Phosphorylation of IRS1 at Serine 307 in Response to Insulin in Human Adipocytes Is Not Likely to be Catalyzed by p70 Ribosomal S6 Kinase

Rajan, Meenu Rohini; Fagerholm, Siri; Jönsson, Cecilia; Kjølhede, Preben; Turkina, Maria V.; Strålfors, Peter

doi:10.1371/journal.pone.0059725

Cited by 16 publications

(25 citation statements)

References 41 publications

(37 reference statements)

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“…6B, blue). Strikingly, the alignment of the doseresponse curves in the signaling cassette IRS1-Grb2-Sos-RasRaf-Mek1/2-ERK1/2 is in sharp contrast to the 10-fold increase in insulin sensitivity 4 in the parallel IRS1-PI3K-PKB-AS160 cassette mediating insulin control of glucose uptake (3). The function of this difference in insulin signal transduction is not known, but it has been shown in yeast cells that alignment of doseresponse curves, due to negative feedback signals, in MAPK signaling allows for higher fidelity in signal transmission (48).…”

Section: Phosphorylation Of Erk1/2 In Response To Different Concentramentioning

confidence: 99%

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A Single Mechanism Can Explain Network-wide Insulin Resistance in Adipocytes from Obese Patients with Type 2 Diabetes

Nyman

Rajan

Fagerholm

et al. 2014

Journal of Biological Chemistry

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Background: Molecular mechanisms of insulin resistance in diabetes are poorly understood. Results: Quantitative systems-wide data reveal that a single mechanism can explain insulin resistance throughout the signaling network in human adipocytes. Conclusion:The most important aspect of the insulin resistance mechanism is an attenuated feedback signal. Significance: The study demonstrates how insulin resistance originates and propagates throughout the signaling network in cells from patients with diabetes.

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Section: Phosphorylation Of Erk1/2 In Response To Different Concentramentioning

confidence: 99%

“…We have taken a systems approach to the investigation of the mechanisms of insulin resistance, and we have previously described the branch of the insulin signaling network that leads to control of glucose uptake in human adipocytes, normally and in T2D (1)(2)(3)(4) (Fig. 1).…”

mentioning

confidence: 99%

A Single Mechanism Can Explain Network-wide Insulin Resistance in Adipocytes from Obese Patients with Type 2 Diabetes

Nyman

Rajan

Fagerholm

et al. 2014

Journal of Biological Chemistry

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“…Also in isolated human adipocytes, insulinstimulated phosphorylation of IRS1 at Ser 307 is affected by rapamycin treatment [66,67]. The phosphorylation of IRS1 at Ser 307 has been suggested to occur downstream of S6K, but we have shown that it is unlikely that S6K is the kinase for phosphorylation of IRS1 at Ser 307, at least in human adipocytes [68]. We have observed a positive effect of phosphorylation of IRS1 at Ser 307 on the phosphorylation of IRS1 at Tyr in human adipocytes: rapamycin reduces also the phosphorylation of IRS1 at Tyr [66].…”

Section: Regulatory Feedbacks Control Insulin Signaling Via Irs1mentioning

confidence: 66%

Insulin signaling dynamics in human adipocytes : Mathematical modeling reveals mechanisms of insulin resistance in type 2 diabetes

Nyman¹

2014

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Type 2 diabetes is characterized by raised blood glucose levels caused by an insufficient insulin control of glucose homeostasis. This lack of control is expressed both through insufficient release of insulin by the pancreatic beta-cells, and through insulin resistance in the insulin-responding tissues. We find insulin resistance of the adipose tissue particularly interesting since it appears to influence other insulin-responding tissues, such as muscle and liver, to also become insulin resistant.The insulin signaling network is highly complex with cross-interacting intermediaries, positive and negative feedbacks, etc. To facilitate the mechanistic understanding of this network, we obtain dynamic, information-rich data and use model-based analysis as a tool to formally test different hypotheses that arise from the experimental observations. With dynamic mathematical models, we are able to combine knowledge and experimental data into mechanistic hypotheses, and draw conclusions such as rejection of hypotheses and prediction of outcomes of new experiments.We aim for an increased understanding of adipocyte insulin signaling and the underlying mechanisms of the insulin resistance that we observe in adipocytes from subjects diagnosed with type 2 diabetes. We also aim for a complete picture of the insulin signaling network in primary human adipocytes from normal and diabetic subjects with a link to relevant clinical parameters: plasma glucose and insulin. Such a complete picture of insulin signaling has not been presented before. Not for adipocytes and not for other types of cells.In this thesis, I present the development of the first comprehensive insulin signaling model that can simulate both normal and diabetic data from adipocytes -and that is linked to a whole-body glucose-insulin model. In the linking process we conclude that at least two glucose uptake parameters differ between the in vivo and in vitro conditions (Paper I). We also perform a model analysis of the early insulin signaling dynamics in rat adipocytes and conclude that internalization is important for an apparent reversed order of phosphorylation seen in these cells (Paper II). In the development of the first version of the comprehensive insulin signaling model, we introduce a key parameter for the diabetic state -an attenuated feedback (Paper III). We finally continue to build on the comprehensive model and include signaling to nuclear transcription via ERK and report substantial crosstalk in the insulin signaling network (Paper IV). Populärvetenskaplig sammanfattningTyp 2-diabetes är en vanligt förekommande sjukdom där kroppens vävnader förlorar sin känslighet mot hormonet insulin. Insulinets uppgift är att hålla en jämn blodsockernivå dygnet runt. Insulin utsöndras i samband med måltider och påverkar muskel-och fettvävnader att ta upp socker och levern att sluta producera socker. Det är viktigt att hålla en jämn blodsockernivå eftersom låga nivåer kan vara direkt dödligt och höga nivåer är skadligt för blodkärlen, vilket i sin tur kan led...

