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Competing ParA Structures Space Bacterial Plasmids Equally over the Nucleoid

Lookup NU author(s): Florian Szardenings, Professor Kenn Gerdes

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2014 Ietswaart et al. Low copy number plasmids in bacteria require segregation for stable inheritance through cell division. This is often achieved by a parABC locus, comprising an ATPase ParA, DNA-binding protein ParB and a parC region, encoding ParB-binding sites. These minimal components space plasmids equally over the nucleoid, yet the underlying mechanism is not understood. Here we investigate a model where ParA-ATP can dynamically associate to the nucleoid and is hydrolyzed by plasmid-associated ParB, thereby creating nucleoid-bound, self-organizing ParA concentration gradients. We show mathematically that differences between competing ParA concentrations on either side of a plasmid can specify regular plasmid positioning. Such positioning can be achieved regardless of the exact mechanism of plasmid movement, including plasmid diffusion with ParA-mediated immobilization or directed plasmid motion induced by ParB/parC-stimulated ParA structure disassembly. However, we find experimentally that parABC from Escherichia coli plasmid pB171 increases plasmid mobility, inconsistent with diffusion/immobilization. Instead our observations favor directed plasmid motion. Our model predicts less oscillatory ParA dynamics than previously believed, a prediction we verify experimentally. We also show that ParA localization and plasmid positioning depend on the underlying nucleoid morphology, indicating that the chromosomal architecture constrains ParA structure formation. Our directed motion model unifies previously contradictory models for plasmid segregation and provides a robust mechanistic basis for self-organized plasmid spacing that may be widely applicable.


Publication metadata

Author(s): Ietswaart R, Szardenings F, Gerdes K, Howard M

Publication type: Article

Publication status: Published

Journal: PLoS Computational Biology

Year: 2014

Volume: 10

Issue: 12

Online publication date: 18/12/2014

Acceptance date: 28/10/2014

Date deposited: 23/11/2017

ISSN (print): 1553-734X

ISSN (electronic): 1553-7358

Publisher: Public Library of Science

URL: https://doi.org/10.1371/journal.pcbi.1004009

DOI: 10.1371/journal.pcbi.1004009

PubMed id: 25521716


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