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Single-molecule analysis of transcription factor binding at transcription sites in live cells
Open accessAbstract
Although numerous live-cell measurements have shown that transcription factors (TFs) bind chromatin transiently, no measurements of transient binding have been reported at the endogenous response elements (REs) where transcription is normally induced. Here we show that at endogenous REs the transcriptionally productive specific binding of two TFs, p53 and the glucocorticoid receptor (GR), is transient. We also find that the transient residence times of GR at endogenous REs are roughly comparable to those at an artificial, multi-copy array of gene regulatory sites, supporting the use of multi-copy arrays for live-cell analysis of transcription. Finally, we find that at any moment only a small fraction of TF molecules are engaged in transcriptionally productive binding at endogenous REs. The small fraction of bound factors provides one explanation for gene bursting and it also indicates that REs may often be unoccupied, resulting in partial responses to transcriptional signals. Despite numerous previous studies, the nature of the interaction of transcription factors (TF) with their endogenous response elements (REs) has remained unclear. Here the authors characterize the binding of p53 and glucocorticoid receptor to their endogenous REs and find that transcriptionally productive interactions are transient and involve only a small fraction of cellular TF molecules.
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Crystal Structure of a p53 Tumor Suppressor-DNA Complex: Understanding Tumorigenic Mutations
Cho, Y., Gorina, S., Jeffrey, P. D., & Pavletich, N. P. (1994) · Science · doi:10.1126/science.8023157 · Cited by 2,551
The quantitative proteome of a human cell line
Beck, M., Schmidt, A., Malmstroem, J., Claassen, M., Ori, A., Szymborska, A., Herzog, F., Rinner, O., Ellenberg, J., & Aebersold, R. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.82 · Cited by 816
The glucocorticoid receptor: rapid exchange with regulatory sites in living cells
McNally, J. G., Müller, W. G., Walker, D., Wolford, R., & Hager, G. L. (2000) · Science · doi:10.1126/science.287.5456.1262 · Cited by 802
Transcriptional Regulation by P53
Beckerman, R., & Prives, C. (2010) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a000935 · Cited by 569
Voss, T. C., Schiltz, R. L., Sung, M.-H., Yen, P. M., Stamatoyannopoulos, J. A., Biddie, S. C., Johnson, T. A., Miranda, T. B., John, S., & Hager, G. L. (2011) · Cell · doi:10.1016/j.cell.2011.07.006 · Cited by 307
Li, J. J., Bickel, P. J., & Biggin, M. D. (2014) · PeerJ · doi:10.7717/peerj.270 · Cited by 279
A threshold mechanism mediates p53 cell fate decision between growth arrest and apoptosis.
Kracikova, M., Akiri, G., George, A., Sachidanandam, R., & Aaronson, S. A. (2013) · Cell Death & Differentiation · doi:10.1038/cdd.2012.155 · Cited by 261
Lickwar, C. R., Mueller, F., Hanlon, S. E., McNally, J. G., & Lieb, J. D. (2012) · Nature · doi:10.1038/nature10985 · Cited by 241
Self-citationBursts and pulses: Insights from single cell studies into transcriptional mechanisms
Chubb, J. R., & Liverpool, T. B. (2010) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2010.06.009 · Cited by 91
Measuring Chromatin Interaction Dynamics on the Second Time Scale at Single-Copy Genes
Poorey, K., Viswanathan, R., Carver, M. N., Karpova, T. S., Cirimotich, S. M., McNally, J. G., Bekiranov, S., & Auble, D. T. (2013) · Science · doi:10.1126/science.1242369 · Cited by 88
Self-citation
Research works printed but not linked: 23
- Hager, G. L., McNally, J. G. & Misteli, T. Transcription dynamics. Mol. Cell 35, 741–753 (2009). · DOI · Paper page
- Mueller, F., Stasevich, T. J., Mazza, D. & McNally, J. G. Quantifying transcription factor kinetics: at work or at play? Crit. Rev. Biochem. Mol. Biol. 48, 492–514 (2013). · DOI
- Bosisio, D. et al. A hyper-dynamic equilibrium between promoter-bound and nucleoplasmic dimers controls NF-kappaB-dependent gene activity. EMBO J. 25, 798–810 (2006). · DOI · Paper page
- Sharp, Z. D. et al. Estrogen-receptor-alpha exchange and chromatin dynamics are ligand- and domain-dependent. J. Cell Sci. 119, 4101–4116 (2006). · DOI
- Karpova, T. S. et al. Concurrent fast and slow cycling of a transcriptional activator at an endogenous promoter. Science 319, 466–469 (2008). · DOI
- Ghamari, A. et al. In vivo live imaging of RNA polymerase II transcription factories in primary cells. Genes Dev. 27, 767–777 (2013). · DOI
- Cisse, I. I. et al. Real-time dynamics of RNA polymerase II clustering in live human cells. Science 341, 664–667 (2013). · DOI · Paper page
- Labeur, M. & Holsboer, F. Molecular mechanisms of glucocorticoid receptor signaling. Medicina (B. Aires) 70, 457–462 (2010).
