Adipocyte-specific ablation of the Ca2+ pump SERCA2 impairs whole-body metabolic function and reveals the diverse metabolic flexibility of white and brown adipose tissue.

OBJECTIVE: Sarco/endoplasmic reticulum Ca2+-ATPase (SERCA) transports Ca2+ from the cytosol into the endoplasmic retitculum (ER) and is essential for appropriate regulation of intracellular Ca2+ homeostasis. The objective of this study was to test the hypothesis that SERCA pumps are involved in the regulation of white adipocyte hormone secretion and other aspects of adipose tissue function and that this control is disturbed in obesity-induced type-2 diabetes. METHODS: SERCA expression was measured in isolated human and mouse adipocytes as well as in whole mouse adipose tissue by Western blot and RT-qPCR. To test the significance of SERCA2 in adipocyte functionality and whole-body metabolism, we generated adipocyte-specific SERCA2 knockout mice. The mice were metabolically phenotyped by glucose tolerance and tracer studies, histological analyses, measurements of glucose-stimulated insulin release in isolated islets, and gene/protein expression analyses. We also tested the effect of pharmacological SERCA inhibition and genetic SERCA2 ablation in cultured adipocytes. Intracellular and mitochondrial Ca2+ levels were recorded with dual-wavelength ratio imaging and mitochondrial function was assessed by Seahorse technology. RESULTS: We demonstrate that SERCA2 is downregulated in white adipocytes from patients with obesity and type-2 diabetes as well as in adipocytes from diet-induced obese mice. SERCA2-ablated adipocytes display disturbed Ca2+ homeostasis associated with upregulated ER stress markers and impaired hormone release. These adipocyte alterations are linked to mild lipodystrophy, reduced adiponectin levels, and impaired glucose tolerance. Interestingly, adipocyte-specific SERCA2 ablation leads to increased glucose uptake in white adipose tissue while the glucose uptake is reduced in brown adipose tissue. This dichotomous effect on glucose uptake is due to differently regulated mitochondrial function. In white adipocytes, SERCA2 deficiency triggers an adaptive increase in fibroblast growth factor 21 (FGF21), increased mitochondrial uncoupling protein 1 (UCP1) levels, and increased oxygen consumption rate (OCR). In contrast, brown SERCA2 null adipocytes display reduced OCR despite increased mitochondrial content and UCP1 levels compared to wild type controls. CONCLUSIONS: Our data suggest causal links between reduced white adipocyte SERCA2 levels, deranged adipocyte Ca2+ homeostasis, adipose tissue dysfunction and type-2 diabetes.

A systems biology analysis of lipolysis and fatty acid release from adipocytes in vitro and from adipose tissue in vivo.

Lipolysis and the release of fatty acids to supply energy fuel to other organs, such as between meals, during exercise, and starvation, are fundamental functions of the adipose tissue. The intracellular lipolytic pathway in adipocytes is activated by adrenaline and noradrenaline, and inhibited by insulin. Circulating fatty acids are elevated in type 2 diabetic individuals. The mechanisms behind this elevation are not fully known, and to increase the knowledge a link between the systemic circulation and intracellular lipolysis is key. However, data on lipolysis and knowledge from in vitro systems have not been linked to corresponding in vivo data and knowledge in vivo. Here, we use mathematical modelling to provide such a link. We examine mechanisms of insulin action by combining in vivo and in vitro data into an integrated mathematical model that can explain all data. Furthermore, the model can describe independent data not used for training the model. We show the usefulness of the model by simulating new and more challenging experimental setups in silico, e.g. the extracellular concentration of fatty acids during an insulin clamp, and the difference in such simulations between individuals with and without type 2 diabetes. Our work provides a new platform for model-based analysis of adipose tissue lipolysis, under both non-diabetic and type 2 diabetic conditions.

Adiponectin is secreted via caveolin 1-dependent mechanisms in white adipocytes.

