New Journal of Physics (Jan 2018)

Looping and clustering model for the organization of protein-DNA complexes on the bacterial genome

  • Jean-Charles Walter,
  • Nils-Ole Walliser,
  • Gabriel David,
  • Jérôme Dorignac,
  • Frédéric Geniet,
  • John Palmeri,
  • Andrea Parmeggiani,
  • Ned S Wingreen,
  • Chase P Broedersz

DOI
https://doi.org/10.1088/1367-2630/aaad39
Journal volume & issue
Vol. 20, no. 3
p. 035002

Abstract

Read online

The bacterial genome is organized by a variety of associated proteins inside a structure called the nucleoid. These proteins can form complexes on DNA that play a central role in various biological processes, including chromosome segregation. A prominent example is the large ParB-DNA complex, which forms an essential component of the segregation machinery in many bacteria. ChIP-Seq experiments show that ParB proteins localize around centromere-like parS sites on the DNA to which ParB binds specifically, and spreads from there over large sections of the chromosome. Recent theoretical and experimental studies suggest that DNA-bound ParB proteins can interact with each other to condense into a coherent 3D complex on the DNA. However, the structural organization of this protein-DNA complex remains unclear, and a predictive quantitative theory for the distribution of ParB proteins on DNA is lacking. Here, we propose the looping and clustering model, which employs a statistical physics approach to describe protein-DNA complexes. The looping and clustering model accounts for the extrusion of DNA loops from a cluster of interacting DNA-bound proteins that is organized around a single high-affinity binding site. Conceptually, the structure of the protein-DNA complex is determined by a competition between attractive protein interactions and loop closure entropy of this protein-DNA cluster on the one hand, and the positional entropy for placing loops within the cluster on the other. Indeed, we show that the protein interaction strength determines the ‘tightness’ of the loopy protein-DNA complex. Thus, our model provides a theoretical framework for quantitatively computing the binding profiles of ParB-like proteins around a cognate ( parS ) binding site.

Keywords