Literature DB >> 18469073

Positive receptor feedback during lineage commitment can generate ultrasensitivity to ligand and confer robustness to a bistable switch.

Santhosh Palani1, Casim A Sarkar.   

Abstract

Cytokines and lineage-specific transcription factors are critical molecular effectors for terminal differentiation during hematopoiesis. Intrinsic transcription factor activity is often believed to drive commitment and differentiation, whereas cytokine receptor signals have been implicated in the regulation of cell proliferation, survival, and differentiation. In erythropoiesis, recent experimental findings provide direct evidence that erythropoietin (Epo) can generate commitment cues via the erythropoietin receptor (EpoR); specifically, EpoR signaling leads to activation of the transcription factor GATA-1, which then triggers transcription of erythrocyte-specific genes. In particular, activated GATA-1 induces two positive feedback loops in the system through the enhanced expression of both inactive GATA-1 and EpoR, the latter of which is externally regulatable by Epo. Based upon this network architecture, we present a mathematical model of GATA-1 activation by EpoR, which bidirectionally links a lineage-specific receptor and transcription factor. Our deterministic model offers insight into stimulus-response relationships between Epo and several downstream effectors. In addition to the survival signals that EpoR provides, steady-state analysis of our model suggests that receptor upregulation during lineage commitment can also generate ultrasensitivity to Epo and bistability in GATA-1 activity. These system-level properties can induce a switch-like characteristic during differentiation and provide robustness to the mature state. The topology also suggests a novel mechanism for achieving robust bistability in a purely deterministic manner without molecular cooperativity. The analytical solution of a generalized, minimal model is provided and the significance of each of the two positive feedback loops is elucidated through bifurcation analysis. This network topology, or variations thereof, may link other receptor-transcription factor pairs and may therefore be of general relevance in cellular decision-making.

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Year:  2008        PMID: 18469073      PMCID: PMC2483757          DOI: 10.1529/biophysj.107.120600

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


  84 in total

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Authors:  S F Tsai; E Strauss; S H Orkin
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4.  Sequence of the human GATA-1 promoter.

Authors:  L I Zon; S H Orkin
Journal:  Nucleic Acids Res       Date:  1992-04-11       Impact factor: 16.971

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Authors:  Heather M Rooke; Stuart H Orkin
Journal:  Blood       Date:  2006-01-03       Impact factor: 22.113

6.  Proliferation and maturation of human erythroid progenitors in liquid culture.

Authors:  E Fibach; D Manor; A Oppenheim; E A Rachmilewitz
Journal:  Blood       Date:  1989-01       Impact factor: 22.113

7.  Structure and promoter activity of the gene for the erythroid transcription factor GATA-1.

Authors:  R Hannon; T Evans; G Felsenfeld; H Gould
Journal:  Proc Natl Acad Sci U S A       Date:  1991-04-15       Impact factor: 11.205

8.  Characterization of murine erythropoietin receptor genes.

Authors:  S Kuramochi; Y Ikawa; K Todokoro
Journal:  J Mol Biol       Date:  1990-12-05       Impact factor: 5.469

9.  Domain swapping used to investigate the mechanism of protein kinase B regulation by 3-phosphoinositide-dependent protein kinase 1 and Ser473 kinase.

Authors:  M Andjelković; S M Maira; P Cron; P J Parker; B A Hemmings
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Journal:  FEBS Lett       Date:  2003-01-16       Impact factor: 4.124

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  21 in total

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4.  Human erythropoietin gene delivery using an arginine-grafted bioreducible polymer system.

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Review 5.  Non-transcriptional regulatory processes shape transcriptional network dynamics.

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6.  Dynamic Modeling of Transcriptional Gene Regulatory Networks.

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7.  The osteogenic effect of erythropoietin on human mesenchymal stromal cells is dose-dependent and involves non-hematopoietic receptors and multiple intracellular signaling pathways.

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8.  Robust hematopoietic progenitor cell commitment in the presence of a conflicting cue.

Authors:  Najaf A Shah; Marshall J Levesque; Arjun Raj; Casim A Sarkar
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9.  Stochastic modeling of B lymphocyte terminal differentiation and its suppression by dioxin.

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10.  Integrating extrinsic and intrinsic cues into a minimal model of lineage commitment for hematopoietic progenitors.

Authors:  Santhosh Palani; Casim A Sarkar
Journal:  PLoS Comput Biol       Date:  2009-09-25       Impact factor: 4.475

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