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

The causal effect of mTORC1-dependent circulating protein levels on nonalcoholic fatty liver disease: A Mendelian randomization study

BACKGROUND

The mechanistic target of rapamycin (mTOR) signal pathway plays a crucial role in the development of nonalcoholic fatty liver disease (NAFLD). However, the causal effect of mTOR downstream proteins on NAFLD remains unknown.

AIMS

We conducted a two-sample Mendelian randomization (MR) study to investigate whether the mTOR-dependent circulating proteins, including Eukaryotic Initiation Factor 4E Binding Proteins (eIF4EBPs), Ribosomal Protein S6K kinase 1 (RP-S6K), Eukaryotic Initiation Factor 4E (eIF4E), Eukaryotic Initiation Factor 4A (eIF4A) and Eukaryotic Initiation Factor 4 G (eIF4G), have causal effects on the risk of NAFLD.

METHODS

The causal estimate was evaluated with the inverse-variance weighted (IVW) method in discovery stage and validation stage. The single-nucleotide polymorphisms (SNPs) were selected to genetically predict exposures from Genome-Wide Association Studies (GWAS). Exposures with statistically significant effects in the discovery dataset would be further validated in the validation dataset.

RESULTS

MR study revealed that eIF4E had a causal effect on NAFLD in both discovery stage (OR = 1.339, P = 0.037) and validation stage (OR = 1.0007, P = 0.022). Sensitivity analyses confirmed robustness of the results.

CONCLUSION

The genetically predicted higher level of mTOR-dependent eIF4E in plasma might have a causal effect on the occurrence of NAFLD.

A comprehensive mechanistic model of adipocyte signaling with layers of confidence

Adipocyte signaling, normally and in type 2 diabetes, is far from fully understood. We have earlier developed detailed dynamic mathematical models for several well-studied, partially overlapping, signaling pathways in adipocytes. Still, these models only cover a fraction of the total cellular response. For a broader coverage of the response, large-scale phosphoproteomic data and systems level knowledge on protein interactions are key. However, methods to combine detailed dynamic models with large-scale data, using information about the confidence of included interactions, are lacking. We have developed a method to first establish a core model by connecting existing models of adipocyte cellular signaling for: (1) lipolysis and fatty acid release, (2) glucose uptake, and (3) the release of adiponectin. Next, we use publicly available phosphoproteome data for the insulin response in adipocytes together with prior knowledge on protein interactions, to identify phosphosites downstream of the core model. In a parallel pairwise approach with low computation time, we test whether identified phosphosites can be added to the model. We iteratively collect accepted additions into layers and continue the search for phosphosites downstream of these added layers. For the first 30 layers with the highest confidence (311 added phosphosites), the model predicts independent data well (70-90% correct), and the predictive capability gradually decreases when we add layers of decreasing confidence. In total, 57 layers (3059 phosphosites) can be added to the model with predictive ability kept. Finally, our large-scale, layered model enables dynamic simulations of systems-wide alterations in adipocytes in type 2 diabetes.

Queueing theory model of mTOR complexes' impact on Akt-mediated adipocytes response to insulin

A queueing theory based model of mTOR complexes impact on Akt-mediated cell response to insulin is presented in this paper. The model includes several aspects including the effect of insulin on the transport of glucose from the blood into the adipocytes with the participation of GLUT4, and the role of the GAPDH enzyme as a regulator of mTORC1 activity. A genetic algorithm was used to optimize the model parameters. It can be observed that mTORC1 activity is related to the amount of GLUT4 involved in glucose transport. The results show the relationship between the amount of GAPDH in the cell and mTORC1 activity. Moreover, obtained results suggest that mTORC1 inhibitors may be an effective agent in the fight against type 2 diabetes. However, these results are based on theoretical knowledge and appropriate experimental tests should be performed before making firm conclusions.

