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Related Concept Videos

Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Transcription Factors02:16

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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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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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Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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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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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
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Human transcription factor protein interaction networks.

Helka Göös1,2, Matias Kinnunen1, Kari Salokas1

  • 1Institute of Biotechnology, HiLIFE, University of Helsinki, Helsinki, Finland.

Nature Communications
|February 10, 2022
PubMed
Summary
This summary is machine-generated.

This study maps human transcription factor (TF) interactions using BioID and AP-MS, revealing dynamic protein networks. Findings highlight TF roles in RNA splicing and chromatin remodeling, and uncover novel Nuclear Factor 1 (NFI) pathway cross-talk.

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Area of Science:

  • Molecular Biology
  • Genetics
  • Biochemistry

Background:

  • Transcription factors (TFs) are crucial regulators of gene expression.
  • Understanding TF protein-protein interactions is key to deciphering transcriptional regulation.
  • Existing interaction data for human TFs is limited.

Purpose of the Study:

  • To comprehensively identify and characterize protein-protein interactions of human TFs.
  • To explore the functional implications of TF interaction networks.
  • To investigate TF interactions with basal transcription machinery and identify novel signaling pathways.

Main Methods:

  • Proximity-dependent biotinylation (BioID) was employed to capture transient TF interactions.
  • Affinity purification mass spectrometry (AP-MS) was used for high-confidence interaction validation.
  • Clustering and correlation analyses were performed on identified TF interaction data.

Main Results:

  • 6703 and 1536 protein-protein interactions were identified for 109 human TFs via BioID and AP-MS, respectively.
  • BioID revealed a higher number of high-confidence interactions, emphasizing the dynamic nature of TF binding.
  • Subgroups of TFs linked to RNA splicing and chromatin remodeling were identified, along with 202 TF-TF interactions, including 118 with Nuclear Factor 1 (NFI) family members.

Conclusions:

  • This study provides an extensive resource of human TF interactions, revealing novel insights into transcriptional regulation.
  • The findings suggest uncharacterized cross-talk between NFI signaling and other TF pathways.
  • TF interactions with basal transcription machinery primarily involve TFIID and SAGA complexes, offering a foundation for future research.