Here we have investigated the role of the protein caveolin 1 (Cav1) and caveolae in the secretion of the white adipocyte hormone adiponectin. Using mouse primary subcutaneous adipocytes genetically depleted of Cav1, we show that the adiponectin secretion, stimulated either adrenergically or by insulin, is abrogated while basal (unstimulated) release of adiponectin is elevated. Adiponectin secretion is similarly affected in wildtype mouse and human adipocytes where the caveolae structure was chemically disrupted. The altered ex vivo secretion in adipocytes isolated from Cav1 null mice is accompanied by lowered serum levels of the high-molecular weight (HMW) form of adiponectin, whereas the total concentration of adiponectin is unaltered. Interestingly, levels of HMW adiponectin are maintained in adipose tissue from Cav1-depleted mice, signifying that a secretory defect is present. The gene expression of key regulatory proteins known to be involved in cAMP/adrenergically triggered adiponectin exocytosis (the beta-3-adrenergic receptor and exchange protein directly activated by cAMP) remains intact in Cav1 null adipocytes. Microscopy and fractionation studies indicate that adiponectin vesicles do not co-localise with Cav1 but that some vesicles are associated with a specific fraction of caveolae. Our studies propose that Cav1 has an important role in secretion of HMW adiponectin, even though adiponectin-containing vesicles are not obviously associated with this protein. We suggest that Cav1, and/or the caveolae domain, is essential for the organisation of signalling pathways involved in the regulation of HMW adiponectin exocytosis, a function that is disrupted in Cav1/caveolae-depleted adipocytes.

Insulin and ß-adrenergic receptors mediate lipolytic and anti-lipolytic signalling that is not altered by type 2 diabetes in human adipocytes.

Control of fatty acid storage and release in adipose tissue is fundamental in energy homeostasis and the development of obesity and type 2 diabetes. We here take the whole signalling network into account to identify how insulin and ß-adrenergic stimulation in concert controls lipolysis in mature subcutaneous adipocytes obtained from non-diabetic and, in parallel, type 2 diabetic women. We report that, and show how, the anti-lipolytic effect of insulin can be fully explained by protein kinase B (PKB/Akt)-dependent activation of the phosphodiesterase PDE3B. Through the same PKB-dependent pathway ß-adrenergic receptor signalling, via cAMP and PI3Kα, is anti-lipolytic and inhibits its own stimulation of lipolysis by 50%. Through this pathway both insulin and ß-adrenergic signalling control phosphorylation of FOXO1. The dose-response of lipolysis is bell-shaped, such that insulin is anti-lipolytic at low concentrations, but at higher concentrations of insulin lipolysis was increasingly restored due to inhibition of PDE3B. The control of lipolysis was not altered in adipocytes from diabetic individuals. However, the release of fatty acids was increased by 50% in diabetes due to reduced reesterification of lipolytically liberated fatty acids. In conclusion, our results reveal mechanisms of control by insulin and ß-adrenergic stimulation - in human adipocytes - that define a network of checks and balances ensuring robust control to secure uninterrupted supply of fatty acids without reaching concentrations that put cellular integrity at risk. Moreover, our results define how selective insulin resistance leave lipolytic control by insulin unaltered in diabetes, while the fatty acid release is substantially increased.

Inhibition of FOXO1 transcription factor in primary human adipocytes mimics the insulin-resistant state of type 2 diabetes.