Digital twin predicting diet response before and after long-term fasting

Today, there is great interest in diets proposing new combinations of macronutrient compositions and fasting schedules. Unfortunately, there is little consensus regarding the impact of these different diets, since available studies measure different sets of variables in different populations, thus only providing partial, non-connected insights. We lack an approach for integrating all such partial insights into a useful and interconnected big picture. Herein, we present such an integrating tool. The tool uses a novel mathematical model that describes mechanisms regulating diet response and fasting metabolic fluxes, both for organ-organ crosstalk, and inside the liver. The tool can mechanistically explain and integrate data from several clinical studies, and correctly predict new independent data, including data from a new study. Using this model, we can predict non-measured variables, e.g. hepatic glycogen and gluconeogenesis, in response to fasting and different diets. Furthermore, we exemplify how such metabolic responses can be successfully adapted to a specific individual’s sex, weight, height, as well as to the individual’s historical data on metabolite dynamics. This tool enables an offline digital twin technology.

Fasting and diet are central components of prevention against cardiovascular disease. Unfortunately, there is little consensus regarding which diet schemes are optimal. This is partially because different clinical studies contribute with different non-connected pieces of knowledge, which have not been fully integrated into a useful and interconnected big picture. In principle, mathematical models describing meal responses could be used for such an integration. However, today’s models still lack critical mechanisms, such as protein metabolism and a dynamic glycogen regulation. Herein, we present a) a new expanded model structure including these mechanisms; b) a set of parameters which can simultaneously describe a wide array of complementary estimation data, in both healthy and diabetic populations; c) a personalisation-script, which allows these generic parameters to be tuned to an individual/sub-population, using demographics (age, weight, height, diabetes status) and historic metabolic data. We exemplify how this personalisation can be used to predict new independent data, including a new clinical study, where a qualitatively new prediction is validated: that an oral protein tolerance test gives a clear response in plasma glucose, after, but not before, a 48h fasting period. Our combined model, parameters, and fitting script lay the foundation for an offline digital twin.

mTOR: A Potential New Target in Nonalcoholic Fatty Liver Disease

The global prevalence of nonalcoholic fatty liver disease (NAFLD) continues to rise, yet effective treatments are lacking due to the complex pathogenesis of this disease. Although recent research has provided evidence for the “multiple strikes” theory, the classic “two strikes” theory has not been overturned. Therefore, there is a crucial need to identify multiple targets in NAFLD pathogenesis for the development of diagnostic markers and targeted therapeutics. Since its discovery, the mechanistic target of rapamycin (mTOR) has been recognized as the central node of a network that regulates cell growth and development and is closely related to liver lipid metabolism and other processes. This paper will explore the mechanisms by which mTOR regulates lipid metabolism (SREBPs), insulin resistance (Foxo1, Lipin1), oxidative stress (PIG3, p53, JNK), intestinal microbiota (TLRs), autophagy, inflammation, genetic polymorphisms, and epigenetics in NAFLD. The specific influence of mTOR on NAFLD was hypothesized to be divided into micro regulation (the mechanism of mTOR’s influence on NAFLD factors) and macro mediation (the relationship between various influencing factors) to summarize the influence of mTOR on the developmental process of NAFLD, and prove the importance of mTOR as an influencing factor of NAFLD regarding multiple aspects. The effects of crosstalk between mTOR and its upstream regulators, Notch, Hedgehog, and Hippo, on the occurrence and development of NAFLD-associated hepatocellular carcinoma are also summarized. This analysis will hopefully support the development of diagnostic markers and new therapeutic targets in NAFLD.

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.

No evidence for change in expression of TBC1D1 and TBC1D4 genes in cultured human adipocytes stimulated by myokines and adipokines

TBC1D1 and TBC1D4 proteins play analogous, but not identical role in governing insulin-signalling pathway. Little is known about changes in expression levels of TBC1D1 and TBC1D4 genes in mammals, including humans. Number of factors were studied, but data remain controversial. The aim of this study was to evaluate the effect of selected cytokines, adipokines and myokines with known or putative insulin sensitivity regulation activity (adiponectin, irisin, omentin, interleukin 6, leptin, resistin, and tumour necrosis factor) on TBC1D1 and TBC1D4 expression levels in cultured differentiated human adipocytes. No significant differences were found between the adipocytes treated with different stimuli and this effect was determined not dose dependent. It is reasonable to conclude that relative shortage of data showing no change in TBC1D1 and TBC1D4 from literature results from publication bias; therefore, our finding provides additional insight into the role of both genes.

