur following insulin treatment, demonstrating the dynamic nature of the pathways. Novel mechanisms of the AKT‐mTORC2 were also identified leading to the identification of SIN1 as an Akt substrate that contributes to the regulation of mTORC2 activity [17]. Proteomic analysis has also been useful in determining that large‐scale changes to proteins that occur in 3T3‐L1 cells during adipogenesis [18]. Wilson‐Fritch et al*.* used mass spectrometry and database correlation analysis to describe a 20–30‐fold increase in mitochondrial proteins during adipogenesis including proteins involved in fatty acid metabolism and those that are mitochondrial chaperones [18]. Further analysis revealed that the insulin‐sensitising drug rosiglitazone (belonging to the thiazolidinedione (TZD) class of drug) also changes expression of mitochondria‐related proteins which makes sense considering it is a known adipogenesis‐inducing agent.

#### **4.2. Proteomic changes in human obesity**

The characterisation of protein expression in organs during obesity can help scientist unveil the biological impact of obesity and lead to a greater understanding of the condition. An interesting area of adipocyte biology is how the subcutaneous adipose tissue (fat found under the skin and largely around the hips, thighs and buttocks) is thought to be the more metabolically active and metabolically healthy type of fat and the visceral adipose tissue (central obesity) which is associated with metabolic dysfunction and disease differs. Via 2D‐DIGE and mass spectrometry analysis, Perez‐Perez and team investigated the protein differences in omental and subcutaneous adipose tissue of healthy obese individuals. These results identified 43 differentially expressed proteins including those that have been linked to lipid and glucose metabolism, lipid transport, protein synthesis and folding inflammation and the cellular stress response [19]. One way of getting proteomic information without the invasiveness of using adipose biopsies is to use peripheral blood mononuclear cells (PBMCs) as a surrogate tissue. Abu‐Farha and colleagues utilised shotgun proteomics to examine the PBMC proteome in lean versus obese individuals [20]. About 1063 proteins were identified as common proteins between both groups (lean and obese participants), and of these, 47 were differentially expressed (by at least 1.5‐fold). Of these 47, 18 were increased and 29 decreased in the obese group compared to lean. As adipose tissue is an endocrine organ that secretes substances (adipokines) that impact metabolism in other tissues, proteomic analysis of these factors is of interest. Human primary subcutaneous adipose tissue cells were cultured and tandem mass spectrometry used to analyse the secretome of the cells [21]. As well as the detection of a number of well‐characterised adipokines‐like adiponectin (validating the technique), this method leads to the identification of multiple serine protease inhibitors (called serpins) [21]. Using this proteomics approach and exposing the adipose cells to different metabolic states and treatments, may be a way to further elucidate the factors that are released by adipocytes, the quantities by which they are released and under which conditions they are released. This could pave the way for a greater understanding as to the endocrine effects of the adipocyte.

#### **4.3. Animal models of obesity and alterations to the proteome**

not correlate to changes in protein levels. Consequently, proteomics is an important area of research to enable the characterisation of the proteome. Traditionally, the expression of individual proteins has been quantified using antibodies and techniques such as western blotting but today many proteins and the whole proteome of a sample can be assessed at once by using various mass spectrometry approaches. Proteins are regulated by a wide variety of chemical alterations after they have been translated. These post‐translational modifications can include but is not limited to phosphorylation, ubiquitination, acetylation, glycosylation, nitrosylation, acetylation and methylation, and consequently, these are all sub‐branches of proteomics.

Insulin plays a major role in the regulation of metabolic homeostasis. In adipose tissue, insulin‐stimulated glucose uptake and the inhibition of lipolysis are two major functions of insulin. Quantitative phosphoproteomics using stable isotope labelling with amino acids in cell culture (SILAC) was used to interrogate the insulin signalling network in response to insulin stimulation in the 3T3‐L1 adipocytes cell culture model [17]. The phosphoproteomics identified 37,248 phosphorylation sites that spanned 5705 proteins. Of these, around 15% were regulated by insulin demonstrating the complexity of the insulin signalling network in adipose cells [17]. A time course analysis also revealed a large variation in when phosphorylation events occur following insulin treatment, demonstrating the dynamic nature of the pathways. Novel mechanisms of the AKT‐mTORC2 were also identified leading to the identification of SIN1 as an Akt substrate that contributes to the regulation of mTORC2 activity [17]. Proteomic analysis has also been useful in determining that large‐scale changes to proteins that occur in 3T3‐L1 cells during adipogenesis [18]. Wilson‐Fritch et al*.* used mass spectrometry and database correlation analysis to describe a 20–30‐fold increase in mitochondrial proteins during adipogenesis including proteins involved in fatty acid metabolism and those that are mitochondrial chaperones [18]. Further analysis revealed that the insulin‐sensitising drug rosiglitazone (belonging to the thiazolidinedione (TZD) class of drug) also changes expression of mitochondria‐related proteins which makes sense considering it is a known