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“…One of the most important consequences of the initiated signaling cascade is the recruitment of Glucose Transporter 4 (GLUT4) containing vesicles into the plasma membrane, which results in an increased uptake of glucose into the adipocyte. In Paper II, we focus on a particular aspect of the green arrow in Figure 32, namely the positive feedback from a downstream component (here shown as mTOR) up to IRS1.This feedback had been shown in other cell types to come directly from S6K, but experimental evidence suggest that this was not the case in human adipocytes [127]. In Paper II, we investigate whether this conclusion held up under further scrutiny, and which conditions must apply for it to be considered valid.…”

Section: Insulin Signaling System In Human Adipocytesmentioning

confidence: 99%

“…We then applied this specific methodology to re-interpret data pertaining to the phosphorylation of IRS1 on serine residue 307. It had previously been shown that in primary human adipocytes, unlike other known cell lines, S6K inhibition by DN transfection did not result in any effect on IRS1-ser307 phosphorylation [127]. This lack of response was used as evidence to suggest that S6K was unlikely to be the kinase responsible for IRS1-ser307 phosphorylation in this cell type.…”

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confidence: 96%

Model-Based Hypothesis Testing in Biomedicine : How Systems Biology Can Drive the Growth of Scientific Knowledge

Johansson¹

2017

Linköping Studies in Science and Technology. Dissertations

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The utilization of mathematical tools within biology and medicine has traditionally been less widespread compared to other hard sciences, such as physics and chemistry. However, an increased need for tools such as data processing, bioinformatics, statistics, and mathematical modeling, have emerged due to advancements during the last decades. These advancements are partly due to the development of high-throughput experimental procedures and techniques, which produce ever increasing amounts of data. For all aspects of biology and medicine, these data reveal a high level of inter-connectivity between components, which operate on many levels of control, and with multiple feedbacks both between and within each level of control. However, the availability of these large-scale data is not synonymous to a detailed mechanistic understanding of the underlying system. Rather, a mechanistic understanding is gained first when we construct a hypothesis, and test its predictions experimentally. Identifying interesting predictions that are quantitative in nature, generally requires mathematical modeling. This, in turn, requires that the studied system can be formulated into a mathematical model, such as a series of ordinary differential equations, where different hypotheses can be expressed as precise mathematical expressions that influence the output of the model.Within specific sub-domains of biology, the utilization of mathematical models have had a long tradition, such as the modeling done on electrophysiology by Hodgkin and Huxley in the 1950s. However, it is only in recent years, with the arrival of the field known as systems biology that mathematical modeling has become more commonplace. The somewhat slow adaptation of mathematical modeling in biology is partly due to historical differences in training and terminology, as well as in a lack of awareness of showcases illustrating how modeling can make a difference, or even be required, for a correct analysis of the experimental data.In this work, I provide such showcases by demonstrating the universality and applicability of mathematical modeling and hypothesis testing in three disparate biological systems. In Paper II, we demonstrate how mathematical modeling is necessary for the correct interpretation and analysis of dominant negative inhibition data in insulin signaling in primary human adipocytes. In Paper III, we use modeling to determine transport rates across the nuclear membrane in yeast cells, and we show how this technique is superior to traditional curve-fitting methods. We also demonstrate the issue of population heterogeneity and the need to account for individual differences between cells and the population at large. In Paper IV, we use mathematical modeling to reject three hypotheses concerning the phenomenon of facilitation in pyramidal nerve cells in rats and mice. We also show how one surviving hypothesis can explain all data and adequately describe independent validation data. Finally, in Paper I, we develop a method for model selection and discri...

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Phosphorylation of IRS1 at Serine 307 in Response to Insulin in Human Adipocytes Is Not Likely to be Catalyzed by p70 Ribosomal S6 Kinase

Cited by 16 publications

References 41 publications

A Single Mechanism Can Explain Network-wide Insulin Resistance in Adipocytes from Obese Patients with Type 2 Diabetes

A Single Mechanism Can Explain Network-wide Insulin Resistance in Adipocytes from Obese Patients with Type 2 Diabetes

Insulin signaling dynamics in human adipocytes : Mathematical modeling reveals mechanisms of insulin resistance in type 2 diabetes

Model-Based Hypothesis Testing in Biomedicine : How Systems Biology Can Drive the Growth of Scientific Knowledge

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