Dynamic modelling of the PI3K/MTOR signalling network uncovers biphasic dependence of mTORC1 activity on the mTORC2 subunit SIN1

The PI3K/MTOR signalling network regulates a broad array of critical cellular processes, including cell growth, metabolism and autophagy. The mechanistic target of rapamycin (MTOR) kinase functions as a core catalytic subunit in two physically and functionally distinct complexes mTORC1 and mTORC2, which also share other common components including MLST8 (also known as GβL) and DEPTOR. Despite intensive research, how mTORC1 and 2 assembly and activity are coordinated, and how they are functionally linked remain to be fully characterized. This is due in part to the complex network wiring, featuring multiple feedback loops and intricate post-translational modifications. Here, we integrate predictive network modelling, in vitro experiments and -omics data analysis to elucidate the emergent dynamic behaviour of the PI3K/MTOR network. We construct new mechanistic models that encapsulate critical mechanistic details, including mTORC1/2 coordination by MLST8 (de)ubiquitination and the Akt-to-mTORC2 positive feedback loop. Model simulations validated by experimental studies revealed a previously unknown biphasic, threshold-gated dependence of mTORC1 activity on the key mTORC2 subunit SIN1, which is robust against cell-to-cell variation in protein expression. In addition, our integrative analysis demonstrates that ubiquitination of MLST8, which is reversed by OTUD7B, is regulated by IRS1/2. Our results further support the essential role of MLST8 in enabling both mTORC1 and 2’s activity and suggest MLST8 as a viable therapeutic target in breast cancer. Overall, our study reports a new mechanistic model of PI3K/MTOR signalling incorporating MLST8-mediated mTORC1/2 formation and unveils a novel regulatory linkage between mTORC1 and mTORC2.

Signalling networks are the key information-processing machineries that underpin the ability of living cells to respond proportionately to extra- (and intra-) cellular cues. The PI3K/MTOR signalling network is one of the most important signalling networks in human cells that regulates cellular response to critical hormones such as insulin; yet our understanding of the network behaviour remains far from complete. Here, we employed a highly integrative approach that combines predictive mathematical modelling, biological experimentation, and data analysis to gain novel systems-level insights into PI3K/MTOR signalling. We constructed new mathematical models of this complex network incorporating important regulatory mechanisms. In contrary to commonly-held views that mTORC2 lies upstream and is a positive regulator of mTORC1, we found that their relationship is highly non-linear and dose dependent. This finding has major implications for anti-mTORC2 therapy as depending on the cellular contexts, inhibiting mTORC2 may either reduce or enhance mTORC1 activation, the latter could inadvertently dampen the effect of mTORC2 blockade. Furthermore, our results demonstrate that MLST8 is required for the assembly and activity of both MTOR complexes and suggest MLST8 is a viable therapeutic target in breast cancer.

An Updated Organ-Based Multi-Level Model for Glucose Homeostasis: Organ Distributions, Timing, and Impact of Blood Flow

Glucose homeostasis is the tight control of glucose in the blood. This complex control is important, due to its malfunction in serious diseases like diabetes, and not yet sufficiently understood. Due to the involvement of numerous organs and sub-systems, each with their own intra-cellular control, we have developed a multi-level mathematical model, for glucose homeostasis, which integrates a variety of data. Over the last 10 years, this model has been used to insert new insights from the intra-cellular level into the larger whole-body perspective. However, the original cell-organ-body translation has during these years never been updated, despite several critical shortcomings, which also have not been resolved by other modeling efforts. For this reason, we here present an updated multi-level model. This model provides a more accurate sub-division of how much glucose is being taken up by the different organs. Unlike the original model, we now also account for the different dynamics seen in the different organs. The new model also incorporates the central impact of blood flow on insulin-stimulated glucose uptake. Each new improvement is clear upon visual inspection, and they are also supported by statistical tests. The final multi-level model describes >300 data points in >40 time-series and dose-response curves, resulting from a large variety of perturbations, describing both intra-cellular processes, organ fluxes, and whole-body meal responses. We hope that this model will serve as an improved basis for future data integration, useful for research and drug developments within diabetes.

Forkhead Box Protein O1: Functional Diversity and Post-Translational Modification, a New Therapeutic Target?