Type 2 diabetes is characterized by insulin resistance in the expanding adipose tissue of obesity. The insulin resistance manifests in human adipocytes as system-wide impairment of insulin signalling. An exception is the regulation of transcription factor FOXO1 (forkhead box protein O1), which is phosphorylated downstream of mTORC2 (mammalian/mechanistic target of rapamycin in complex with raptor) and is therefore not exhibiting impaired response to insulin. However, the abundance, and activity, of FOXO1 is reduced by half in adipocytes from patients with diabetes. To elucidate the effect of reduced FOXO1 activity, we here transduced human adipocytes with a dominant-negative construct of FOXO1 (DN-FOXO1). Inhibition of FOXO1 reduced the abundance of insulin receptor, glucose transporter-4, ribosomal protein S6, mTOR and raptor. Functionally, inhibition of FOXO1 induced an insulin-resistant state network-wide, a state that qualitatively and quantitatively mimicked adipocytes from patients with type 2 diabetes. In contrast, and in accordance with these effects of DN-FOXO1, overexpression of wild-type FOXO1 appeared to augment insulin signalling. We combined experimental data with mathematical modelling to show that the impaired insulin signalling in FOXO1-inhibited cells to a large extent can be explained by reduced mTORC1 activity - a mechanism that defines much of the diabetic state in human adipocytes. Our findings demonstrate that FOXO1 is critical for maintaining normal insulin signalling of human adipocytes.

Cross-talks via mTORC2 can explain enhanced activation in response to insulin in diabetic patients.

The molecular mechanisms of insulin resistance in Type 2 diabetes have been extensively studied in primary human adipocytes, and mathematical modelling has clarified the central role of attenuation of mammalian target of rapamycin (mTOR) complex 1 (mTORC1) activity in the diabetic state. Attenuation of mTORC1 in diabetes quells insulin-signalling network-wide, except for the mTOR in complex 2 (mTORC2)-catalysed phosphorylation of protein kinase B (PKB) at Ser473 (PKB-S473P), which is increased. This unique increase could potentially be explained by feedback and interbranch cross-talk signals. To examine if such mechanisms operate in adipocytes, we herein analysed data from an unbiased phosphoproteomic screen in 3T3-L1 adipocytes. Using a mathematical modelling approach, we showed that a negative signal from mTORC1-p70 S6 kinase (S6K) to rictor-mTORC2 in combination with a positive signal from PKB to SIN1-mTORC2 are compatible with the experimental data. This combined cross-branch signalling predicted an increased PKB-S473P in response to attenuation of mTORC1 - a distinguishing feature of the insulin resistant state in human adipocytes. This aspect of insulin signalling was then verified for our comprehensive model of insulin signalling in human adipocytes. Introduction of the cross-branch signals was compatible with all data for insulin signalling in human adipocytes, and the resulting model can explain all data network-wide, including the increased PKB-S473P in the diabetic state. Our approach was to first identify potential mechanisms in data from a phosphoproteomic screen in a cell line, and then verify such mechanisms in primary human cells, which demonstrates how an unbiased approach can support a direct knowledge-based study.

Scaffolding protein IQGAP1: an insulin-dependent link between caveolae and the cytoskeleton in primary human adipocytes?

The ubiquitously expressed IQ motif-containing GTPase activating protein-1 (IQGAP1) is a scaffolding protein implicated in an array of cellular functions, in particular by binding to cytoskeletal elements and signaling proteins. A role of IQGAP1 in adipocytes has not been reported. We therefore investigated the cellular IQGAP1 interactome in primary human adipocytes. Immunoprecipitation and quantitative mass spectrometry identified caveolae and caveolae-associated proteins as the major IQGAP1 interactors alongside cytoskeletal proteins. We confirmed co-localization of IQGAP1 with the defining caveolar marker protein caveolin-1 by confocal microscopy and proximity ligation assay. Most interestingly, insulin enhanced the number of IQGAP1 interactions with caveolin-1 by five-fold. Moreover, we found a significantly reduced abundance of IQGAP1 in adipocytes from patients with type 2 diabetes compared with cells from nondiabetic control subjects. Both the abundance of IQGAP1 protein and mRNA were reduced, indicating a transcriptional defect in diabetes. Our findings suggest a novel role of IQGAP1 in insulin-regulated interaction between caveolae and cytoskeletal elements of the adipocyte, and that this is quelled in the diabetic state.

Systems-wide Experimental and Modeling Analysis of Insulin Signaling through Forkhead Box Protein O1 (FOXO1) in Human Adipocytes, Normally and in Type 2 Diabetes.