The characterisation of protein expression in organs during obesity can help scientist unveil the biological impact of obesity and lead to a greater understanding of the condition. An interesting area of adipocyte biology is how the subcutaneous adipose tissue (fat found under the skin and largely around the hips, thighs and buttocks) is thought to be the more metabolically active and metabolically healthy type of fat and the visceral adipose tissue (central obesity) which is associated with metabolic dysfunction and disease differs. Via 2D‐DIGE and mass spectrometry analysis, Perez‐Perez and team investigated the protein differences in omental and subcutaneous adipose tissue of healthy obese individuals. These results identified 43 differentially expressed proteins including those that have been linked to lipid and glucose metabolism, lipid transport, protein synthesis and folding inflammation and the cellular stress response [19]. One way of getting proteomic information without the invasiveness of using adipose biopsies is to use peripheral blood mononuclear cells (PBMCs) as

**4.1. Proteomic analysis in adipocyte cell culture models**

30 Adiposity - Omics and Molecular Understanding

adipogenesis‐inducing agent.

**4.2. Proteomic changes in human obesity**

One way to look at the way obesity impacts biology and metabolism is to look at and study the white adipose tissue (WAT) itself. A global label‐free phosphoproteomic screen of WAT in mice discordant for obesity due to high‐fat feeding detected and quantified a total of 7696 peptides. Differential phosphorylation levels between groups were found at 282 phosphosites from 191 different proteins [22]. This data set identified phosphorylation changes in enzymes involved in metabolic pathways such as glucose and lipid homeostasis pathways, linking these proteins to disturbed metabolism [22]. Importantly, the authors were able to further dissect out the likely impact of adiposity by using the data set to provide predictions on upstream kinases that are likely affected. These predictions revealed well‐known kinase families such as AMPK and AKT that have been heavily studied in metabolic dysregulation verifying their approach. It also identified others such as MRCKα and PAK 1 and 2 whose role is unknown in relation to obesity [22]. Thus, this sort of analysis has the potential to uncover novel pathways altered with obesity and how this alters adipocyte function.

We all know that some individuals seem to put on weight even though they consume a healthy, low‐fat diet, whereas others eat all of the energy‐dense junk food that they want and do not have any impact on their waistlines. As this would rule out calorie content as the driving force for this type of accumulation of adiposity, it is likely that there is an underlying susceptibility in these individuals. Xie and colleagues tried to replicate this in an animal study where they performed proteomic analysis on mice that were either obesity resistant or obesity prone [23]. Results indicated that ubiquinol‐cytochrome c reductase core protein 1 (Uqcrc1) and Enolase 3 were decreased and monoglyceride lipase (MGLL) and glucose‐6‐phosphate dehydrogenase (G6PDH) were increased in the visceral adipose tissue of obesity‐prone mice compared to obesity‐resistant mice [23]. These proteins involved in energy metabolism, glycolysis and fat synthesis may provide a clue as to why visceral adipose tissue is more or less likely to store energy and expand.

Though adipose tissue is obviously important to study, other metabolic organs are also too important to study. Baiges et al. [24] investigated the effects of a high‐fat diet (HFD) on the rat liver proteome. Analysis identified 1,131 liver proteins and demonstrated that a high‐fat diet changed the expression of 90 of these proteins. As one would have hypothesised, many of these proteins are involved in glucose and lipid metabolism [24]. Proteomics can also be further enhanced by analysing sub‐cellular compartments such as mitochondria. In a study comparing lean versus obese mice, Nesteruk et al. [25] purified isolated mitochondria from both liver and skeletal muscle and analysed mitochondrial‐associated proteins via mass spectrometry. Analysis identified 1,675 liver and 704 muscle mitochondria‐associated proteins and of these, 221 liver and 44 muscle proteins were differentially expressed between the lean and obese groups [25]. Analysis of"sub‐proteomes" such as the ones at the mitochondrial proteome may be used more in the future to identify cellular compartment‐ specific changes associated with obesity. This type of analysis is also beneficial in the sense that it can increase the sensitivity of the process and allow the detection of lowly expressed proteins.

Looking into the future, the combination and integration of proteomics analysis with other"omic" platform analysis such as genomics, transcriptomics and metabolomics may provide a useful systems biology approach to further understand the regulation of whole‐body fat mass.