Forkhead box protein O1 (FoXO1) is a transcription factor involved in the regulation of a wide variety of physiological process including glucose metabolism, lipogenesis, bone mass, apoptosis, and autophagy. FoXO1 dysfunction is involved in the pathophysiology of various diseases including metabolic diseases, atherosclerosis, and tumors. FoXO1 activity is regulated in response to different physiological or pathogenic conditions by changes in protein expression and post-translational modifications. Various modifications cooperate to regulate FoXO1 activity and FoXO1 target gene transcription. In this review, we summarize how different post-translational modifications regulate FoXO1 physiological function, which may provide new insights for drug design and development.

Finding new edges: systems approaches to MTOR signaling

Cells have evolved highly intertwined kinase networks to finely tune cellular homeostasis to the environment. The network converging on the mechanistic target of rapamycin (MTOR) kinase constitutes a central hub that integrates metabolic signals and adapts cellular metabolism and functions to nutritional changes and stress. Feedforward and feedback loops, crosstalks and a plethora of modulators finely balance MTOR-driven anabolic and catabolic processes. This complexity renders it difficult — if not impossible — to intuitively decipher signaling dynamics and network topology. Over the last two decades, systems approaches have emerged as powerful tools to simulate signaling network dynamics and responses. In this review, we discuss the contribution of systems studies to the discovery of novel edges and modulators in the MTOR network in healthy cells and in disease.

Insulin and β-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 β-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 β-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 β-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 β-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.

Whole Transcriptome Analysis of Obese Adipose Tissue Suggests u001kfc.1 as a Potential Regulator to Glucose Homeostasis

Long non-coding RNA (LncRNAs) are newly highlighted key factors controlling brown adipogenesis and development, but their regulatory effect to white adipocyte is still merely understood. Deciphering their underlying mechanism could be a novel way to discovering potential targets of obesity. Therefore, we conducted a whole transcriptome analysis in white adipose tissue from obese patients for the first time. Six obese patients and five control subjects were selected for microarray assay. Differentially expressed coding genes (DEGs), targets of lncRNAs, and alternatively spliced genes in obesity group were systematically compared in a functional framework based on a global gene regulatory network. It was demonstrated that all the three kinds of transcripts were enriched in pathways related to glucose metabolism while only DEGs showed closer proximity to neuro-endocrine-immune system. Thus, a lncRNA-regulated core network was constructed by a stepwise strategy using DEGs as seed nodes. From the core network, we identified a decreased lncRNA, uc001kfc.1, as potential cis-regulator for phosphatase and tensin homolog (PTEN) to enhance insulin sensitivity of white adipocytes in obese patients. We further validated the down-regulation of uc001kfc.1 and PTEN in an independent testing sample set enrolling 22 subjects via qRT-PCR. Although whether the decreased uc001kfc.1 correlated with low risk of diabetes deserved to be examined in an expanded cohort with long-term follow-up visit, the present study highlighted the potential of lncRNA regulating glucose homeostasis in human adipose tissue from a global perspective. With further improvement, such network-based analyzing protocol proposed in this study could be applied to interpreting function of more lncRNAs from other whole transcriptome data.

AKT/mTORC2 Inhibition Activates FOXO1 Function in CLL Cells Reducing B-Cell Receptor-Mediated Survival

PURPOSE

To determine whether inhibition of mTOR kinase-mediated signaling represents a valid therapeutic approach for chronic lymphocytic leukemia (CLL).

EXPERIMENTAL DESIGN

Stratification of mTOR activity was carried out in patients with primary CLL samples and an aggressive CLL-like mouse model. The potency of dual mTOR inhibitor AZD8055 to induce apoptosis in primary CLL cells was assessed in the presence/absence of B-cell receptor (BCR) ligation. Furthermore, we addressed the molecular and functional impact of dual mTOR inhibition in combination with BTK inhibitor ibrutinib.

