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Related Concept Videos

General Transcription Factors01:30

General Transcription Factors

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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...
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RNA Polymerase II Accessory Proteins02:36

RNA Polymerase II Accessory Proteins

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Proteins that regulate transcription can do so either via direct contact with RNA Polymerase or through indirect interactions facilitated by adaptors, mediators, histone-modifying proteins, and nucleosome remodelers. Direct interactions to activate transcription is seen in bacteria as well as in some eukaryotic genes. In these cases, upstream activation sequences are adjacent to the promoters, and the activator proteins interact directly with the transcriptional machinery. For example, in...
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Transcription Factors02:16

Transcription Factors

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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...
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Master Transcription Regulators02:23

Master Transcription Regulators

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Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
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Combinatorial Gene Control02:33

Combinatorial Gene Control

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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...
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Transcription Elongation Factors02:35

Transcription Elongation Factors

11.0K
Transcription elongation is a dynamic process that alters depending upon the sequence heterogeneity of the DNA being transcribed. Hence, it is not surprising that the elongation complex's composition also varies along the way while transcribing a gene.
The transcription elongation is regulated via pausing of RNA polymerase on several occasions during transcription. In bacteria, these halts are necessary because the transcription of DNA into mRNA is coupled to the translation of that mRNA...
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Related Experiment Video

Updated: Aug 6, 2025

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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Performance Prediction of Fundamental Transcriptional Programs.

Prasaad T Milner1, Ziqiao Zhang2, Zachary D Herde1

  • 1School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-2000, United States.

ACS Synthetic Biology
|March 20, 2023
PubMed
Summary
This summary is machine-generated.

Researchers developed a predictive tool for designing complex biological circuits. This method uses single-input logic operations to accurately model and predict the performance of multi-input genetic logic gates, accelerating synthetic biology advancements.

Keywords:
antirepressorsbiological circuit predictionsynthetic gene circuitssynthetic transcription factorstranscriptional programming

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Area of Science:

  • Synthetic biology
  • Genetic engineering
  • Computational biology

Background:

  • Transcriptional programming uses engineered transcription factors for cellular decision-making (e.g., Boolean logic).
  • Increasing complexity of biological circuits makes exhaustive experimental evaluation impractical.
  • A predictive tool is needed to guide and accelerate the design of transcriptional programs.

Purpose of the Study:

  • To develop and experimentally characterize a collection of network-capable single-input logical operations.
  • To use this data to model and predict the performance of more complex two-input logical operations.
  • To establish a foundation for the predictive design of increasingly complex transcriptional programs.

Main Methods:

  • Development and experimental characterization of engineered BUFFER (repressor) and NOT (antirepressor) logical operations.
  • Utilized developed metrology to model and predict the performance of compressed two-input AND and NOR gates.
  • Extended modeling to predict performance of compressed mixed phenotype logical operations (A NIMPLY B and B NIMPLY A gates).

Main Results:

  • Successfully developed and characterized a library of single-input logical operations.
  • Accurately modeled and predicted the performance of fundamental two-input compressed logical operations.
  • Demonstrated that single-input data is sufficient for predicting complex circuit performance.

Conclusions:

  • Single-input data provides a robust foundation for predicting the behavior of complex genetic logic circuits.
  • The developed metrology and predictive models accelerate the design of synthetic gene networks.
  • This work enables the predictive design of transcriptional programs with significantly greater complexity.