Literature DB >> 22248283

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

Elin Nyman1, Siri Fagerholm, David Jullesson, Peter Strålfors, Gunnar Cedersund.   

Abstract

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.
© 2012 The Authors Journal compilation © 2012 FEBS.

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Year:  2012        PMID: 22248283     DOI: 10.1111/j.1742-4658.2012.08488.x

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  7 in total

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

Authors:  Niclas Bergqvist; Elin Nyman; Gunnar Cedersund; Karin G Stenkula
Journal:  J Biol Chem       Date:  2017-05-11       Impact factor: 5.157

2.  A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling.

Authors:  Cemal Erdem; Arnab Mutsuddy; Ethan M Bensman; William B Dodd; Michael M Saint-Antoine; Mehdi Bouhaddou; Robert C Blake; Sean M Gross; Laura M Heiser; F Alex Feltus; Marc R Birtwistle
Journal:  Nat Commun       Date:  2022-06-21       Impact factor: 17.694

3.  LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

Authors:  Rasmus Magnusson; Guido Pio Mariotti; Mattias Köpsén; William Lövfors; Danuta R Gawel; Rebecka Jörnsten; Jörg Linde; Torbjörn E M Nordling; Elin Nyman; Sylvie Schulze; Colm E Nestor; Huan Zhang; Gunnar Cedersund; Mikael Benson; Andreas Tjärnberg; Mika Gustafsson
Journal:  PLoS Comput Biol       Date:  2017-06-22       Impact factor: 4.475

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

Authors:  Rasmus Magnusson; Mika Gustafsson; Gunnar Cedersund; Peter Strålfors; Elin Nyman
Journal:  Biosci Rep       Date:  2017-01-24       Impact factor: 3.840

5.  Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors.

Authors:  Nicolas Sundqvist; Nina Grankvist; Jeramie Watrous; Jain Mohit; Roland Nilsson; Gunnar Cedersund
Journal:  PLoS Comput Biol       Date:  2022-04-11       Impact factor: 4.779

6.  Rapamycin reverses insulin resistance (IR) in high-glucose medium without causing IR in normoglycemic medium.

Authors:  O V Leontieva; Z N Demidenko; M V Blagosklonny
Journal:  Cell Death Dis       Date:  2014-05-08       Impact factor: 8.469

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

Authors:  Rikard Johansson; Peter Strålfors; Gunnar Cedersund
Journal:  BMC Syst Biol       Date:  2014-04-17
  7 in total

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