Literature DB >> 18539637

Identifying fragilities in biochemical networks: robust performance analysis of Fas signaling-induced apoptosis.

Jason E Shoemaker1, Francis J Doyle.   

Abstract

Proper control of apoptotic signaling is critical to immune response and development in multicellular organisms. Two tools from control engineering are applied to a mathematical model of Fas ligand signaling-induced apoptosis. Structured singular value analysis determines the volume in parameter space within which the system parameters may exist and still maintain efficacious signaling, but is limited to linear behaviors. Sensitivity analysis can be applied to nonlinear systems but is difficult to relate to performance criteria. Thus, structured singular value analysis is used to quantify performance during apoptosis rejection, ensuring that the system remains sensitive but not overly so to apoptotic stimuli. Sensitivity analysis is applied when the system has switched to the death-inducing, apoptotic steady state to determine parameters significant to maintaining the bistability. The analyses reveal that the magnitude of the death signal is fragile to perturbations in degradation parameters (failures in the ubiquitin/proteasome mechanism) while the timing of signal expression can be tuned by manipulating local parameters. Simultaneous parameter uncertainty highlights apoptotic fragility to disturbances in the ubiquitin/proteasome system. Sensitivity analysis reveals that the robust signaling characteristics of the apoptotic network is due to network architecture, and the apoptotic signaling threshold is best manipulated by interactions upstream of the apoptosome.

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Year:  2008        PMID: 18539637      PMCID: PMC2527273          DOI: 10.1529/biophysj.107.123398

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  34 in total

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2.  Robustness properties of circadian clock architectures.

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Review 3.  Computational identification of inhibitors of protein-protein interactions.

Authors:  Shijun Zhong; Alba T Macias; Alexander D MacKerell
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4.  Linear systems approach to analysis of complex dynamic behaviours in biochemical networks.

Authors:  H Schmidt; E W Jacobsen
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5.  Impairment of the ubiquitin-proteasome system by cellular FLIP.

Authors:  Toshiyasu Ishioka; Ryohei Katayama; Ryo Kikuchi; Michie Nishimoto; Shinji Takada; Ritsuko Takada; Shu-ichi Matsuzawa; John C Reed; Takashi Tsuruo; Mikihiko Naito
Journal:  Genes Cells       Date:  2007-06       Impact factor: 1.891

6.  Bistability in apoptosis: roles of bax, bcl-2, and mitochondrial permeability transition pores.

Authors:  E Z Bagci; Y Vodovotz; T R Billiar; G B Ermentrout; I Bahar
Journal:  Biophys J       Date:  2005-12-09       Impact factor: 4.033

7.  The course of etoposide-induced apoptosis from damage to DNA and p53 activation to mitochondrial release of cytochrome c.

Authors:  Natalie O Karpinich; Marco Tafani; Ronald J Rothman; Matteo A Russo; John L Farber
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8.  Ubiquitin-proteasome pathway as a primary defender against TRAIL-mediated cell death.

Authors:  S Kim; K Choi; D Kwon; E N Benveniste; C Choi
Journal:  Cell Mol Life Sci       Date:  2004-05       Impact factor: 9.261

9.  Kinetic simulation of signal transduction system in hippocampal long-term potentiation with dynamic modeling of protein phosphatase 2A.

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Review 10.  Transcription protein STAT1: biology and relation to cancer.

Authors:  L Adámková; K Soucková; J Kovarík
Journal:  Folia Biol (Praha)       Date:  2007       Impact factor: 0.906

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  7 in total

1.  Analysis of a mathematical model of apoptosis: individual differences and malfunction in programmed cell death.

Authors:  Elife Zerrin Bagci; S Murat Sen; Mehmet C Camurdan
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Review 2.  Dynamic modelling of oestrogen signalling and cell fate in breast cancer cells.

Authors:  John J Tyson; William T Baumann; Chun Chen; Anael Verdugo; Iman Tavassoly; Yue Wang; Louis M Weiner; Robert Clarke
Journal:  Nat Rev Cancer       Date:  2011-06-16       Impact factor: 60.716

3.  Ensembles of signal transduction models using Pareto Optimal Ensemble Techniques (POETs).

Authors:  Sang Ok Song; Anirikh Chakrabarti; Jeffrey D Varner
Journal:  Biotechnol J       Date:  2010-07       Impact factor: 4.677

4.  Fathead minnow steroidogenesis: in silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk.

Authors:  Jason E Shoemaker; Kalyan Gayen; Natàlia Garcia-Reyero; Edward J Perkins; Daniel L Villeneuve; Li Liu; Francis J Doyle
Journal:  BMC Syst Biol       Date:  2010-06-28

5.  Understanding dynamics using sensitivity analysis: caveat and solution.

Authors:  Thanneer M Perumal; Rudiyanto Gunawan
Journal:  BMC Syst Biol       Date:  2011-03-15

6.  Confidence from uncertainty--a multi-target drug screening method from robust control theory.

Authors:  Camilla Luni; Jason E Shoemaker; Kevin R Sanft; Linda R Petzold; Francis J Doyle
Journal:  BMC Syst Biol       Date:  2010-11-24

7.  An Ultrasensitive Mechanism Regulates Influenza Virus-Induced Inflammation.

Authors:  Jason E Shoemaker; Satoshi Fukuyama; Amie J Eisfeld; Dongming Zhao; Eiryo Kawakami; Saori Sakabe; Tadashi Maemura; Takeo Gorai; Hiroaki Katsura; Yukiko Muramoto; Shinji Watanabe; Tokiko Watanabe; Ken Fuji; Yukiko Matsuoka; Hiroaki Kitano; Yoshihiro Kawaoka
Journal:  PLoS Pathog       Date:  2015-06-05       Impact factor: 6.823

  7 in total

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