Insulin resistance is a major aspect of type 2 diabetes (T2D), which results from impaired insulin signaling in target cells. Signaling to regulate forkhead box protein O1 (FOXO1) may be the most important mechanism for insulin to control transcription. Despite this, little is known about how insulin regulates FOXO1 and how FOXO1 may contribute to insulin resistance in adipocytes, which are the most critical cell type in the development of insulin resistance. We report a detailed mechanistic analysis of insulin control of FOXO1 in human adipocytes obtained from non-diabetic subjects and from patients with T2D. We show that FOXO1 is mainly phosphorylated through mTORC2-mediated phosphorylation of protein kinase B at Ser(473) and that this mechanism is unperturbed in T2D. We also demonstrate a cross-talk from the MAPK branch of insulin signaling to stimulate phosphorylation of FOXO1. The cellular abundance and consequently activity of FOXO1 are halved in T2D. Interestingly, inhibition of mTORC1 with rapamycin reduces the abundance of FOXO1 to the levels in T2D. This suggests that the reduction of the concentration of FOXO1 is a consequence of attenuation of mTORC1, which defines much of the diabetic state in human adipocytes. We integrate insulin control of FOXO1 in a network-wide mathematical model of insulin signaling dynamics based on compatible data from human adipocytes. The diabetic state is network-wide explained by attenuation of an mTORC1-to-insulin receptor substrate-1 (IRS1) feedback and reduced abundances of insulin receptor, GLUT4, AS160, ribosomal protein S6, and FOXO1. The model demonstrates that attenuation of the mTORC1-to-IRS1 feedback is a major mechanism of insulin resistance in the diabetic state.

Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes.

We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets, corresponding multi-level mathematical models are needed, i.e. models that simultaneously capture multiple layers of the biological, physiological and disease-level organization (also referred to as quantitative systems pharmacology-QSP-models). However, today's multi-level models are not yet embedded in end-usage applications, neither in drug research and development nor in the clinic. Given the expectations and claims made historically, this seemingly slow adoption may seem surprising. Therefore, we herein consider a specific example-type 2 diabetes-and critically review the current status and identify key remaining steps for these models to become mainstream in the future. This overview reveals how, today, we may use models to ask scientific questions concerning, e.g., the cellular origin of insulin resistance, and how this translates to the whole-body level and short-term meal responses. However, before these multi-level models can become truly useful, they need to be linked with the capabilities of other important existing models, in order to make them 'personalized' (e.g. specific to certain patient phenotypes) and capable of describing long-term disease progression. To be useful in drug development, it is also critical that the developed models and their underlying data and assumptions are easily accessible. For clinical end-usage, in addition, model links to decision-support systems combined with the engagement of other disciplines are needed to create user-friendly and cost-efficient software packages.

Model-Based Quantification of the Systemic Interplay between Glucose and Fatty Acids in the Postprandial State.

In metabolic diseases such as Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, the systemic regulation of postprandial metabolite concentrations is disturbed. To understand this dysregulation, a quantitative and temporal understanding of systemic postprandial metabolite handling is needed. Of particular interest is the intertwined regulation of glucose and non-esterified fatty acids (NEFA), due to the association between disturbed NEFA metabolism and insulin resistance. However, postprandial glucose metabolism is characterized by a dynamic interplay of simultaneously responding regulatory mechanisms, which have proven difficult to measure directly. Therefore, we propose a mathematical modelling approach to untangle the systemic interplay between glucose and NEFA in the postprandial period. The developed model integrates data of both the perturbation of glucose metabolism by NEFA as measured under clamp conditions, and postprandial time-series of glucose, insulin, and NEFA. The model can describe independent data not used for fitting, and perturbations of NEFA metabolism result in an increased insulin, but not glucose, response, demonstrating that glucose homeostasis is maintained. Finally, the model is used to show that NEFA may mediate up to 30-45% of the postprandial increase in insulin-dependent glucose uptake at two hours after a glucose meal. In conclusion, the presented model can quantify the systemic interactions of glucose and NEFA in the postprandial state, and may therefore provide a new method to evaluate the disturbance of this interplay in metabolic disease.