- Oakley, R. H. & Cidlowski, J. A. The biology of the glucocorticoid receptor: new signaling mechanisms in health and disease. J. Allergy Clin. Immunol. 132, 1033–1044 (2013). · DOI · Paper page
- Los, G. V. et al. HaloTag: a novel protein labeling technology for cell imaging and protein analysis. ACS Chem. Biol. 3, 373–382 (2008). · DOI · Paper page
- Mazza, D., Abernathy, A., Golob, N., Morisaki, T. & McNally, J. G. A benchmark for chromatin binding measurements in live cells. Nucleic Acids Res. 40, e119 (2012). · DOI · Paper page
- Kaeser, M. D. & Iggo, R. D. Chromatin immunoprecipitation analysis fails to support the latency model for regulation of p53 DNA binding activity in vivo. Proc. Natl Acad. Sci. USA 99, 95–100 (2002). · DOI · Paper page
- Wang, Y., Blandino, G., Oren, M. & Givol, D. Induced p53 expression in lung cancer cell line promotes cell senescence and differentially modifies the cytotoxicity of anti-cancer drugs. Oncogene 17, 1923–1930 (1998). · DOI
- Tokunaga, M., Imamoto, N. & Sakata-Sogawa, K. Highly inclined thin illumination enables clear single-molecule imaging in cells. Nat. Methods 5, 159–161 (2008). · DOI · Paper page
- Becker, M. et al. Dynamic behavior of transcription factors on a natural promoter in living cells. EMBO Rep. 3, 1188–1194 (2002). · DOI · Paper page
- Chen, J. Y., Funk, W. D., Wright, W. E., Shay, J. W. & Minna, J. D. Heterogeneity of transcriptional activity of mutant p53 proteins and p53 DNA target sequences. Oncogene 8, 2159–2166 (1993).
- Ojasoo, T., Doré, J. C., Gilbert, J. & Raynaud, J. P. Binding of steroids to the progestin and glucocorticoid receptors analyzed by correspondence analysis. J. Med. Chem. 31, 1160–1169 (1988). · doi:10.1021/jm00401a015
- Stavreva, D. A., Müller, W. G., Hager, G. L., Smith, C. L. & McNally, J. G. Rapid glucocorticoid receptor exchange at a promoter is coupled to transcription and regulated by chaperones and proteasomes. Mol. Cell. Biol. 24, 2682–2697 (2004). · DOI · Paper page
- Müller, W. G. et al. Organization of chromatin and histone modifications at a transcription site. J. Cell Biol. 177, 957–967 (2007). · DOI
- Perlmann, T., Eriksson, P. & Wrange, O. Quantitative analysis of the glucocorticoid receptor-DNA interaction at the mouse mammary tumor virus glucocorticoid response element. J. Biol. Chem. 265, 17222–17229 (1990). · DOI
- Stasevich, T. J. & McNally, J. G. Assembly of the transcription machinery: ordered and stable, random and dynamic, or both? Chromosoma 120, 533–545 (2011). · DOI
- John, S. et al. Chromatin accessibility pre-determines glucocorticoid receptor binding patterns. Nat. Genet. 43, 264–268 (2011). · DOI · Paper page
- Müller, W. G., Walker, D., Hager, G. L. & McNally, J. G. Large-scale chromatin decondensation and recondensation regulated by transcription from a natural promoter. J. Cell Biol. 154, 33–48 (2001). · DOI · Paper page
Cited by
Steroid Receptors Reprogram FoxA1 Occupancy through Dynamic Chromatin Transitions
Swinstead, E. E., Miranda, T. B., Paakinaho, V., Baek, S., Goldstein, I., Hawkins, M., Karpova, T. S., Ball, D., Mazza, D., Lavis, L. D., et al. (2016) · Cell · doi:10.1016/j.cell.2016.02.067 · Cited by 312
Self-citationTranscription factor assisted loading and enhancer dynamics dictate the hepatic fasting response
Goldstein, I., Baek, S., Presman, D. M., Paakinaho, V., Swinstead, E. E., & Hager, G. L. (2017) · Genome Research · doi:10.1101/gr.212175.116 · Cited by 121
Swinstead, E. E., Paakinaho, V., Presman, D. M., & Hager, G. L. (2016) · BioEssays · doi:10.1002/bies.201600137 · Cited by 100
A matter of time: Using dynamics and theory to uncover mechanisms of transcriptional bursting
Lammers, N. C., Kim, Y. J., Zhao, J., & Garcia, H. G. (2020) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2020.08.001 · Cited by 99
Dynamic enhancer function in the chromatin context
Goldstein, I., & Hager, G. L. (2018) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1390 · Cited by 25
Metadata
- Authors
- Morisaki, T., Müller, W. G., Golob, N., Mazza, D., & McNally, J. G.
- Venue
- Nature Communications
- Published
- 2014-07-18
- Volume
- 5
- Issue
- 1
- Pages
- 4456-4456
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W1980586499
- Cited by
- 168
- References
- 10
- FWCI
- 7.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
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