Literature DB >> 9224632

Analysis of E-box DNA binding during myeloid differentiation reveals complexes that contain Mad but not Max.

K M Ryan1, G D Birnie.   

Abstract

It has been shown that during myeloid differentiation the levels of mad1 mRNA are induced before the loss of c-Myc protein. This suggests that inactivation of the differentiation-blocking activity of c-Myc might not occur primarily through the loss of Myc protein, but through an increase in the levels of its antagonist, Mad1. To investigate this question we have analysed the levels of mad1 mRNA during differentiation of myeloid leukaemic HL60 cells. Although levels of mad1 mRNA were moderately increased after induction with phorbol ester, we also found that differentiation could be achieved with other inducers without any concomitant up-regulation of mad1 mRNA. In addition, analysis of E-box DNA binding revealed that, although Myc-Max complexes were lost rapidly after differentiation induction, formation of Mad1-containing complexes only occurred during the later stages of the differentiation programme. Further analysis of these Mad-containing complexes revealed that they were also unlikely to have the capacity to antagonize c-Myc function, as they did not contain Max. Therefore these data suggest that an increase in the levels of mad1 mRNA or the formation of a Mad-Max complex are unlikely to be essential or determining events for myeloid differentiation. In addition, the discovery of DNA-binding complexes that contain Mad1, but not Max, opens up this transcription factor network to include other Max-like proteins or proteins of an unrelated nature.

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Year:  1997        PMID: 9224632      PMCID: PMC1218531          DOI: 10.1042/bj3250079

Source DB:  PubMed          Journal:  Biochem J        ISSN: 0264-6021            Impact factor:   3.857


  36 in total

1.  A switch from Myc:Max to Mad:Max heterocomplexes accompanies monocyte/macrophage differentiation.

Authors:  D E Ayer; R N Eisenman
Journal:  Genes Dev       Date:  1993-11       Impact factor: 11.361

2.  Mad: a heterodimeric partner for Max that antagonizes Myc transcriptional activity.

Authors:  D E Ayer; L Kretzner; R N Eisenman
Journal:  Cell       Date:  1993-01-29       Impact factor: 41.582

Review 3.  Myc-Max-Mad: a transcription factor network controlling cell cycle progression, differentiation and death.

Authors:  B Amati; H Land
Journal:  Curr Opin Genet Dev       Date:  1994-02       Impact factor: 5.578

4.  c-Myc induces the expression and activity of ornithine decarboxylase.

Authors:  A J Wagner; C Meyers; L A Laimins; N Hay
Journal:  Cell Growth Differ       Date:  1993-11

5.  The ornithine decarboxylase gene is a transcriptional target of c-Myc.

Authors:  C Bello-Fernandez; G Packham; J L Cleveland
Journal:  Proc Natl Acad Sci U S A       Date:  1993-08-15       Impact factor: 11.205

6.  Sequence-specific transcriptional activation by Myc and repression by Max.

Authors:  C Amin; A J Wagner; N Hay
Journal:  Mol Cell Biol       Date:  1993-01       Impact factor: 4.272

7.  Oncogenic activity of the c-Myc protein requires dimerization with Max.

Authors:  B Amati; M W Brooks; N Levy; T D Littlewood; G I Evan; H Land
Journal:  Cell       Date:  1993-01-29       Impact factor: 41.582

8.  Expression of mad, mxi1, max and c-myc during induced differentiation of hematopoietic cells: opposite regulation of mad and c-myc.

Authors:  L G Larsson; M Pettersson; F Oberg; K Nilsson; B Lüscher
Journal:  Oncogene       Date:  1994-04       Impact factor: 9.867

9.  Gene-regulatory properties of Myc helix-loop-helix/leucine zipper mutants: Max-dependent DNA binding and transcriptional activation in yeast correlates with transforming capacity.

Authors:  D H Crouch; F Fisher; W Clark; P S Jayaraman; C R Goding; D A Gillespie
Journal:  Oncogene       Date:  1993-07       Impact factor: 9.867

10.  The c-Myc protein induces cell cycle progression and apoptosis through dimerization with Max.

Authors:  B Amati; T D Littlewood; G I Evan; H Land
Journal:  EMBO J       Date:  1993-12-15       Impact factor: 11.598

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  1 in total

1.  Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia.

Authors:  Li Wei Chang; Jacqueline E Payton; Wenlin Yuan; Timothy J Ley; Rakesh Nagarajan; Gary D Stormo
Journal:  Genome Biol       Date:  2008-02-21       Impact factor: 13.583

  1 in total

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