RESULTS

Differential regulation of basal mTORC1 activity was observed in poor prognostic CLL samples, with elevated p4EBP1T37/46 and decreased p70S6 kinase activity, suggesting that dual mTORC1/2 inhibitors may exhibit improved response in poor prognostic CLL compared with rapalogs. AZD8055 treatment of primary CLL cells significantly reduced CLL survival in vitro compared with rapamycin, preferentially targeting poor prognostic subsets and overcoming BCR-mediated survival advantages. Furthermore, AZD8055, and clinical analog AZD2014, significantly reduced CLL tumor load in mice. AKT substrate FOXO1, while overexpressed in CLL cells of poor prognostic patients in LN biopsies, peripheral CLL cells, and mouse-derived CLL-like cells, appeared to be inactive. AZD8055 treatment partially reversed FOXO1 inactivation downstream of BCR crosslinking, significantly inhibiting FOXO1T24 phosphorylation in an mTORC2-AKT-dependent manner, to promote FOXO1 nuclear localization, activity, and FOXO1-mediated gene regulation. FOXO1 activity was further significantly enhanced on combining AZD8055 with ibrutinib.

CONCLUSIONS

Our studies demonstrate that dual mTOR inhibitors show promise as future CLL therapies, particularly in combination with ibrutinib.

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.

The Interface of Pancreatic Cancer With Diabetes, Obesity, and Inflammation: Research Gaps and Opportunities: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases Workshop

A workshop on "The Interface of Pancreatic Cancer with Diabetes, Obesity, and Inflammation: Research Gaps and Opportunities" was held by the National Institute of Diabetes and Digestive and Kidney Diseases on October 12, 2017. The purpose of the workshop was to explore the relationship and possible mechanisms of the increased risk of pancreatic ductal adenocarcinoma (PDAC) related to diabetes, the role of altered intracellular energy metabolism in PDAC, the mechanisms and biomarkers of diabetes caused by PDAC, the mechanisms of the increased risk of PDAC associated with obesity, and the role of inflammatory events and mediators as contributing causes of the development of PDAC. Workshop faculty reviewed the state of the current knowledge in these areas and made recommendations for future research efforts. Further knowledge is needed to elucidate the basic mechanisms contributing to the role of hyperinsulinemia, hyperglycemia, adipokines, and acute and chronic inflammatory events on the development of PDAC.

Systems biology reveals uncoupling beyond UCP1 in human white fat-derived beige adipocytes

Pharmaceutical induction of metabolically active beige adipocytes in the normally energy storing white adipose tissue has potential to reduce obesity. Mitochondrial uncoupling in beige adipocytes, as in brown adipocytes, has been reported to occur via the uncoupling protein 1 (UCP1). However, several previous in vitro characterizations of human beige adipocytes have only measured UCP1 mRNA fold increase, and assumed a direct correlation with metabolic activity. Here, we provide an example of pharmaceutical induction of beige adipocytes, where increased mRNA levels of UCP1 are not translated into increased protein levels, and perform a thorough analysis of this example. We incorporate mRNA and protein levels of UCP1, time-resolved mitochondrial characterizations, and numerous perturbations, and analyze all data with a new fit-for-purpose mathematical model. The systematic analysis challenges the seemingly obvious experimental conclusion, i.e., that UCP1 is not active in the induced cells, and shows that hypothesis testing with iterative modeling and experimental work is needed to sort out the role of UCP1. The analyses demonstrate, for the first time, that the uncoupling capability of human beige adipocytes can be obtained without UCP1 activity. This finding thus opens the door to a new direction in drug discovery that targets obesity and its associated comorbidities. Furthermore, the analysis advances our understanding of how to evaluate UCP1-independent thermogenesis in human beige adipocytes.

Mathematical modeling of white adipocyte exocytosis predicts adiponectin secretion and quantifies the rates of vesicle exo- and endocytosis