Dominant negative inhibition data should be analyzed using mathematical modeling--re-interpreting data from insulin signaling.

As our ability to measure the complexity of intracellular networks has evolved, it has become increasingly clear that we need new methods for data analysis: methods involving mathematical modeling. Nevertheless, it is still uncontroversial to publish and interpret experimental results without a model-based proof that the reasoning is correct. In the present study, we argue that this attitude probably needs to change in the future. We illustrate this need for modeling by considering the common experimental technique of using dominant-negative constructs. More specifically, we consider published time-series and dose-response data which previously have been used to argue that the protein S6 kinase does not phosphorylate insulin receptor substrate-1 at a specific serine residue. Using a presented general approach to interpret such data, we now demonstrate that the given dominant-negative data are not conclusive (i.e. that in the absence of other proofs, S6 kinase still may be the kinase). Using simulations with uncertainty analysis and analytical solutions, we show that an alternative explanation is centered around depletion of substrate, which can be tested experimentally. This analysis thus illustrates both the necessity and the benefits of using mathematical modeling to fully understand the implications of biological data, even for a small system and relatively simple data.

A single mechanism can explain network-wide insulin resistance in adipocytes from obese patients with type 2 diabetes.

The response to insulin is impaired in type 2 diabetes. Much information is available about insulin signaling, but understanding of the cellular mechanisms causing impaired signaling and insulin resistance is hampered by fragmented data, mainly obtained from different cell lines and animals. We have collected quantitative and systems-wide dynamic data on insulin signaling in primary adipocytes and compared cells isolated from healthy and diabetic individuals. Mathematical modeling and experimental verification identified mechanisms of insulin control of the MAPKs ERK1/2. We found that in human adipocytes, insulin stimulates phosphorylation of the ribosomal protein S6 and hence protein synthesis about equally via ERK1/2 and mTORC1. Using mathematical modeling, we examined the signaling network as a whole and show that a single mechanism can explain the insulin resistance of type 2 diabetes throughout the network, involving signaling both through IRS1, PKB, and mTOR and via ERK1/2 to the nuclear transcription factor Elk1. The most important part of the insulin resistance mechanism is an attenuated feedback from the protein kinase mTORC1 to IRS1, which spreads signal attenuation to all parts of the insulin signaling network. Experimental inhibition of mTORC1 using rapamycin in adipocytes from non-diabetic individuals induced and thus confirmed the predicted network-wide insulin resistance.

Combining test statistics and models in bootstrapped model rejection: it is a balancing act.

BACKGROUND: Model rejections lie at the heart of systems biology, since they provide conclusive statements: that the corresponding mechanistic assumptions do not serve as valid explanations for the experimental data. Rejections are usually done using e.g. the chi-square test (χ2) or the Durbin-Watson test (DW). Analytical formulas for the corresponding distributions rely on assumptions that typically are not fulfilled. This problem is partly alleviated by the usage of bootstrapping, a computationally heavy approach to calculate an empirical distribution. Bootstrapping also allows for a natural extension to estimation of joint distributions, but this feature has so far been little exploited. RESULTS: We herein show that simplistic combinations of bootstrapped tests, like the max or min of the individual p-values, give inconsistent, i.e. overly conservative or liberal, results. A new two-dimensional (2D) approach based on parametric bootstrapping, on the other hand, is found both consistent and with a higher power than the individual tests, when tested on static and dynamic examples where the truth is known. In the same examples, the most superior test is a 2D χ2vsχ2, where the second χ2-value comes from an additional help model, and its ability to describe bootstraps from the tested model. This superiority is lost if the help model is too simple, or too flexible. If a useful help model is found, the most powerful approach is the bootstrapped log-likelihood ratio (LHR). We show that this is because the LHR is one-dimensional, because the second dimension comes at a cost, and because LHR has retained most of the crucial information in the 2D distribution. These approaches statistically resolve a previously published rejection example for the first time. CONCLUSIONS: We have shown how to, and how not to, combine tests in a bootstrap setting, when the combination is advantageous, and when it is advantageous to include a second model. These results also provide a deeper insight into the original motivation for formulating the LHR, for the more general setting of nonlinear and non-nested models. These insights are valuable in cases when accuracy and power, rather than computational speed, are prioritized.

