A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network

Lan K Nguyen, Miguel AS Cavadas, Carsten C Scholz, Susan F Fitzpatrick, Ulrike Bruning, Eoin P Cummins, Murtaza Tambuwala, Mario C Manres, Boris N Kholodenko, Cormac T Taylor, Alex Cheong

Research output: Contribution to journalArticle

71 Citations (Scopus)

Abstract

Activation of the hypoxia-inducible factor (HIF) pathway is a critical step in the transcriptional response to hypoxia. Although many of the key proteins involved have been characterised, the dynamics of their interactions in generating this response remain unclear. In the present study, we have generated a comprehensive mathematical model of the HIF-1α pathway based on core validated components and dynamic experimental data, and confirm the previously described connections within the predicted network topology. Our model confirms previous work demonstrating that the steps leading to optimal HIF-1α transcriptional activity require sequential inhibition of both prolyl- and asparaginyl-hydroxylases. We predict from our model (and confirm experimentally) that there is residual activity of the asparaginyl-hydroxylase FIH (factor inhibiting HIF) at low oxygen tension. Furthermore, silencing FIH under conditions where prolyl-hydroxylases are inhibited results in increased HIF-1α transcriptional activity, but paradoxically decreases HIF-1α stability. Using a core module of the HIF network and mathematical proof supported by experimental data, we propose that asparaginyl hydroxylation confers a degree of resistance upon HIF-1α to proteosomal degradation. Thus, through in vitro experimental data and in silico predictions, we provide a comprehensive model of the dynamic regulation of HIF-1α transcriptional activity by hydroxylases and use its predictive and adaptive properties to explain counter-intuitive biological observations.
LanguageEnglish
Pages1454
JournalJOURNAL OF CELL SCIENCE
Volume126
Issue number6
DOIs
Publication statusPublished - 2013

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Hypoxia-Inducible Factor 1
Prolyl Hydroxylases
Mixed Function Oxygenases
Hypoxia
Hydroxylation
Computer Simulation
Theoretical Models
Oxygen

Cite this

Nguyen, L. K., Cavadas, M. AS., Scholz, C. C., Fitzpatrick, S. F., Bruning, U., Cummins, E. P., ... Cheong, A. (2013). A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network. JOURNAL OF CELL SCIENCE, 126(6), 1454. https://doi.org/10.1242/jcs.119974
Nguyen, Lan K ; Cavadas, Miguel AS ; Scholz, Carsten C ; Fitzpatrick, Susan F ; Bruning, Ulrike ; Cummins, Eoin P ; Tambuwala, Murtaza ; Manres, Mario C ; Kholodenko, Boris N ; Taylor, Cormac T ; Cheong, Alex. / A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network. In: JOURNAL OF CELL SCIENCE. 2013 ; Vol. 126, No. 6. pp. 1454.
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Nguyen, LK, Cavadas, MAS, Scholz, CC, Fitzpatrick, SF, Bruning, U, Cummins, EP, Tambuwala, M, Manres, MC, Kholodenko, BN, Taylor, CT & Cheong, A 2013, 'A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network', JOURNAL OF CELL SCIENCE, vol. 126, no. 6, pp. 1454. https://doi.org/10.1242/jcs.119974

A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network. / Nguyen, Lan K; Cavadas, Miguel AS; Scholz, Carsten C; Fitzpatrick, Susan F; Bruning, Ulrike; Cummins, Eoin P; Tambuwala, Murtaza; Manres, Mario C; Kholodenko, Boris N; Taylor, Cormac T; Cheong, Alex.

In: JOURNAL OF CELL SCIENCE, Vol. 126, No. 6, 2013, p. 1454.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network

AU - Nguyen, Lan K

AU - Cavadas, Miguel AS

AU - Scholz, Carsten C

AU - Fitzpatrick, Susan F

AU - Bruning, Ulrike

AU - Cummins, Eoin P

AU - Tambuwala, Murtaza

AU - Manres, Mario C

AU - Kholodenko, Boris N

AU - Taylor, Cormac T

AU - Cheong, Alex

PY - 2013

Y1 - 2013

N2 - Activation of the hypoxia-inducible factor (HIF) pathway is a critical step in the transcriptional response to hypoxia. Although many of the key proteins involved have been characterised, the dynamics of their interactions in generating this response remain unclear. In the present study, we have generated a comprehensive mathematical model of the HIF-1α pathway based on core validated components and dynamic experimental data, and confirm the previously described connections within the predicted network topology. Our model confirms previous work demonstrating that the steps leading to optimal HIF-1α transcriptional activity require sequential inhibition of both prolyl- and asparaginyl-hydroxylases. We predict from our model (and confirm experimentally) that there is residual activity of the asparaginyl-hydroxylase FIH (factor inhibiting HIF) at low oxygen tension. Furthermore, silencing FIH under conditions where prolyl-hydroxylases are inhibited results in increased HIF-1α transcriptional activity, but paradoxically decreases HIF-1α stability. Using a core module of the HIF network and mathematical proof supported by experimental data, we propose that asparaginyl hydroxylation confers a degree of resistance upon HIF-1α to proteosomal degradation. Thus, through in vitro experimental data and in silico predictions, we provide a comprehensive model of the dynamic regulation of HIF-1α transcriptional activity by hydroxylases and use its predictive and adaptive properties to explain counter-intuitive biological observations.

AB - Activation of the hypoxia-inducible factor (HIF) pathway is a critical step in the transcriptional response to hypoxia. Although many of the key proteins involved have been characterised, the dynamics of their interactions in generating this response remain unclear. In the present study, we have generated a comprehensive mathematical model of the HIF-1α pathway based on core validated components and dynamic experimental data, and confirm the previously described connections within the predicted network topology. Our model confirms previous work demonstrating that the steps leading to optimal HIF-1α transcriptional activity require sequential inhibition of both prolyl- and asparaginyl-hydroxylases. We predict from our model (and confirm experimentally) that there is residual activity of the asparaginyl-hydroxylase FIH (factor inhibiting HIF) at low oxygen tension. Furthermore, silencing FIH under conditions where prolyl-hydroxylases are inhibited results in increased HIF-1α transcriptional activity, but paradoxically decreases HIF-1α stability. Using a core module of the HIF network and mathematical proof supported by experimental data, we propose that asparaginyl hydroxylation confers a degree of resistance upon HIF-1α to proteosomal degradation. Thus, through in vitro experimental data and in silico predictions, we provide a comprehensive model of the dynamic regulation of HIF-1α transcriptional activity by hydroxylases and use its predictive and adaptive properties to explain counter-intuitive biological observations.

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DO - 10.1242/jcs.119974

M3 - Article

VL - 126

SP - 1454

JO - JOURNAL OF CELL SCIENCE

T2 - JOURNAL OF CELL SCIENCE

JF - JOURNAL OF CELL SCIENCE

SN - 0021-9533

IS - 6

ER -

Nguyen LK, Cavadas MAS, Scholz CC, Fitzpatrick SF, Bruning U, Cummins EP et al. A dynamic model of the hypoxia-inducible factor 1 (HIF-1 ) network. JOURNAL OF CELL SCIENCE. 2013;126(6):1454. https://doi.org/10.1242/jcs.119974