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Related Concept Videos

Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Transcription Factors02:16

Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
General Transcription Factors01:30

General Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
Eukaryotic Transcription Activators02:42

Eukaryotic Transcription Activators

Transcription activators are proteins that promote the transcription of genes from DNA to RNA. In most cases, these proteins contain two separate domains ‒ a domain that binds to DNA and a domain for activating transcription; however, in some cases, a single domain is responsible for both binding and activation of transcription, as seen in the glucocorticoid receptor and MyoD.
The binding domains are capable of recognizing and interacting with regulatory sequences on the DNA. These domains are...

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Related Experiment Video

Updated: Jun 12, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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Using the Tet-On system to develop a procedure for extracting transcription factor activation dynamics.

Zuyi Huang1, Colby Moya, Arul Jayaraman

  • 1Artie McFerrin Department of Chemical Engineering, Texas A&M University, 200 Jack E Brown, College Station, TX 77843-3122, USA.

Molecular Biosystems
|June 17, 2010
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Summary

Researchers developed a novel reporter system to accurately measure transcription factor dynamics. This method uses an artificial transcription factor to precisely control gene expression, advancing genomics and systems biology research.

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Area of Science:

  • Genomics
  • Systems Biology
  • Molecular Biology

Background:

  • Gene expression regulation by transcription factors is crucial in genomics and systems biology.
  • Reporter systems (GFP, luciferase) are commonly used to study transcription factor dynamics.
  • Existing methods struggle to accurately determine transcription factor dynamics due to reliance on known cellular machinery and model verification challenges.

Purpose of the Study:

  • To develop a reporter system for accurately determining transcription factor dynamics.
  • To overcome limitations of current methods that depend on cellular context and require model validation.
  • To create a controllable system for validating models of transcription factor activation.

Main Methods:

  • Developed a reporter cell line expressing GFP driven by an inducible artificial transcription factor (tTA) and a minimal promoter.
  • Activated the artificial transcription factor independently of cellular machinery using doxycycline.
  • Applied an inverse problem solution to GFP reporter data to model and validate the artificial transcription factor’s activation dynamics.

Main Results:

  • Experimental data and model predictions for the artificial transcription factor dynamics showed strong agreement.
  • Successfully demonstrated the utility of the developed reporter system and inverse problem approach.
  • Established a controllable system for direct measurement and modeling of transcription factor activation.

Conclusions:

  • The developed reporter system and inverse problem approach accurately capture transcription factor dynamics.
  • This method provides a reliable way to validate models used in systems biology.
  • Future applications include characterizing the dynamics of currently uncharacterized transcription factors.