The concentration of ß-carotene in human adipocytes, but not the whole-body adipocyte stores, is reduced in obesity.

We have examined the concentration of ß-carotene in the fat of isolated abdominal subcutaneous adipocytes obtained from lean (BMI<23 kg/m²), non-obese with higher BMI (23≤BMI<28 kg/m²), obese (BMI≥28 kg/m²), and from a group of obese subjects with type 2 diabetes. The concentration of ß-carotene was 50% lower in the adipocytes from the obese and obese/diabetic groups compared with the lean and non-obese groups. Interestingly, the total amount of ß-carotene in the adipocyte stores of each subject was constant among all groups. Triacylglycerol constituted 92±1% (by weight) of the adipocyte lipids in the lean group and this was increased to 99±2% in the obese group with diabetes (p<0.05). The concentration of cholesteryl esters was in all cases <0.1 g per 100 g of total lipids, demonstrating that mature human adipocytes have negligible stores of cholesteryl ester. Our findings demonstrate that adipocyte concentrations of ß-carotene are reduced in obese subjects. The lower concentrations in adipocytes from subjects with type 2 diabetes apparently reflect subjects obesity. Our finding that whole-body stores of ß-carotene in adipocytes are constant raises new questions regarding what function it serves, as well as the mechanisms for maintaining constant levels in the face of varied adipose tissue mass among individuals over a period of time.

Global differences in specific histone H3 methylation are associated with overweight and type 2 diabetes.

BACKGROUND: Epidemiological evidence indicates yet unknown epigenetic mechanisms underlying a propensity for overweight and type 2 diabetes. We analyzed the extent of methylation at lysine 4 and lysine 9 of histone H3 in primary human adipocytes from 43 subjects using modification-specific antibodies. RESULTS: The level of lysine 9 dimethylation was stable, while adipocytes from type 2 diabetic and non-diabetic overweight subjects exhibited about 40% lower levels of lysine 4 dimethylation compared with cells from normal-weight subjects. In contrast, trimethylation at lysine 4 was 40% higher in adipocytes from overweight diabetic subjects compared with normal-weight and overweight non-diabetic subjects. There was no association between level of modification and age of subjects. CONCLUSIONS: The findings define genome-wide molecular modifications of histones in adipocytes that are directly associated with overweight and diabetes, and thus suggest a molecular basis for existing epidemiological evidence of epigenetic inheritance.

Phosphorylation of IRS1 at serine 307 in response to insulin in human adipocytes is not likely to be catalyzed by p70 ribosomal S6 kinase.

The insulin receptor substrate-1 (IRS1) is phosphorylated on serine 307 (human sequence, corresponding to murine serine 302) in response to insulin as part of a feedback loop that controls IRS1 phosphorylation on tyrosine residues by the insulin receptor. This in turn directly affects downstream signaling and is in human adipocytes implicated in the pathogenesis of insulin resistance and type 2 diabetes. The phosphorylation is inhibited by rapamycin, a specific inhibitor of mammalian target of rapamycin (mTOR) in complex with raptor (mTORC1). The mTORC1-downstream p70 ribosomal protein S6 kinase (S6K1), which is activated by insulin, can phosphorylate IRS1 at serine 307 in vitro and is considered the physiological protein kinase. Because the IRS1 serine 307-kinase catalyzes a critical step in the control of insulin signaling and constitutes a potential target for treatment of insulin resistance, it is important to know whether S6K1 is the physiological serine 307-kinase or not. We report that, by several criteria, S6K1 does not phosphorylate IRS1 at serine 307 in response to insulin in intact human primary adipocytes: (i) The time-courses for phosphorylation of S6K1 and its phosphorylation of S6 are not compatible with the phosphorylation of IRS1 at serine 307; (ii) A dominant-negative construct of S6K1 inhibits the phosphorylation of S6, without effect on the phosphorylation of IRS1 at serine 307; (iii) The specific inhibitor of S6K1 PF-4708671 inhibits the phosphorylation of S6, without effect on phosphorylation of IRS1 at serine 307. mTOR-immunoprecipitates from insulin-stimulated adipocytes contains an unidentified protein kinase specific for phosphorylation of IRS1 at serine 307, but it is not mTOR or S6K1.

