4.6 Article

Mechanistic Analysis of the VirA Sensor Kinase in Agrobacterium tumefaciens Using Structural Models

期刊

FRONTIERS IN MICROBIOLOGY
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2022.898785

关键词

VirA; two-component system; AlphaFold; Agrobacterium tumefaciens; histidine kinase

资金

  1. The University of Richmond
  2. Virginia Commonwealth University
  3. Jeffress Memorial Trust Awards [PTE: 29502]

向作者/读者索取更多资源

This study utilizes molecular modeling technology to investigate the role of VirA protein in Agrobacterium tumefaciens pathogenesis. The research finds that the mechanism of VirA's response to host signals is still not fully understood, but the structural model generated by AlphaFold provides a basis for further study. By analyzing the structure and function of a specific region of VirA, this study proposes a model for VirA signal reception and explores potential phenol-binding sites of VirA, further deepening our understanding of signal perception in A. tumefaciens.
Agrobacterium tumefaciens pathogenesis of plants is initiated with signal reception and culminates with transforming the genomic DNA of its host. The histidine sensor kinase VirA receives and reacts to discrete signaling molecules for the full induction of the genes necessary for this process. Though many of the components of this process have been identified, the precise mechanism of how VirA coordinates the response to host signals, namely phenols and sugars, is unknown. Recent advances of molecular modeling have allowed us to test structure/function predictions and contextualize previous experiments with VirA. In particular, the deep mind software AlphaFold has generated a structural model for the entire protein, allowing us to construct a model that addresses the mechanism of VirA signal reception. Here, we deepen our analysis of the region of VirA that is critical for phenol reception, model and probe potential phenol-binding sites of VirA, and refine its mechanism to strengthen our understanding of A. tumefaciens signal perception.

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