Solution structure of the Mu end DNA-binding ibeta subdomain of phage Mu transposase: modular DNA recognition by two

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S Schumacher1, R T Clubb, M Cai

  • 1Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA.

The EMBO Journal
|February 21, 1998
PubMed

Insights

The phage Mu transposase (MuA) end-binding domain has a modular structure. Its two subdomains cooperate to bind DNA with higher affinity, enabling precise Mu genome integration.

Area of Science:

  • Molecular Biology
  • Structural Biology
  • Genetics

Background:

  • Phage Mu transposase (MuA) is crucial for integrating the Mu genome into host DNA.
  • MuA assembles higher-order nucleoprotein complexes at the Mu genome ends.
  • Understanding MuA's DNA-binding domain (Ibetagamma) is key to its function.

Purpose of the Study:

  • To determine the three-dimensional solution structure of the MuA Ibeta subdomain.
  • To elucidate the structure-function relationship of the MuA Ibetagamma end-binding domain.
  • To investigate the DNA-binding mechanism and cooperative interactions of MuA subdomains.

Main Methods:

  • Multidimensional NMR spectroscopy was used to determine the Ibeta subdomain structure.
  • DNA-binding assays were performed to assess subdomain and whole domain affinities.
  • Structural comparisons were made with other helix-turn-helix (HTH) DNA-binding proteins.

Main Results:

  • The Ibeta subdomain structure comprises five alpha-helices, including an HTH motif.
  • Each subdomain (Ibeta and Igamma) binds to a specific half of the Mu DNA recognition site.
  • The complete Ibetagamma domain exhibits 100- to 1000-fold higher DNA-binding affinity than individual subdomains, indicating cooperativity.

Conclusions:

  • The MuA end DNA-binding domain possesses a modular organization.
  • Cooperative binding of the Ibeta and Igamma subdomains enhances Mu DNA recognition and integration.
  • A model for the Ibetagamma domain-DNA interaction is proposed based on structural and binding data.

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