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Journal of Biochemistry Advance Access published online on July 25, 2007
Journal of Biochemistry, doi:10.1093/jb/mvm151
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© 2007 The Japanese Biochemical Society

An analytical rate expression for the kinetics of gene transcription mediated by dimeric transcription factors

Hsih-Te Yang1,3, Chao-Ping Hsu2 and Ming-Jing Hwang3,*

1Institute of Biochemistry and Molecular Biology, National Yang-Ming University, Taipei, Taiwan
2Institute of Chemistry, Academia Sinica, Taipei, Taiwan
3Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan

*Correspondence: Ming-Jing Hwang, Ph.D. Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan, tel: +886-2-2789-9033 fax: +886-2-2788-7641, email: mjhwang{at}ibms.sinica.edu.tw

Received April 17, 2007; Accepted June 1, 2007


  Abstract

To model gene transcription kinetics, empirical fitting with the Hill function or S-system is often used. In this study, we derived an analytical expression for gene transcription rates in a manner similar to that developed for enzyme kinetics to describe the kinetics of gene transcription mediated by dimeric transcription factors such as Gcn4p, a Saccharomyces cerevisiae master gene regulator. We showed that the analytical rate expression and its parameters estimated from several sets of experimental data could accurately reproduce the experimentally measured promoter binding activity of Gcn4p. Furthermore, the analytical rate expression allowed us to derive analytically, rather than fit empirically, the parameters of the Hill function and S-system for use in modeling transcription kinetics. We found that a plot of gene transcription rate against Gcn4p concentration gave a sigmoidal dose-response curve with a positive cooperativity Hill coefficient (~1.25), in accordance with previous experimental findings on the promoter binding of dimeric transcription factors. The characteristics of the dose-response curve around the estimated cellular Gcn4p concentration suggest that transcription regulation is efficiently controlled under physiological conditions. This work is a useful initial step towards analytically modeling and simulating complicated gene transcription networks.

Key Words: Enzyme kinetics, Hill function, gene transcription modeling, S-system, transcription kinetics


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