Insulin signaling in type 2 diabetes: experimental and modeling analyses reveal mechanisms of insulin resistance in human adipocytes.

Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis.

Caveolins and caveolae, roles in insulin signalling and diabetes.

Much data in the scientific literature demonstrate a fundamental involvement of caveolae in insulin action, although particular aspects remain matters of debate. The insulin receptor and part of the downstream signalling mediators are localized in or recruited to caveolae. Moreover, as part of the signalling, insulin receptors are rapidly endocytosed by caveolae in response to the hormone. The insulin regulated glucose transporter GLUT4 appears to localize to caveolae after insulin-stimulated translocation to the plasma membrane, while the endocytosis of GLUT4 may involve a clathrin-mediated process. Insulin resistance due to dysfunction of insulin signalling in target tissues is a primary cornerstone of Type 2 diabetes. Lack of caveolae makes animals and human beings insulin resistant, but there is presently no evidence that caveolae play a role in the pathogenesis of insulin resistance in obesity and Type 2 diabetes.

Insulin signaling - mathematical modeling comes of age.

Signaling pathways that only a few years ago appeared simple and understandable, albeit far from complete, have evolved into very complex multi-layered networks of cellular control mechanisms, which in turn are integrated in a similarly complex whole-body level of control mechanisms. This complexity sets limits for classical biochemical reasoning, such that a correct and complete analysis of experimental data while taking the full complexity into account is not possible. In this Opinion we propose that mathematical modeling can be used as a tool in insulin signaling research, and we demonstrate how recent developments in modeling - and the integration of modeling in the experimental process - provide new possibilities to approach and decipher complex biological systems more efficiently.

Mechanistic explanations for counter-intuitive phosphorylation dynamics of the insulin receptor and insulin receptor substrate-1 in response to insulin in murine adipocytes.

Insulin signaling through insulin receptor (IR) and insulin receptor substrate-1 (IRS1) is important for insulin control of target cells. We have previously demonstrated a rapid and simultaneous overshoot behavior in the phosphorylation dynamics of IR and IRS1 in human adipocytes. Herein, we demonstrate that in murine adipocytes a similar overshoot behavior is not simultaneous for IR and IRS1. The peak of IRS1 phosphorylation, which is a direct consequence of the phosphorylation and the activation of IR, occurs earlier than the peak of IR phosphorylation. We used a conclusive modeling framework to unravel the mechanisms behind this counter-intuitive order of phosphorylation. Through a number of rejections, we demonstrate that two fundamentally different mechanisms may create the reversed order of peaks: (i) two pools of phosphorylated IR, where a large pool of internalized IR peaks late, but phosphorylation of IRS1 is governed by a small plasma membrane-localized pool of IR with an early peak, or (ii) inhibition of the IR-catalyzed phosphorylation of IRS1 by negative feedback. Although (i) may explain the reversed order, this two-pool hypothesis alone requires extensive internalization of IR, which is not supported by experimental data. However, with the additional assumption of limiting concentrations of IRS1, (i) can explain all data. Also, (ii) can explain all available data. Our findings illustrate how modeling can potentiate reasoning, to help draw nontrivial conclusions regarding competing mechanisms in signaling networks. Our work also reveals new differences between human and murine insulin signaling.