Adiponectin is a hormone secreted from white adipocytes and takes part in the regulation of several metabolic processes. Although the pathophysiological importance of adiponectin has been thoroughly investigated, the mechanisms controlling its release are only partly understood. We have recently shown that adiponectin is secreted via regulated exocytosis of adiponectin-containing vesicles, that adiponectin exocytosis is stimulated by cAMP-dependent mechanisms, and that Ca²⁺ and ATP augment the cAMP-triggered secretion. However, much remains to be discovered regarding the molecular and cellular regulation of adiponectin release. Here, we have used mathematical modeling to extract detailed information contained within our previously obtained high-resolution patch-clamp time-resolved capacitance recordings to produce the first model of adiponectin exocytosis/secretion that combines all mechanistic knowledge deduced from electrophysiological experimental series. This model demonstrates that our previous understanding of the role of intracellular ATP in the control of adiponectin exocytosis needs to be revised to include an additional ATP-dependent step. Validation of the model by introduction of data of secreted adiponectin yielded a very close resemblance between the simulations and experimental results. Moreover, we could show that Ca²⁺-dependent adiponectin endocytosis contributes to the measured capacitance signal, and we were able to predict the contribution of endocytosis to the measured exocytotic rate under different experimental conditions. In conclusion, using mathematical modeling of published and newly generated data, we have obtained estimates of adiponectin exo- and endocytosis rates, and we have predicted adiponectin secretion. We believe that our model should have multiple applications in the study of metabolic processes and hormonal control thereof.

A systems biology analysis connects insulin receptor signaling with glucose transporter translocation in rat adipocytes

Type 2 diabetes is characterized by insulin resistance, which arises from malfunctions in the intracellular insulin signaling network. Knowledge of the insulin signaling network is fragmented, and because of the complexity of this network, little consensus has emerged for the structure and importance of the different branches of the network. To help overcome this complexity, systems biology mathematical models have been generated for predicting both the activation of the insulin receptor (IR) and the redistribution of glucose transporter 4 (GLUT4) to the plasma membrane. Although the insulin signal transduction between IR and GLUT4 has been thoroughly studied with modeling and time-resolved data in human cells, comparable analyses in cells from commonly used model organisms such as rats and mice are lacking. Here, we combined existing data and models for rat adipocytes with new data collected for the signaling network between IR and GLUT4 to create a model also for their interconnections. To describe all data (>140 data points), the model needed three distinct pathways from IR to GLUT4: (i) via protein kinase B (PKB) and Akt substrate of 160 kDa (AS160), (ii) via an AS160-independent pathway from PKB, and (iii) via an additional pathway from IR, e.g. affecting the membrane constitution. The developed combined model could describe data not used for training the model and was used to generate predictions of the relative contributions of the pathways from IR to translocation of GLUT4. The combined model provides a systems-level understanding of insulin signaling in rat adipocytes, which, when combined with corresponding models for human adipocytes, may contribute to model-based drug development for diabetes.

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.

Could S6K1 immunopositivity be used to distinguish early and advanced stages of endometrioid endometrial adenocarcinoma?

OBJECTIVE

To assess whether the immunopositivity of S6K1, a crucial effector of the mTOR signaling pathway, varies between early-stage low-grade and advanced-stage high-grade endometrial endometrioid adenocarcinoma (EEA) as well as to discuss its prognostic significance.

MATERIAL AND METHODS

A total of 22 normal endometrial tissue samples (Control group) and 41 EEA specimens (Study group) were enrolled in the study, and all the samples underwent immunohistochemical staining for S6 kinase alpha (S6K1). The study group was further evaluated in two subgroups; stage 1A, grade 1 (Group 1) and stage ≥1A, grade 2 or 3 (Group 2). Group 2 patients were considered as a poor prognosis for EEA. The samples were examined by two independent pathologists. Statistical analyses were performed using the Student's t-test for continuous variables, the Chi-square test for categorical variables, and one-way analysis of variance for the comparison of multiple variables.

RESULTS

The immunopositivity rate for all the included EEA patients was 56.1%, whereas none of the 22 normal endometrial tissue samples revealed immunoreactivity for S6K1. The immunopositivity rates were significantly different between Groups 1 and 2 [38.1% (8/21) and 75.0% (15/20), respectively, p=0.039]. When S6K1 positivity was used as a criterion of poor prognosis in EEA, the sensitivity, specificity, positive predictive value, and negative predictive value were calculated to be 62%, 75%, 72%, and 65%, respectively (OR: 4.9 and 95% CI: 1.3-18.7).

CONCLUSION

S6K1 was positive in the majority of EEAs and malignancies at an advanced stage. Higher grade disease had a significantly higher rate of S6K1 positivity. S6K1 immunopositivity appears to be a promising method to predict poor prognosis in EEA.

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.